Drawing on more than two decades of experience in customer experience technology, Andy shares lessons from building cloud contact center platforms and developing AI-enabled solutions. He explains how AI can improve the customer journey, support human agents, streamline interactions, and make sophisticated customer experience technology more accessible to mid-market businesses.

The conversation also explores AI agents, knowledge bases, retrieval-augmented generation (RAG), real-time voice interactions, shared AI agents, and the architectural decisions that can determine whether an AI platform remains adaptable as technology evolves.

Andy also challenges the narrative that AI should simply replace people. He discusses the risks of overhyping automation, why human oversight remains essential, and how business leaders can identify practical opportunities for AI adoption without getting caught up in the latest headlines.

• How AI is transforming customer experience and contact center technology.
• The three stages of the customer journey and where AI can make a difference.
• Why an integrated approach to AI is more valuable than implementing disconnected tools.
• How knowledge bases, RAG, and AI agents can improve customer interactions.
• Why human involvement remains important in AI-powered customer service.
• How shared AI agents can support multiple businesses while reducing costs.
• The importance of natural conversations, low latency, and context-aware AI.
• Why adaptable architecture matters in a rapidly evolving AI landscape.
• What companies can learn from highly publicized attempts to replace workers with AI.
• Where AI adoption may be underestimated, including legal and government applications.
• How mid-market businesses can identify their biggest problems and evaluate AI solutions.
• Why proof-of-concept projects can help leaders validate value before committing to a larger investment.

00:00 Introduction to Andy Bird and AI in customer experience 01:54 Andy’s career journey into product and technology leadership 04:56 Building AI-powered customer experience platforms 05:10 The three stages of the customer journey 06:39 Why customer experience technology needs a holistic approach 08:22 Introducing Izzy and customizable AI agents 10:00 Identifying the ideal customers for AI-powered CX 11:48 Self-service AI and keeping humans in the loop 12:18 How business process outsourcing is evolving 12:48 Understanding shared AI agents 14:13 Improving the end-customer experience 15:00 Natural conversations and knowledge-grounded AI 19:02 Latency, transparency, and the AI customer experience 22:20 Choosing AI models based on performance, cost, and use case 23:43 Optimizing costs while improving customer satisfaction 24:07 Why legacy systems and architectural decisions create challenges 28:32 The most overhyped and underrated areas of AI 29:16 Why replacing people with AI can backfire 31:00 Why human support still matters in customer service 32:06 Practical advice for business leaders adopting AI 33:03 Start with your three biggest business problems 34:21 Finding a trusted partner and validating AI solutions

“My job is optimization of cost for my client.”

Andy’s perspective is that AI should improve the economics of customer experience while supporting better service, rather than simply shifting costs or eliminating jobs.

“AI is moving so rapidly you have to be able to adapt.”

The technology landscape changes quickly, making flexibility an important consideration when choosing models, vendors, and platform architectures.

“You identify your top three problems that you have.”

His advice to business leaders is to begin with the problems that matter most, research solutions that address them, and validate results before expanding adoption.

Andy Bird is the CPTO of IzzyLabs, a company developing AI-powered customer experience solutions through its Izzy platform. He brings more than two decades of experience in customer experience technology, product management, and platform development.

His work centers on customer satisfaction, practical AI adoption, cost optimization, and using technology to strengthen the capabilities of people.

• Company: IzzyLabs
• Website: https://izzyops.ai
• Email: bird.andy@gmail.com
• LinkedIn: https://www.linkedin.com/in/birdandy/

• Website: https://leadingaiagility.com
• LinkedIn: https://www.linkedin.com/in/mattzembruski/
• Email: matt@leadingaiagility.com
• Phone / Text / WhatsApp: +1 978-618-5778

In this episode of the AI Accelerator Podcast, Matt Zembruski speaks with Cliff Berg, managing partner of Agile 2 Academy, founder of the Agile 2 initiative, and architect of the Throughline AI strategic execution platform.

With 30 years of experience studying how organizations operate, Cliff shares why traditional planning and task management can get in the way of agility, and how AI can help leaders connect strategy, goals, and execution.

The conversation explores how AI agents become more effective when they understand an organization's intentions, why leaders should give teams problems to solve rather than simply assigning tasks, and how businesses can introduce AI while keeping humans involved in important decisions.

• Why organizational agility depends on leadership behavior, not just frameworks
• The origins of Throughline and its AI-powered strategic execution platform
• Connecting strategy, planning, and daily work
• Why solving problems can be more effective than assigning tasks
• Lessons from SpaceX's approach to rapid experimentation and execution
• How psychological safety develops when teams are empowered to try things
• Why AI agents need access to organizational goals, intentions, and context
• The importance of human oversight in AI-powered workflows
• How AI can identify dependencies, delays, risks, and strategic misalignment
• Building roadmaps around outcomes instead of excessive task tracking
• Practical ways to identify low-hanging fruit for AI adoption
• Using AI to review subcontract agreements and save time
• Helping mid-market companies connect AI adoption to long-term business strategy

00:00 Introduction to the AI Accelerator Podcast 

00:56 Meet Cliff Berg: Agile 2 and Throughline AI 

02:28 Why Cliff Built an AI-Powered Execution Platform 

03:45 Connecting Strategy, Planning, and Execution 

04:51 Why Traditional Task Planning Can Get in the Way 

05:46 The Problem-Centric Approach to Work 

06:43 What Organizations Can Learn From SpaceX 

08:02 Empowering Teams and Building Psychological Safety 

09:54 Giving AI Agents the Context They Need 

10:30 Understanding Organizational Intentions 

11:56 Why Strategic Context Matters for AI Deployments 

13:38 How Throughline Agents Understand and Prioritize Work 

14:52 Keeping Humans in the Loop 

15:45 Why AI Output Quality Matters More Than Speed 

17:50 Connecting Strategy to Everyday Execution 

18:28 Defining Mission, Vision, and Strategy 

19:58 Building Flexible Roadmaps and Goals 

21:37 Using AI to Identify Dependencies and Misalignment 

22:20 Advice for Business Leaders Starting With AI 

23:44 Finding Practical AI Use Cases 

24:11 Automating Subcontract Reviews With AI 

25:30 Moving From Quick Wins to Strategic AI Adoption 

26:18 How to Connect With Cliff Berg

"The tools we have make it really hard to do all this."

"What we need is a tool that actually creates this line of sight from strategy through planning and execution."

"The behavioral norm there is to give people problems to solve, not tasks to do."

"What we want is good output. We want aligned output."

"The AI cannot say that's done."

Cliff Berg is the managing partner of Agile 2 Academy, founder of the Agile 2 movement, and architect of the Throughline AI agent strategic execution platform.

He has spent approximately 30 years studying how organizations operate and helping businesses improve agility, planning, and execution. Cliff previously co-founded Digital Focus, a technology company that grew from two people to 200 employees in five years before being acquired in 2006.

In 2019, he launched the Agile 2 initiative and became the lead author of Agile 2: The Next Iteration of Agile, examining why conventional Agile approaches can fail to produce genuine organizational agility.

Cliff has led more than 10 Agile and DevOps transformations, authored six books, and worked with executives and delivery teams to address organizational and technical challenges. His work combines software engineering, systems thinking, leadership, and AI to help organizations connect strategy with execution.

Website: https://www.throughlineai.net 

LinkedIn: https://www.linkedin.com/in/cliffberg/

Website: https://leadingaiagility.com 

LinkedIn: https://www.linkedin.com/in/mattzembruski/ 

Email: matt@leadingaiagility.com 

Phone / Text / WhatsApp: +1 978-618-5778

In this episode of the AI Accelerator Podcast, Matt Zembruski sits down with Melissa Reeve, creator of the Hyperadaptive Model and author of Hyperadaptive: Re-wiring the Enterprise to Become AI-Native, to explore how organizations can move beyond AI pilots and build the systems, governance, and human capabilities needed to continuously adapt.

Drawing on 25 years of experience as an executive and Agile thought leader, including serving as the first VP of Marketing at Scaled Agile and co-founding the Agile Marketing Alliance, Melissa shares a practical, human-centered approach to enterprise AI transformation.

The conversation explores the five stages of becoming AI-native, dynamic governance, AI Impact Hubs, the activation layer that can help organizations turn AI experiments into results, and why the companies succeeding with AI may be the ones that double down on what makes humans uniquely valuable.

In This Episode, Melissa Reeve Discusses:

• The Hyperadaptive Model for AI transformation
• The five stages of becoming an AI-native organization
• Why AI pilots often fail to translate into enterprise results
• The importance of an organizational activation layer
• Dynamic governance in an AI-powered enterprise
• How AI changes traditional organizational boundaries
• Building AI Impact Hubs across departments
• How HR, Finance, and other functions may evolve alongside AI
• Upskilling and reskilling employees for AI-plus-human roles
• Lessons from Greenfield Savings Bank's AI transformation
• Why AI adoption is more than a technology or licensing decision
• How leaders can identify pain points and match them with AI solutions
• Why successful AI organizations may need to double down on human capabilities
• Rewiring traditional organizations to become more adaptive

Chapters

00:00 Introduction 00:56 Meet Melissa Reeve, Creator of the Hyperadaptive Model 01:18 The Five Stages of Becoming AI-Native 02:02 Melissa's Journey From Japan and Toyota to Agile Transformation 06:00 From Process Excellence to AI Transformation 12:31 Breaking Organizational Silos With AI 13:00 Building AI Impact Hubs 13:24 Upskilling and Reskilling for an AI-Plus-Human Future 21:29 Why AI Success Requires Doubling Down on What Makes Us Human 26:20 A Real-World AI Transformation Story: Greenfield Savings Bank 27:00 Moving From AI Technology to Human-Centered Transformation

Key Learnings

1. Becoming AI-native requires more than adding AI tools

Melissa's Hyperadaptive Model focuses on the organizational transformation required to become AI-native. The challenge isn't simply choosing an AI model or purchasing licenses. Organizations need to rethink how their processes, people, governance, and operating systems work together as AI becomes part of everyday work.

2. AI transformation requires an activation layer

One of the central ideas discussed in the episode is the need for an activation layer between AI pilots and actual business results. Organizations can experiment with AI, run pilots, and demonstrate impressive technology. But without the systems and organizational mechanisms required to activate those capabilities, pilots can remain disconnected from meaningful outcomes.

3. AI breaks down traditional organizational boundaries

AI doesn't necessarily stay inside traditional departmental boxes. As Melissa explains, people increasingly need to work across what she calls their "adjacent competencies." Instead of thinking only about what HR does or what Finance does, organizations need to ask how AI is changing the work, roles, and capabilities within each function.

4. AI Impact Hubs can help organizations manage this transition

Melissa describes the concept of AI Impact Hubs as a way to understand how AI and automation are affecting different parts of an organization.

These hubs can examine questions such as:

• How is automation changing work within Finance?
• How are roles evolving?
• Can frontline employees be upskilled or reskilled?
• What new AI-plus-human roles could emerge?
• How can organizations support employees through the transition?

This creates a more systematic approach to organizational adaptation.

5. AI adoption should start with real pain points

The Greenfield Savings Bank example illustrates a practical approach to AI adoption. Rather than treating AI as simply a technology rollout, the CEO selected one or two people from each department to identify significant pain points and then match an AI solution to those problems. The shift was from focusing primarily on licensing and deploying technology to focusing on the people, problems, and outcomes that AI could actually improve.

6. The future isn't only about AI doing more

A major theme of the conversation is that organizations succeeding with AI may be the ones that double down on what makes humans most valuable. As automation changes tasks and workflows, organizations need to think carefully about what humans should continue doing, what new capabilities employees need, and how people and AI can work together.

💬 Melissa Reeve's Key Insights

"The future belongs to those who are willing to rewire."

"There's a real mindset shift that needs to happen."

"How is automation impacting the folks in Finance? What are those roles evolving into?"

"The goal of this Impact Hub... is looking at the impact."

"The companies succeeding with AI are the ones that are doubling down on what makes us the most human."

About Melissa Reeve

Melissa Reeve is the creator of the Hyperadaptive Model and author of Hyperadaptive: Re-wiring the Enterprise to Become AI-Native.

She brings more than 25 years of experience as an executive and Agile thought leader. Her work includes studying the Toyota Production System in Japan, serving as the first VP of Marketing at Scaled Agile, and co-founding the Agile Marketing Alliance.

Melissa developed the Hyperadaptive Model to help organizations combine process excellence, systems thinking, and the human side of AI integration. Her research-backed approach focuses on helping companies move from stalled AI pilots toward becoming truly AI-native and continuously adaptive organizations.

She lives in Boulder, Colorado, with her husband, dogs, and chickens.

Follow Melissa Reeve

Website: http://hyperadaptive.solutions LinkedIn: https://www.linkedin.com/in/melissamreeve/

Follow Matt Zembruski

Website: https://leadingaiagility.com LinkedIn: https://www.linkedin.com/in/mattzembruski/ Email: matt@leadingaiagility.com Phone / Text / WhatsApp: +1 978-618-5778

In this episode of the AI Accelerator Podcast, Matt Zembruski sits down with Andre Cuenin, Chief Revenue Officer at SolarWinds, to explore how AI is changing enterprise workflows, customer preparation, data utilization, and the future of business.

With more than 20 years of experience driving revenue at technology companies including Veracode, Rapid7, Cherwell Software, Stratavia, and CA, Andre brings a practical revenue and leadership perspective to the AI transformation happening across organizations.

The conversation explores the difference between simply optimizing existing processes and using AI to create entirely new ways of solving business problems.

In This Episode, Andre Cuenin Discusses:

• How AI can optimize existing business workflows
• Using AI to prepare for customer meetings
• How AI agents can connect information across CRM, finance, and support systems
• The importance of data breadth and quality when implementing AI
• Why organizations need to think beyond individual employee productivity
• How leaders should approach AI adoption and transformation
• The difference between AI optimization and AI-driven opportunity
• Why AI may represent one of the most significant technology shifts of our lifetime
• How companies can stay competitive as AI adoption accelerates
• What separates organizations that successfully leverage AI from those that risk being left behind

Chapters

00:00 Introduction 01:03 Meet Andre Cuenin, CRO at SolarWinds 01:15 What AI Is Really Doing to Jobs Today 06:14 Applying AI to Optimize Existing Workflows 06:37 Using an AI Agent to Prepare for Customer Meetings 07:08 The Optimization Path for AI 10:50 Connecting AI to the Breadth of Enterprise Data 11:15 Data Quality and Building Better AI Workflows 14:58 Andre's Recommendations for Business Leaders 19:03 AI as a Major Technology Shift 19:48 Two Types of Companies in the Future 20:00 Optimization vs. New Business Opportunities 21:00 Staying Competitive in an AI-Driven Market

Key Learnings

1. Start with optimization

Andre describes one practical path for AI adoption as optimization: take something the organization already does and use AI to perform it more effectively and efficiently.

2. AI agents can connect information across the organization

One of the biggest opportunities comes from connecting AI to the information already distributed throughout an organization. Customer information may exist across multiple systems. An AI agent can help bring that information together so employees don't have to manually search through different platforms to understand the full customer story.

3. Data breadth and quality matter

Connecting an AI system to enterprise data is only part of the challenge. Organizations also need to consider whether the AI has access to the breadth of data that actually matters and how they can perform appropriate quality checks on that information. Better AI outcomes require organizations to think carefully about their underlying data.

4. AI creates opportunities beyond optimization

Andre describes a distinction between using AI to do existing work better and using AI to solve problems in completely different ways. Optimization can make existing processes faster and more efficient. The larger opportunity may come from asking: What could we do differently if AI fundamentally changed how this problem was solved?

5. AI could reshape competitive advantage

Andre believes AI represents one of the most significant technology shifts many people will experience during their lifetime. For business leaders, the challenge is not simply understanding AI. It is figuring out how to leverage it while maintaining competitiveness.mAs AI adoption accelerates, companies that successfully integrate AI into both optimization and new opportunities may gain an advantage over organizations that fail to adapt.

💬 Andre Cuenin's Key Insights

"You do what you have done before, but more effectively, more efficiently."

"A great example of doing something I did before, but much more effectively and efficiently."

"How can I leverage it and also make sure I stay competitive?"

"There’s gonna be two types of companies in the future."

About Andre Cuenin

Andre Cuenin serves as Chief Revenue Officer at SolarWinds, where he oversees revenue generation relating to the company's observability, database, and service management solutions.

He brings more than 20 years of experience driving revenue growth strategies at technology companies including Veracode, Rapid7, Cherwell Software, Stratavia, and CA.

Throughout his career, Andre has focused on building cultures of trust, candor, teamwork, and sustainable customer outcomes. He holds a Bachelor of Computer Science from the University of Applied Sciences and Arts of Western Switzerland and an MBA from Strathclyde University in Glasgow.

Follow Andre Cuenin

Website: https://www.solarwinds.com/ LinkedIn: https://www.linkedin.com/in/andrecuenin/

Follow Matt Zembruski

Website: https://leadingaiagility.com LinkedIn: https://www.linkedin.com/in/mattzembruski/ Email: matt@leadingaiagility.com Phone / Text / WhatsApp: +1 978-618-5778

In this episode of the AI Accelerator Podcast, Matt Zembruski sits down with Swathi Young, technology executive, AI strategist, and award-winning CTO, to explore what organizations need to do to turn AI pilots into production-ready solutions.

With more than 20 years of experience in enterprise technology and over 100 AI, data, and transformation initiatives across healthcare, finance, transportation, and the public sector, Swathi brings a practical perspective on AI strategy, responsible AI, business value, and organizational transformation.

The conversation also explores why employee productivity is advancing faster than enterprise-wide AI workflows, how organizations can build trust around AI, and what responsible AI looks like for companies that don't have dedicated compliance or AI leadership roles.

In This Episode, Swathi Young Discusses:

• Why AI productivity gains aren't always translating into enterprise-wide transformation
• Moving from AI pilots to production and measurable business impact
• The "art of the possible" for AI in different industries
• Why the AI model itself is rarely the biggest organizational bottleneck
• Building responsible AI without breaking customer or citizen trust
• Lessons from deploying a generative AI citizen services assistant for the City of Virginia Beach
• Using AWS Bedrock and generative AI in a production environment
• The economics of AI, including cost, ROI, and business value
• AI transformation in government and the public sector
• An ethical AI framework developed for U.S. federal agencies
• The minimum viable approach to responsible AI for midsize organizations
• Preparing the workforce for an AI-first future
• How leaders can move from being AI-curious to becoming AI-powered

Chapters

00:00 Introduction 01:01 Meet Swathi Young: 20+ Years in Enterprise Technology 02:00 From Software Developer to AI Strategist and CTO 06:23 The AI Gap: Employee Productivity vs. Enterprise Transformation 07:00 Showing Leaders the Art of the Possible 07:27 Building Trust Through Responsible AI 13:13 Why AI Models Aren't Usually the Biggest Bottleneck 16:25 Deploying Generative AI for Citizen Services 22:45 An Ethical AI Framework for Federal Agencies 23:00 The Minimum Viable Approach to Responsible AI 24:00 AI Strategy, ROI and Business Value 25:00 Preparing Organizations for an AI-First Future

Key Learnings

1. AI productivity is not the same as AI transformation Employees can already use AI to write emails, summarize documents, and accelerate individual tasks. But Swathi points out that end-to-end enterprise workflows are not changing at the same pace. The opportunity for leaders is to move beyond individual productivity and examine how AI can fundamentally improve the workflows that run the organization.

2. Leaders need to understand the art of the possible One of the questions Swathi hears most often from business and public-sector leaders is essentially:

What could AI actually do in my organization?

Understanding the possibilities requires looking at specific use cases within an organization's industry, workflows, customers, and operational environment.

3. Responsible AI is about maintaining trust Organizations aren't only asking what AI can do. They're also asking how they can use it responsibly without damaging the trust they've built with customers and citizens over many years.

Responsible AI therefore needs to be considered alongside strategy, implementation, governance, and the customer experience.

4. The AI model isn't always the bottleneck Swathi discusses a common challenge in enterprise AI: organizations can have access to increasingly capable models, but still struggle to translate those capabilities into production outcomes.

The surrounding organizational infrastructure, processes, data, governance, and workflows can be just as important as the model itself.

5. Production deployment matters Swathi highlights the launch of a citizen services virtual assistant for the City of Virginia Beach as a project she is particularly proud of.

The assistant, known as BeachBoard, uses generative AI and AWS Bedrock to help answer questions about city services, including areas such as utility payments and employment opportunities.

For Swathi, an important part of the achievement was getting the system into production rather than leaving it as an AI pilot.

About Swathi Young Swathi Young is a technology executive, AI strategist, and award-winning CTO with more than 20 years of experience leading digital transformation across the public and private sectors.

She has delivered more than 100 AI, data, and enterprise technology initiatives across healthcare, finance, transportation, and government, helping organizations move from AI experimentation toward measurable business impact.

Swathi advises government agencies and enterprises on AI strategy, responsible AI, data modernization, and emerging technologies. She is also the co-author of an Ethical AI framework developed for the U.S. government and created The AI Blueprint, a strategy workshop designed to help leaders move from AI-curious to AI-powered.

A graduate of Georgetown University's McDonough School of Business Executive MBA program, Swathi is passionate about making AI practical, trustworthy, and accessible.

💬 Swathi Young's Key Insights

"The actual end-to-end workflows in an enterprise... that's not changing as quickly."

"What is the art of the possible?"

"How could we use this AI responsibly?"

"Very proud that this project got deployed to production and did not stay in the pilot phase."

Follow Swathi Young

Website: https://theaiblueprint.net LinkedIn: https://www.linkedin.com/in/swathiyoung/

Follow Matt Zembruski

Website: https://leadingaiagility.com LinkedIn: https://www.linkedin.com/in/mattzembruski/ Email: matt@leadingaiagility.com Phone / Text / WhatsApp: +1 978-618-5778

In this episode of the AI Accelerator Podcast, Matt Zembruski sits down with Dr. Jeff Sutherland, co-creator of Scrum and Scrum@Scale and a signatory of the Agile Manifesto, to explore how Scrum is evolving for an AI-powered world.

Jeff's background in AI goes back decades, including his work at the Stanford AI Lab with John McCarthy and his involvement with the MIT AI Lab, where he provided development space for Rodney Brooks as he worked on autonomous robotics.

Today, Jeff is applying those lessons to AI-native teams through ScrumAI.org, exploring how humans and AI agents can work together through disciplined protocols, autonomous teams, and AI-augmented workflows.

The conversation covers everything from the origins of Scrum to AI agents running software development work, AI-powered infrastructure management, and what business leaders need to consider as AI changes the way organizations operate.

In This Episode, Dr. Jeff Sutherland Discusses:

• His early work at the Stanford AI Lab and connection to John McCarthy
• His experience with Rodney Brooks and the development of autonomous robotics
• How lessons from robotics influenced the creation of Scrum
• Why Jeff describes Scrum as a protocol
• Why AI agents need structured processes and protocols
• How Scrum can be adapted for AI-augmented teams
• The role of AI agents in software development
• Using AI to manage servers and technology infrastructure
• The emerging model of AI-augmented Scrum teams
• How AI can amplify the capacity of a team
• Measuring AI contribution alongside human work
• The changing roles of Product Owners and Scrum Masters
• What CEOs and executives need to do to adapt to AI
• How organizations can begin building AI capabilities
• The future of AI-native organizations

Chapters 00:00 - Welcome to the AI Accelerator Podcast 01:01 - Meet Dr. Jeff Sutherland, Co-Creator of Scrum 02:22 - Jeff's Early AI Journey at Stanford 04:37 - From AI Databases to Autonomous Robotics 06:27 - How Robotics Inspired Scrum 07:27 - Scrum as a Protocol for AI Agents 09:33 - Jeff's OpenClaw Project and AI Stack 10:15 - Building AI-Powered Infrastructure Operations 13:43 - ScrumAI and Scrum@Scale for AI Agents 15:20 - Using AI to Amplify Teams 16:23 - Measuring AI Contribution in Scrum 17:41 - What Business Leaders Need to Know About AI 19:45 - What Jeff Is Building at ScrumAI.org 20:50 - How CEOs Can Start Adapting to AI 22:12 - The AI Adoption Gap 23:16 - How to Connect With Jeff 24:12 - Closing Thoughts

The transcript traces Jeff's AI background from Stanford and MIT through robotics and into his current work applying Scrum to AI agents.

Key Learnings 1. AI Doesn't Eliminate the Need for Process Jeff argues that AI agents can make the same kinds of mistakes humans make, but they can make them much faster. His approach is to build the Scrum protocol directly into AI-driven workflows so that agents operate within defined structures.

2. Scrum Can Be Applied to AI Agents Jeff describes Scrum as a protocol for creating autonomous, self-organizing teams that collaborate toward a goal. In his current work, he is exploring how that protocol can be applied to teams that include AI agents.

3. AI Can Amplify Existing Teams Rather than simply replacing people, Jeff discusses using AI to augment teams and increase their capacity. He describes a goal of making a single team capable of producing the value of multiple traditional teams.

4. AI Work Can Be Measured Within Existing Scrum Practices Jeff explains how his web team is tracking AI-generated work alongside human work on the Jira board, including measuring the story points completed by AI and humans during a sprint.

5. Leaders Need to Build AI Capability Now Jeff's advice to executives is centered on education and organizational adaptation. He describes the need for companies to identify people who understand AI deeply and begin building structured programs to help the organization adapt.

6. AI Requires Continuous Adaptation A major theme of the conversation is the pace of change. Jeff argues that leaders need to continuously educate their teams and learn how to use new tools rather than treating AI as a temporary technology trend.

💬 Jeff Sutherland's Key Insights “Simple rules generate really smart behavior really fast.”

“Scrum is really a protocol.”

“They really need Scrum more than the humans, because they screw up faster than humans.”

“The goal is to augment the team and make the single team worth 10 teams.”

About Dr. Jeff Sutherland Dr. Jeff Sutherland is the co-creator of Scrum and Scrum@Scale and a signatory of the Agile Manifesto. His career in technology and AI spans decades, including early work at the Stanford AI Lab under John McCarthy and work connected to the MIT AI Lab and Rodney Brooks.

Today, Jeff focuses on writing, consulting, and applying Scrum principles to AI through ScrumAI.org. His current work explores how humans and autonomous AI agents can operate together through structured protocols, AI-augmented Scrum teams, and new approaches to organizational productivity.

Follow Dr. Jeff Sutherland

• Website: https://scrumai.org/
• LinkedIn: https://www.linkedin.com/in/jeffsutherland/

Follow Matt Zembruski

• Website: https://leadingaiagility.com
• LinkedIn: https://www.linkedin.com/in/mattzembruski/
• Email: matt@leadingaiagility.com
• Phone / Text / WhatsApp: +1 978-618-5778

In this episode of the AI Accelerator Podcast, Matt Zembruski talks with Katy Sherman, VP of Technology at BeSmartee, about how AI is reshaping Agile, product management, engineering, and technology leadership. With more than 30 years in technology, from software engineer to leading Product, Engineering, Support, and Information Security for a SaaS lending platform, Katy explains why AI is transforming Agile rather than killing it, why documenting intent is now a core engineering discipline, and how leaders can use AI to improve both speed and decision quality.

At the center of the conversation are two questions every software organization should be asking: What is the system supposed to be doing? And what is it actually doing?

In this episode:

• Is AI killing Agile, or transforming it into something better?

• Why the Agile Manifesto may need a second look in the age of AI

• Why humans struggle to keep context across large amounts of documentation

• Documenting intent before AI writes the code

• Why faster development isn't automatically better development

• Using AI to connect goals, KPIs, requirements, acceptance criteria, tests, and code

• Why Product and Engineering are converging, and why Product Operations matters

• How BeSmartee adopts AI while balancing security, quality, and customer expectations

Key quote: "What is the system supposed to be doing and what is it really doing?" – Katy Sherman

 Timestamps:

00:00 Welcome to the AI Accelerator Podcast

00:14 Meet Katy Sherman, VP of Technology at BeSmartee

01:27 Katy's journey from software engineer to technology and product leader

03:36 Why combining Product and Engineering creates better business outcomes

04:32 AI adoption in fintech: security and managing risk

05:25 Is AI killing Agile?

06:30 The massive transformation happening in software development

07:40 Reexamining the Agile Manifesto in the age of AI

08:38 Why humans struggle with massive amounts of documentation

09:43 From comprehensive documentation to code as the durable record

10:49 What AI changes about comprehension, context, and software development

12:05 AI-generated code and the need to document intent

13:09 Why successful organizations will need stronger statements of intent

14:38 How BeSmartee is adapting its operating model

15:07 Balancing speed, quality, and customer expectations

16:05 The two questions at the heart of software quality

17:40 Why knowing what a system will actually do is difficult

18:34 The danger of simply accelerating code production

19:28 Using AI to document and validate intent

20:52 What is the system supposed to do, and what is it actually doing?

21:25 Separating code generation from context and decision-making

22:01 Using AI to connect goals, KPIs, requirements, tests, and code

22:48 Getting the benefits of AI without losing control

23:19 Final thoughts with Katy Sherman

Connect with Katy Sherman:

Website: https://www.besmartee.com/

LinkedIn: https://www.linkedin.com/in/katy-sherman/

Connect with Matt Zembruski:

Website: https://leadingaiagility.com

LinkedIn: https://www.linkedin.com/in/mattzembruski/

Email: matt@leadingaiagility.com

Phone / Text / WhatsApp: +1 978-618-5778

About the AI Accelerator Podcast: Hosted by Matt Zembruski, the AI Accelerator Podcast explores how leaders are moving beyond AI hype and putting artificial intelligence to work in real organizations, with practical perspectives on AI adoption, digital transformation, leadership, innovation, and the future of work. 

In this episode of the AI Accelerator Podcast, host Matt Zembruski sits down with Johanna Rothman, known as the Pragmatic Manager, to explore what practical AI adoption really looks like inside product development organizations.

Johanna Rothman has worked in software and product development since 1977 and has written 21 books covering management, leadership, project management, and product development. Her approach is straightforward: understand your current reality, focus on what actually works, and avoid adopting technology simply because everyone else is doing it.

The conversation explores why clean organizational data may matter more than massive datasets, how AI can improve the flow of information across teams, and why organizations need to rethink how they make decisions in an increasingly AI-enabled workplace.

Johanna also explains why teams should use AI together, rather than treating AI as an individual productivity tool. Effective collaboration, better information flow, shorter feedback loops, and faster decision-making can all play a role in creating more adaptable organizations.

In This Episode, Johanna Rothman Discusses: ◼️ Why AI hype makes pragmatic thinking more important than ever ◼️ Why clean data can be more valuable than enormous datasets ◼️ How organizations can use AI to uncover insights from their existing data ◼️ The difference between cost accounting and measuring organizational flow ◼️ Why value stream mapping can help companies understand how work actually moves ◼️ How AI can improve the flow of information and features across an organization ◼️ Why product development teams need to use AI collaboratively ◼️ The concept of flow debt and how accelerating one piece of work can affect everything else ◼️ Why organizations often need fewer features delivered faster rather than more features ◼️ How AI can support better decision-making without removing human judgment ◼️ Why important business decisions should be treated as experiments ◼️ How shorter roadmaps and faster iterations can make organizations more adaptable ◼️ Why finance, HR, sales, and marketing also need to become more adaptable ◼️ How leaders can think differently about AI adoption and organizational change ◼️ The importance of protecting sensitive and proprietary company data when using AI

Chapters 00:00 Welcome to the AI Accelerator Podcast 00:30 Introducing Johanna Rothman, the Pragmatic Manager 01:30 Johanna's journey through product development and management 03:00 Cutting through the AI hype 05:00 Clean data, small models, and practical AI 07:50 What does dirty organizational data look like? 08:20 Cost accounting vs. flow and throughput 09:00 Using AI with value stream mapping 10:00 Measuring work, wait time, WIP, throughput, and cycle time 11:00 AI readiness and organizational assessments 12:00 Why organizations need to understand their current reality 14:20 Data quality and using AI for better business insights 15:15 Understanding flow debt 15:40 Why collaborative teams should use AI together 17:00 Improving information flow across organizations 18:30 AI, decision-making, and organizational effectiveness 19:50 Why valuable decisions should be treated as experiments 21:00 Johanna's writing, books, and pragmatic management philosophy 23:50 Building adaptable organizations with shorter roadmaps 25:00 Why organizations need to experiment and pivot 26:00 The future of AI and organizational adaptability

Key Learnings ✔ AI adoption should begin with understanding the organization's real problems ✔ Clean, useful data can be more valuable than simply having more data ✔ AI can help organizations analyze flow, throughput, cycle time, and work-in-progress ✔ Product development is fundamentally collaborative work ✔ Teams can get more value from AI when they use it together ✔ Faster information flow can lead to better and faster decisions ✔ Organizations often need fewer features delivered more effectively ✔ Important decisions should remain flexible and be treated as experiments ✔ Shorter roadmaps allow organizations to respond to changing conditions ✔ AI should strengthen human decision-making rather than eliminate it ✔ Organizations need to build a culture of experimentation and adaptability

💬 Johanna's Key Insights “The hype cycle is unbelievable.”

“What we need is effective flow of information and flow of features.”

“The faster you can make that flow of information move, the faster people can then make better decisions.”

“The most valuable decisions need to be able to be thought of as experiments.”

About Johanna Rothman Johanna Rothman, known as the Pragmatic Manager, is an author, consultant, and expert in product development, project management, program management, portfolio management, leadership, and modern management. She has written 21 books along with hundreds of articles and thousands of blog posts. Her work focuses on helping leaders and teams understand their current reality, improve collaboration, and focus on outcomes that matter.

Follow Johanna Rothman Website: Rothman Consulting Group LinkedIn: Johanna Rothman LinkedIn YouTube: Johanna Rothman YouTube Links: Johanna Rothman Linktree

Follow Matt Zembruski Website: Leading AI Agility LinkedIn: Matt Zembruski LinkedIn Email: matt@leadingaiagility.com Phone / Text / WhatsApp: +1 978-618-5778

✔ Existing AI models can be the better choice for common business problems. ✔ Open-source models are becoming increasingly important in the AI landscape. ✔ Businesses should start AI adoption with a manageable process rather than trying to transform everything at once. ✔ The best AI opportunities often come from eliminating friction in existing business processes. 💬 Erick’s Key Insights “There's two decisions you have to make right up front.” “Is that solution going to be unique to my business?” “Start small.” “Reinvent it from the ground up.” About Erick Watson Erick Watson helps AI labs, Web3 protocols, and venture studios turn frontier research into products people use. Through SproutVest, he works as a fractional CPO, embedding with founding teams for 6–12 months to define product lines, build go-to-market strategies, and ship products. Follow Erick Watson Website: https://sproutvest.com LinkedIn: https://www.linkedin.com/company/sproutvest X: https://x.com/sproutvest Bluesky: https://bsky.app/profile/sproutvest.bsky.social Telegram: https://t.me/ErickWa GitHub: https://github.com/ErickWa Follow Matt Zembruski Website: https://leadingaiagility.com LinkedIn: https://www.linkedin.com/in/mattzembruski/ Email: matt@leadingaiagility.com Phone / Text / WhatsApp: +1 978-618-5778

In this episode of the AI Accelerator Podcast, host Matt Zembruski sits down with Alvin Pereira, Senior Director and Head of Strategy & Operations for Global Workforce Management Products at ADP, former product leader at Google and Disney, and founder of The Pereira Foundation, to discuss how leaders can embrace AI while keeping people at the center of every decision.

Drawing from his experience leading products, building teams, and driving innovation across some of the world's most recognized organizations, Alvin shares practical insights on AI adoption, organizational transformation, product leadership, and creating cultures where innovation thrives.

From Disney's MagicBand platform to enterprise workforce technology, Alvin explains how AI is accelerating product development, reducing barriers to innovation, and enabling organizations to move from idea to execution faster than ever before.

At the heart of Alvin's philosophy is one powerful idea:

"AI should enhance the human."

In this episode, Alvin reveals:

◼️ Why AI should amplify people rather than replace them

◼️ How leaders can reduce fear and resistance around AI adoption

◼️ Why experimentation beats perfection in today's rapidly changing world

◼️ How AI is accelerating product development and innovation cycles

◼️ The importance of empathy in leadership and product design

◼️ Lessons learned from building products at Disney, Google, and ADP

◼️ Why culture matters more than process when driving transformation

◼️ How small teams can achieve extraordinary results

◼️ The role of change management in successful AI adoption

◼️ Why leaders must stay connected to customers and frontline employees

◼️ How AI can help organizations move from idea to prototype faster

◼️ The importance of servant leadership in modern organizations

◼️ Why adaptability is becoming the most valuable business skill

◼️ How leaders can create environments where innovation flourishes

◼️ What the future of AI-powered organizations may look like

Chapters

00:00 Welcome to the AI Accelerator Podcast

00:29 Introducing Alvin Pereira

01:22 Alvin's Career Journey Across Technology, Hospitality & Product Leadership

03:04 Lessons from Google, Disney, Hilton & ADP

03:31 Product Management, Design & Customer-Centric Innovation

06:07 The AI Revolution and Product Development

07:00 Why AI Should Enhance Humans, Not Replace Them

09:04 Managing Organizational Change in the AI Era

12:05 Helping Teams Embrace AI Through Experimentation

14:21 Building a Growth Mindset Culture

15:32 Empowering Teams to Solve Bigger Problems

20:32 Leadership Lessons for Driving Innovation

21:22 Building Disney's MagicBand Experience

24:36 Culture, Trust & Organizational Success

26:26 The Biggest Opportunities Leaders Should Focus On

29:14 Accelerating Innovation with AI

31:42 Leadership, Legacy & The Pereira Foundation

33:24 Final Thoughts

Key Learnings

✔ AI is most powerful when it enhances human capability

✔ Organizations that embrace experimentation adapt faster

✔ Change management is often harder than technology adoption

✔ Great leaders focus on removing obstacles for their teams

✔ Empathy remains a critical competitive advantage

✔ Culture drives innovation more effectively than process alone

✔ AI enables faster prototyping, testing, and iteration

✔ Small, empowered teams can create outsized impact

✔ Customer-focused innovation produces better outcomes

✔ The future belongs to leaders who combine technology with humanity

💬 Alvin's Most Powerful Quotes

"AI should enhance the human."

"You don't build products for yourself. You build them for the people who use them."

"It's not impossible. We just haven't figured out how to do it yet."

"The best framework is the one that helps your team get things done."

"Culture exists for the people inside the organization."

"Leadership is about serving your team."

"The faster you can move from idea to prototype, the faster you can learn."

"Technology changes. Human needs don't."

About Alvin Pereira

Alvin Pereira is a product and strategy executive with leadership experience spanning ADP, Google, Disney, Hilton, and Workforce Software. Throughout his career, he has led product innovation, digital transformation initiatives, and organizational growth efforts focused on creating exceptional customer experiences.

Currently serving as Senior Director and Head of Strategy & Operations for Global Workforce Management Products at ADP, Alvin helps organizations navigate change while building products that improve how people work.

Beyond his corporate leadership roles, Alvin is also the founder of The Pereira Foundation, focused on expanding opportunities and supporting communities through education and service.

Follow Alvin Pereira LinkedIn: https://www.linkedin.com/in/alvinpereira/

Follow Matt Zembruski Website: https://leadingaiagility.com

LinkedIn: https://www.linkedin.com/in/mattzembruski/

Email: matt@leadingaiagility.com

Phone Text WhatsApp: +1 978-618-5778

#AI #ArtificialIntelligence #Leadership #ProductManagement #Innovation #DigitalTransformation #FutureOfWork #AIAdoption #ProductLeadership #ADP #Disney #Google #AIAcceleratorPodcast #MattZembruski #AlvinPereira

In this episode of the AI Accelerator Podcast, host Matt Zembruski sits down with Chris Seferlis, Strategic Advisor at Microsoft, Boston University Professor, author, keynote speaker, and enterprise AI strategist, to discuss what leaders need to understand about AI adoption, Microsoft Copilot, AI agents, and the future of work.

Drawing from years of experience helping enterprise organizations implement AI solutions, Chris shares why so many AI projects fail, how leaders should think about productivity versus replacement, and why successful AI adoption starts with people, process, and business outcomes—not technology.

From Microsoft Copilot and Azure AI to enterprise data strategies and agentic workflows, Chris provides practical insights leaders can use today to unlock real business value while avoiding the common pitfalls that derail AI initiatives.

At the heart of Chris's message is one critical idea:

"Start with the business problem, not the AI."

In this episode, Chris reveals:

◼️ Why most AI projects fail to meet expectations ◼️ The biggest mistakes leaders make when implementing AI ◼️ Why AI should enhance people, not simply replace them ◼️ How Microsoft Copilot is changing workplace productivity ◼️ The difference between Copilot Chat and Microsoft 365 Copilot ◼️ Why data quality remains critical for AI success ◼️ How organizations can maximize existing Microsoft investments ◼️ The rise of AI agents and agentic workflows ◼️ Why business outcomes should drive AI strategy ◼️ How AI is transforming enterprise operations and decision-making ◼️ The role of governance, security, and responsible AI adoption ◼️ Why leaders need hands-on AI experience themselves ◼️ How organizations can build an AI-ready culture ◼️ Practical examples of AI-powered automation and productivity gains ◼️ What the future of work looks like in an AI-driven world

Key Learnings

✔ Most AI failures are caused by poor strategy, not poor technology ✔ Organizations must define business outcomes before implementing AI ✔ AI is currently creating more productivity gains than workforce replacement ✔ Data quality remains one of the biggest success factors for AI initiatives ✔ Microsoft Copilot is evolving into a powerful enterprise productivity platform ✔ AI agents will automate increasingly complex business workflows ✔ Leaders should personally experiment with AI before driving adoption across teams ✔ Successful AI adoption requires change management and employee engagement ✔ Governance and security must be part of every AI strategy ✔ Organizations that embrace AI thoughtfully will gain a significant competitive advantage

💬 Chris's Most Powerful Quotes

"Most AI projects fail because organizations don't clearly define what success looks like."

"AI should be tied to a business outcome, not deployed for the sake of using AI."

"The companies seeing the biggest wins are using AI to augment people, not replace them."

"Your data strategy is your AI strategy."

"Leaders need to experience AI firsthand before they can successfully lead AI transformation."

"The future belongs to organizations that can combine human expertise with AI capabilities."

Follow Chris Seferlis

LinkedIn: https://www.linkedin.com/in/cseferlis/

Website: https://seferlis.com/

YouTube: https://www.youtube.com/@ChrisSeferlis

X: https://x.com/bizdataviz

Email: chris@bizdataviz.com

Follow Matt Zembruski

Website: https://leadingaiagility.com

LinkedIn: https://www.linkedin.com/in/mattzembruski/

Email: matt@leadingaiagility.com

Phone / Text / WhatsApp: +1 978-618-5778

In this episode of the AI Accelerator Podcast, host Matt Zembruski sits down with Amanda C. Chambers, CEO of The Institute for Organizational Leadership (IOL Global), to explore how AI is reshaping leadership, learning and development, project management, marketing operations, and organizational growth.

With more than 25 years of experience in executive operations, instructional design, leadership development, podcast production, and business strategy, Amanda shares practical insights on how organizations can responsibly integrate AI while keeping people at the center of transformation.

From AI-powered marketing systems and content workflows to leadership coaching and workforce development, Amanda explains why the companies that thrive in the AI era will be the ones that invest in both technology and human capability.

At the heart of Amanda’s message is a powerful leadership principle:

“Let your people learn.”

In this episode, Amanda reveals:

◼️ Why organizations must train employees to use AI responsibly ◼️ How AI enhances human creativity instead of replacing people ◼️ The role of leadership in guiding AI adoption across teams ◼️ Why learning and development will become more important in the AI era ◼️ How IOL Global manages AI-powered marketing and YouTube operations ◼️ The practical ways Amanda’s team uses Claude, ChatGPT, and AI workflows ◼️ Why executives must personally learn AI—not just delegate it ◼️ The importance of strategic partnerships in navigating AI transformation ◼️ How AI is accelerating instructional design and content creation ◼️ Why organizations that refuse AI adoption risk falling behind ◼️ The future of AI-powered project management and leadership operations ◼️ How companies can maintain the human element while automating workflows ◼️ Why ethical AI adoption and workforce training matter more than ever ◼️ How curiosity, adaptability, and learning culture drive long-term success ◼️ Amanda’s core philosophy: “AI should help people do better work.”

Key Learnings

✔ AI should enhance people—not replace them ✔ Organizations must actively train teams to use AI responsibly ✔ Learning and development are becoming even more valuable in the AI era ✔ Leaders must personally understand AI to guide transformation effectively ✔ AI creates more time for creativity, strategy, and relationship building ✔ Human oversight remains essential in AI-powered workflows ✔ Strategic partnerships accelerate AI learning and implementation ✔ Ethical AI adoption requires intentional leadership ✔ Marketing, content creation, and project management are rapidly evolving with AI ✔ Curiosity and adaptability are becoming core leadership skills

💬 Amanda’s Most Powerful Quotes

“Let your people learn.” “AI is helping people do better work.” “You need to train your teams to use these tools responsibly.” “Learning is not going away—it’s changing.” “It’s not about replacing people. It’s about enhancing what we can do.”

Follow Amanda C. Chambers

Website: http://www.iolglobal.com/

LinkedIn: https://www.linkedin.com/in/amandacchambers/

Facebook: https://www.facebook.com/amanda.chambers.330467/

Follow Matt Zembruski

Website: https://leadingaiagility.com LinkedIn: https://www.linkedin.com/in/mattzembruski/

In this episode of the AI Accelerator Podcast, host Matt Zembruski sits down with Jenny Korten, Co Partner at Thinking 5.0 and creator of Mind Nudger AI, to explore one of the most important leadership questions of the AI era: How do we use AI to enhance human wisdom instead of replacing it?

Drawing from decades of neuroscience based leadership coaching, intergenerational strategy, and enterprise transformation across Africa, Europe, and Asia, Jenny shares how leaders can bridge the widening gap between exponential AI advancement and incremental human learning.

From mindset rewiring and cognitive bias to HR transformation, AI readiness, and the neuroscience of sustainable learning, Jenny introduces a people first model for AI adoption that empowers organizations to evolve without sacrificing humanity.

At the center of Jenny’s philosophy is a bold idea: The future is not about AI replacing people—it is about AI amplifying collective human intelligence.

In this episode, Jenny reveals:

◼️ Why AI adoption fails when companies invest in software but ignore people ◼️ The “Formula 1 car without a trained driver” analogy for enterprise AI ◼️ How neuroscience explains resistance to AI and organizational change ◼️ Why leaders must move from tech first to people first thinking ◼️ The hidden danger of AI anxiety and survival mode in the workforce ◼️ How Thinking 5.0 helps organizations protect and enhance human wisdom ◼️ The Mind Nudger AI framework for habit formation and learning retention ◼️ The O.R.A. Method: Observe, Reflect, Act ◼️ Why reflection—not reaction—is the leadership skill of the future ◼️ How HR must evolve from administrative support to strategic transformation ◼️ Why intergenerational alignment is essential for future ready organizations ◼️ How AI can reduce burnout while improving strategic capacity ◼️ The importance of training the human mind as much as the machine ◼️ Why collective intelligence will define next generation leadership ◼️ Jenny’s powerful question: “Are we the last human generation with wisdom?”

Key Learnings

✔ AI transformation without human transformation creates failure  ✔ Reflection is becoming a competitive leadership advantage  ✔ AI should reduce burnout—not increase anxiety  ✔ Human wisdom must remain central in AI strategy  ✔ Organizations need both technology investment and people investment  ✔ HR and L&D are essential drivers of AI readiness  ✔ Intergenerational alignment strengthens organizational resilience  ✔ Sustainable learning requires incremental habit building  ✔ AI can empower people when paired with critical thinking  ✔ Collective intelligence is the real future of work

💬 Jenny’s Most Powerful Quotes

“If you invest $1 in technology, invest $1 in the human mind.”  “AI is the Formula 1 car but your people are the driver.”  “The future is not about AI. The future is about evolving collective intelligence.”  “Reflection reconnects us with human wisdom.”  “Are we the last human generation with wisdom?”

Follow Jenny Korten

Thinking 5.0: https://www.thinking50.studio/ LinkedIn: https://www.linkedin.com/in/jenny-korten-736b16219/ Email: jenny@thinking50.studio

Follow Matt Zembruski

Website: https://leadingaiagility.com LinkedIn: https://www.linkedin.com/in/mattzembruski/ Email: matt@leadingaiagility.com Phone Text WhatsApp: +1 978-618-5778

In this episode of the AI Accelerator Podcast, host Matt Zembruski sits down with Tanya Boyd, Co Founder of Project Success Academy and Director of Creative Collaboration at Corbeau, to explore how AI, creativity, and continuous learning are reshaping the future of project leadership.

With more than 20 years of experience across disaster recovery, healthcare, IT, marketing, and government, Tanya brings a rare blend of strategic project leadership, creative innovation, and real world resilience. From Hurricane Katrina disaster recovery to PMI leadership, keynote stages, and AI powered corporate training, Tanya’s journey proves that adaptability, communication, and curiosity are the ultimate competitive advantages.

As a PMP®, PMI ACP®, keynote speaker, and co author of Projectland Goes to the Movies, Tanya shares how project managers, executives, and everyday professionals can embrace AI not as a threat but as a tool for growth, creativity, and transformation.

Together, Matt and Tanya unpack how leaders can overcome AI imposter syndrome, use AI to sharpen communication, strengthen personal branding, improve training programs, and future proof their careers in an era of intelligent transformation.

In this episode, Tanya reveals:

◼️ How disaster recovery shaped her project management journey  ◼️ Why AI imposter syndrome is real and how to overcome it  ◼️ The biggest fears project managers face about AI  ◼️ Why continuous learning is the key to career resilience  ◼️ How AI can enhance creativity, communication, and leadership  ◼️ Practical ways project managers can use AI today  ◼️ Why authenticity matters when using AI for personal branding  ◼️ How AI can improve speaking, presentations, and corporate training  ◼️ Why networking and visibility are more important than ever  ◼️ How to future proof your career in a rapidly changing economy  ◼️ Why relationship building remains a uniquely human advantage  ◼️ The evolving role of project managers in an AI driven world  ◼️ How AI can create more time for strategy and leadership  ◼️ Why curiosity and communication unlock innovation

Key Learnings

✔ AI should be used as a growth tool not a fear trigger  ✔ Continuous learning is essential for career resilience  ✔ Project managers must combine technical, strategic, and people skills  ✔ AI can enhance communication, creativity, and execution  ✔ Authenticity matters even more in an AI powered world  ✔ Networking and visibility are critical career accelerators  ✔ AI can strengthen leadership through better preparation and strategy  ✔ Adaptability is the ultimate advantage in uncertain times  ✔ Human relationships remain irreplaceable  ✔ Leaders who embrace AI now will gain long term competitive advantage

💬 Tanya’s Most Powerful Quotes

“We all feel like we’re behind with AI and that’s normal.”  “You’re never going to have it all figured out just like project management.”  “Continuous learning is your greatest protection.”  “AI can help you grow, but authenticity is what makes you matter.”  “The goal is to gain more time back for relationships and strategy.”

Follow Tanya Boyd

Website: https://projectsuccessacademy.com/ YouTube: https://www.youtube.com/@ProjectSuccess_Academy LinkedIn: https://www.linkedin.com/company/project-success-academy/posts/?feedView=all

Follow Matt Zembruski

Website:

In this episode of the AI Accelerator Podcast, host Matt Zembruski sits down with Benjamin Dowd, CEO of The Phoenix Firm, to explore what it really takes to move from AI hype to execution.

With over 20 years of experience advising enterprise leaders across Canada, Central America, and South America, Ben shares how organizations can modernize, automate, and scale using AI in a way that delivers measurable outcomes not just ideas.

As a Certified AI Consultant and former Senior Banking Executive, Ben brings a unique blend of financial expertise, strategy, and hands on implementation experience. His work focuses on helping leaders bridge the gap between ambition and execution, designing AI adoption roadmaps that actually work in the real world.

Together, they unpack how organizations can build AI strategies that drive clarity, control, and competitive advantage while avoiding the common pitfalls that keep companies stuck in theory.

In this episode, Benjamin reveals:

◼️ Why most organizations struggle to move from AI ideas to execution ◼️ The difference between AI hype and measurable business impact ◼️ How to design AI strategies that actually deliver outcomes ◼️ Why governance and AI literacy are critical for success ◼️ The role of intelligent automation in scaling operations ◼️ How leaders can align AI initiatives with real business goals ◼️ Why enterprise adoption requires more than just new tools ◼️ The importance of change management in AI transformation ◼️ How to build clarity and control in AI driven environments ◼️ Why data driven decision making is at the core of AI success ◼️ The biggest mistakes organizations make when adopting AI ◼️ How executives can lead confidently in an era of intelligent transformation ◼️ Why operational excellence matters more than experimentation alone ◼️ How AI can create adaptive and scalable business systems

Key Learnings

✔ AI success depends on execution not ideas ✔ Strategy must be aligned with measurable business outcomes ✔ Governance and AI literacy are essential for sustainable adoption ✔ Intelligent automation enables scalable transformation ✔ Change management is critical in enterprise AI initiatives ✔ Data driven decisions are at the core of AI enabled organizations ✔ Leaders must bridge the gap between vision and execution ✔ Operational excellence matters more than experimentation alone ✔ AI requires both strategy and hands on implementation ✔ Organizations must move beyond hype to achieve real impact

💬 Benjamin’s Most Powerful Quotes

“Organizations don’t fail because of lack of ideas they fail because of lack of execution.” “AI is only valuable when it creates measurable business outcomes.” “Strategy without implementation is just theory.” “Clarity and control are what turn AI into competitive advantage.” “Leaders must move from ambition to operational excellence.”

Follow Benjamin Dowd

LinkedIn: https://www.linkedin.com/company/thephoenixfirm Website: https://thephoenixfirm.ca/ Spotify: https://open.spotify.com/show/5fHRe53AqHuVS3YimmIZv1 YouTube: https://www.youtube.com/@ThePhoenixFirm-h8j

Follow Matt Zembruski

Website: https://leadingaiagility.com LinkedIn: https://www.linkedin.com/in/mattzembruski/ Facebook: https://www.facebook.com/mzembruski Instagram: https://www.instagram.com/thelif

"Change equals opportunity — if we can get people to see the opportunity, it becomes something they might even get behind."

"You have to demonstrate to your team that you care — not just about mission accomplishment, but about them as a person."

"If the vision looks the same as the mission today, I kind of know where we stand."

"All we've done when we become a leader is turn the page to a new chapter, because now we have a responsibility for everyone on the team." Follow Ryan Batchelor Website: https://www.cruxleaders.org/ LinkedIn: https://www.linkedin.com/in/ryan-batchelor-stl/ Email: ryanb@cruxleaders.org Follow Matt Zembrowski Website: https://leadingaiagility.com LinkedIn: https://www.linkedin.com/in/mattzembruski/ Email: matt@leadingaiagility.com Phone/Text/WhatsApp: +1 978-618-5778 Facebook: https://www.facebook.com/mzembruski Instagram: https://www.instagram.com/thelifeofmattz/

In this episode of the AI Accelerator Podcast, host Matt Zembrowski sits down with Tom Famularo, CEO and Founder of Cap20AI, to explore how AI is fundamentally changing how businesses operate, build software, and make decisions.

With decades of experience building, scaling, and exiting technology companies, Tom shares what most organizations get wrong about AI, why adoption is a human problem not a technical one, and how leaders can rethink their entire business model in an AI driven world.

Together, they break down the shift from workflows to outcomes, why traditional SaaS models are under threat, and how companies can scale expert thinking using AI while keeping humans in the loop.

In this episode, Tom reveals:

◼️ Why AI adoption is more about people than technology ◼️ How AI is different from every previous tech wave ◼️ Why AI behaves like a self improving system ◼️ The real reason organizations resist AI adoption ◼️ The danger of relying too much on AI outputs ◼️ Why humans must stay in the loop ◼️ How to overcome organizational resistance to change ◼️ The importance of greenfield innovation inside companies ◼️ Why transformation should be business led not tech led ◼️ The shift from workflows to outcome driven systems ◼️ How AI can eliminate traditional software development cycles ◼️ Why scaling expert thinking is more valuable than automating tasks ◼️ Real world use cases in insurance and financial services ◼️ How AI improves consistency and decision quality ◼️ Why SaaS companies are at risk in the AI era ◼️ The concept of the SaaS apocalypse ◼️ Why companies must be willing to cannibalize their own business ◼️ How consulting and tech models will evolve with AI

Key Learnings

✔ AI adoption is primarily a human and cultural challenge ✔ Technology is no longer the bottleneck in transformation ✔ AI enables faster execution but still requires human judgment ✔ Organizations must rethink how they build and operate systems ✔ Outcome driven systems will replace traditional workflows ✔ Scaling expert thinking creates massive leverage ✔ AI improves consistency across large teams ✔ Companies must embrace change even if it disrupts current success ✔ SaaS and consulting models are being fundamentally reshaped ✔ Leaders must prioritize long term transformation over short term stability

💬 Tom’s Most Powerful Quotes

“AI is not the problem. Adoption is the problem.” “The friction is organizational, not technological.” “AI can get you to 90 percent fast, but the last 10 percent matters.” “Scale the expert, not just the task.” “Transformation should be driven by the business, not technology.”

Follow Tom Famularo

Website: https://cap20.ai/ LinkedIn: https://www.linkedin.com/in/tom-famularo-4b018311/

Follow Matt Zembrowski

Website: https://leadingaiagility.com LinkedIn: https://www.linkedin.com/in/mattzembruski/ Email: matt@leadingaiagility.com Phone/Text/WhatsApp: +1 978-618-5778 Facebook: https://www.facebook.com/mzembruski Instagram: https://www.instagram.com/thelifeofmattz/

AI is evolving fast but without control it creates inconsistency, risk, and missed opportunities.

In this episode of the AI Accelerator Podcast, host Matt Zembrowski sits down with Alapeti “AL” Ware, Co-Founder of 8P3P, to explore how AI is shifting from tools to true intelligence infrastructure.

With a background in XR, metaverse development, and enterprise AI systems, Al shares how he is building an intelligence control layer that governs AI outputs, personalizes learning, and integrates seamlessly into existing systems without replacing them.

Together, they break down what it really takes to make AI useful in education and enterprise, why most implementations fail, and how organizations can move from experimentation to real impact.

In this episode, Al reveals:

◼️ Why most AI implementations fail in real-world systems ◼️ The problem with inconsistent AI outputs ◼️ What an intelligence control layer actually is ◼️ How AI can personalize learning for every student ◼️ Why traditional grading systems are broken ◼️ How AI supports teachers instead of replacing them ◼️ The role of AI in workforce training and onboarding ◼️ Why AI should never replace human decision-making ◼️ The importance of governance and policy in AI systems ◼️ Why “rip and replace” is a mistake in enterprise tech ◼️ How to integrate AI without disrupting existing workflows ◼️ The shift from AI tools to AI infrastructure ◼️ Why LLMs alone are not the future of AI ◼️ How adaptive learning improves long-term outcomes ◼️ The opportunity to reshape education using AI

Key Learnings

✔ AI is inconsistent without proper control layers ✔ Most companies are adding AI instead of integrating it ✔ Personalized learning is one of AI’s biggest opportunities ✔ AI should assist humans, not replace decision-making ✔ Governance and policy are critical for AI success ✔ Education and workforce training follow similar models ✔ Integration is better than replacing existing systems ✔ Focused AI systems will outperform generic tools ✔ Human oversight remains essential in all AI workflows ✔ The future of AI lies in infrastructure, not interfaces

💬 Al’s Most Powerful Quotes

“AI should never be the final decision-maker.” “An 85 percent does not mean a student understands the subject.” “We don’t replace systems, we control the intelligence inside them.” “Most companies are just putting a sticker on AI.” “The future of AI is systems connected to LLMs, not LLMs themselves.”

Follow Alapeti Ware

Website: https://8p3p.io LinkedIn: https://www.linkedin.com/in/drgenius/

Follow Matt Zembrowski

Website: https://leadingaiagility.com LinkedIn: https://www.linkedin.com/in/mattzembruski/ Email: matt@leadingaiagility.com Phone/Text/WhatsApp: +1 978-618-5778 Facebook: https://www.facebook.com/mzembruski Instagram: https://www.instagram.com/thelifeofmattz/

In this episode of the AI Accelerator Podcast, host Matt Zembruski sits down with Dave Westgarth, Head of Delivery at Unifeye, to explore how AI is transforming agile teams, delivery metrics, and the future of digital work.

With over a decade of experience across development, agile leadership, and enterprise delivery, Dave shares practical insights into integrating AI into real workflows — without sacrificing engineering standards, strategic thinking, or team wellbeing.

Together, they unpack what happens when AI accelerates everything — from coding to experimentation — and why organizations must rethink metrics, leadership expectations, and even career development in an AI-powered world.

In this episode, Dave reveals:

◼️ Why AI is the biggest sustained transformation wave in modern tech ◼️ The danger of “prototype purgatory” in AI adoption ◼️ Why traditional delivery metrics may soon become meaningless ◼️ How cycle time, DORA, and flow metrics change in an AI world ◼️ What Parkinson’s Law 2.0 means for AI-powered professionals ◼️ Why speed alone is not a strategic advantage ◼️ How AI democratizes development — but doesn’t replace craftsmanship ◼️ The risks of messy AI-generated code in production systems ◼️ Why security, scalability, and architecture still require human expertise ◼️ How product managers can now experiment without heavy engineering lift ◼️ The difference between experimentation tools and production systems ◼️ Why organizations must adopt a learning mindset, not just new tools ◼️ The leadership recalibration required in AI acceleration ◼️ How AI increases expectations — and the burnout risk that follows ◼️ Why understanding how LLMs work reduces fear and increases effectiveness

Key Learnings

✔ AI dramatically accelerates delivery — but speed must serve strategy ✔ Traditional agile metrics will need rethinking in an AI-first world ✔ AI lowers experimentation cost, increasing innovation capacity ✔ Production-grade systems still require engineering discipline ✔ Security and scalability cannot be “prompted” into existence ✔ Organizations must move from tool adoption to learning adoption ✔ Leaders must recalibrate expectations as productivity rises ✔ AI increases output — and can increase burnout ✔ Technical literacy reduces fear and improves AI effectiveness ✔ Waiting for best practices to stabilize may mean falling behind

💬 Dave’s Most Powerful Quotes

“Speed is not a natural good.” “AI doesn’t remove the need for craftsmanship.” “The barrier to entry has never been lower.” “Work grows to fill the capacity AI creates.” “If you understand how LLMs work, a lot of fear disappears.”

Follow Dave Westgarth

• LinkedIn: Dave Westgarth https://www.linkedin.com/in/dave-westgarth/
• X: https://x.com/dave_westgarth
• Linktree: https://linktr.ee/davewestgarth

Follow Matt Zembruski

• Website: https://leadingaiagility.com
• LinkedIn: https://www.linkedin.com/in/mattzembruski/
• Email: matt@leadingaiagility.com
• Phone/Text/WhatsApp: +1 978-618-5778
• Facebook: https://www.facebook.com/mzembruski
• Instagram: https://www.instagram.com/thelifeofmattz/

In this episode of the AI Accelerator Podcast, host Matt Zembruski sits down with Arman Eshraghi, serial entrepreneur and Founder and CEO of Qrvey.

Having founded four B2B software companies, Arman brings decades of experience building data platforms across major technology shifts from Windows to web to cloud and now AI. Together, they explore what embedded analytics really means, how SaaS companies should think about AI adoption, and why the future of software includes both humans and AI agents working side by side.

In this episode, Arman reveals:

◼️ How falling in love with a Commodore 64 sparked his entrepreneurial journey ◼️ Why each major tech wave created a new software opportunity ◼️ What embedded analytics actually means for SaaS companies ◼️ The hidden complexity of multi tenant data environments ◼️ Why charts and dashboards alone do not create real value ◼️ How Qrvey solves over 500 deep SaaS analytics challenges ◼️ The difference between BI tools and true embedded analytics platforms ◼️ How AI has evolved from structured data to multimodal intelligence ◼️ Why generative AI changes how software interacts with humans ◼️ The rise of AI agents as digital workers inside software systems ◼️ How AI adoption differs based on company DNA ◼️ Why speed matters but reckless adoption is dangerous ◼️ The tension between execution and innovation in AI transformation ◼️ How SaaS companies should think about accuracy, cost, and AI risk ◼️ Why not every company should move at the same AI speed

Key Learnings

✔ Embedded analytics is far more complex than dashboards ✔ SaaS companies must solve multi tenant data challenges differently ✔ AI is shifting from structured data to multimodal understanding ✔ AI agents will become active users of software systems ✔ Innovation speed must align with company DNA ✔ Execution discipline remains critical during AI transformation ✔ Not every AI capability belongs in production immediately ✔ Accuracy, cost, and governance still matter deeply ✔ The future of SaaS includes collaboration between humans and AI ✔ Companies that ignore AI entirely risk falling behind

💬 Arman’s Most Powerful Quotes

“AI is like hiring new digital employees.” “Not every company should move at the same AI speed.” “You need to know your company’s DNA before deciding your AI strategy.” “If you do not keep up, you fall behind. If you move too fast, you break things.” “Charts and dashboards alone do not create value.”

Follow Arman Eshraghi

• LinkedIn: Arman Eshraghi https://www.linkedin.com/in/aeshraghi/
• Website: Qrvey https://qrvey.com/
• YouTube: https://www.youtube.com/@qrvey

Follow Matt Zembruski

• Website: https://leadingaiagility.com
• LinkedIn: https://www.linkedin.com/in/mattzembruski/
• Email: matt@leadingaiagility.com
• Phone/Text/WhatsApp: +1 978-618-5778
• Facebook: https://www.facebook.com/mzembruski
• Instagram: https://www.instagram.com/thelifeofmattz/

In this episode of the AI Accelerator Podcast, host Matt Zembruski sits down with Matt Sims, global Lean Master Black Belt, transformation leader, and founder of Ever-So-Lean.

With more than twenty five years leading operational excellence and cultural transformation across industries, Matt shares his journey from being labelled an underachiever at school to becoming a globally recognized authority in Lean, Six Sigma, and leadership development. Together, they explore how technology and AI are reshaping operational environments, why the human side of change is more important than ever, and how leaders can build high performance cultures that thrive alongside automation.

In this episode, Matt reveals:

◼️ How being labelled an underachiever sparked a lifelong drive for improvement ◼️ The moment continuous improvement “clicked” and changed his career trajectory ◼️ Why Lean is fundamentally about developing people, not cutting costs ◼️ The danger of focusing on efficiency before culture ◼️ How small improvements compound into massive performance gains ◼️ The power of observing work at the source before proposing solutions ◼️ Why early career change efforts often fail without engagement ◼️ A real world example of simple innovation that transformed performance ◼️ Lessons learned from Royal Mail to Amazon scale operations ◼️ How robotics removed waste without replacing human value ◼️ The evolution from manual data collection to AI driven dashboards ◼️ Why understanding data matters more than collecting more of it ◼️ The risks of blindly trusting AI generated insights ◼️ Why the future of transformation is human centric ◼️ How to engage people before implementing change

Key Learnings

✔ Lean is about developing people before optimizing processes ✔ Sustainable performance starts with culture ✔ Small improvements compound over time ✔ Engagement determines whether change sticks ✔ Technology should remove waste, not human value ✔ AI accelerates analysis but still requires human judgment ✔ Data literacy is critical in an AI driven world ✔ Leaders must prioritize the human side of transformation ✔ Continuous improvement is a mindset, not a project ✔ Cultural alignment determines long term success

💬 Matt’s Most Powerful Quotes

“Lean is about developing people.” “If you focus only on saving money, you will fail.” “The biggest variable in change is people.” “Technology should remove waste, not replace value.” “Understanding the data matters more than collecting it.”

Follow Matt Sims

• LinkedIn: Matt Sims https://www.linkedin.com/in/matt-sims-38173427/ • Website: Ever-So-Lean https://www.eversolean.com/ • Instagram: https://www.instagram.com/matt_sims_uk/ • X: https://twitter.com/MattSims_UK • YouTube: https://www.youtube.com/@matsims970 • Facebook: https://www.facebook.com/matsimsradio

Follow Matt Zembruski (Host)

• Website: https://leadingaiagility.com
• LinkedIn: https://www.linkedin.com/in/mattzembruski/
• Email: matt@leadingaiagility.com
• Phone/Text/WhatsApp: +1 978-618-5778
• Facebook: https://www.facebook.com/mzembruski
• Instagram: https://www.instagram.com/thelifeofmattz/

In this episode of the AI Accelerator Podcast, host Matt Zembruski sits down with Jacqueline Strominger, Master Networker, Growth Strategist, and High Performance Leadership Coach.

For more than two decades, Jacqueline has helped CEOs, entrepreneurs, and business leaders transform networking from a transactional activity into a strategic driver of revenue, referrals, and influence. As the founder of Missing Link Network and creator of the LEAP to Your Success framework, she teaches leaders how to turn who they know into what they grow.

Together, Matt and Jacqueline explore what most professionals get wrong about networking, how AI can enhance authentic relationship building, and why intentional follow up is the real competitive advantage.

In this episode, you will learn:

◼️ Why most networking remains transactional instead of relational ◼️ The mindset shift from selling to serving ◼️ How to build trust based systems that drive referrals ◼️ The difference between introductions and real relationships ◼️ Why “What do you do?” is often the wrong first question ◼️ How vulnerability builds business faster than pitching ◼️ Practical ways AI supports authentic relationship building ◼️ Using AI for event preparation and research ◼️ How to capture networking notes in real time ◼️ Automating personalized follow up without losing authenticity ◼️ Leveraging AI as a strategic assistant ◼️ Turning conversations into revenue opportunities ◼️ Building a referral ecosystem that compounds over time ◼️ Why relationship energy determines long term growth

Key Learnings

✔ Networking is a long term growth strategy, not a short term transaction ✔ Trust builds revenue faster than pitching ✔ Authenticity scales when systems support it ✔ AI accelerates preparation and follow up ✔ Personalized follow up creates competitive advantage ✔ Research builds confidence before conversations ✔ Relationship capital compounds over time ✔ Leaders who master connection outperform those who only sell

💬 Most Powerful Quotes

“People do business with people they know, like, and trust.” “Stop asking what someone does before you know who they are.” “AI does not replace relationships. It strengthens them.” “Networking is not transactional. It is transformational.” “Feed AI the right information and it becomes your strategic assistant.”

Follow Jacqueline Strominger (Guest)

• LinkedIn: Jacqueline Strominger https://www.linkedin.com/in/jstrominger/
• Website: LEAP to Your Success https://leaptoyoursuccess.com/

Follow Matt Zembruski (Host)

• Website: https://leadingaiagility.com
• LinkedIn: https://www.linkedin.com/in/mattzembruski/
• Email: matt@leadingaiagility.com
• Phone/Text/WhatsApp: +1 978-618-5778
• Facebook: https://www.facebook.com/mzembruski
• Instagram: https://www.instagram.com/thelifeofmattz/

In this episode of the AI Accelerator Podcast, host Matt Zembruski sits down with Ondra Němčík, coach, thinker, and builder working at the intersection of technology, psychology, and human well-being.

Ondra shares his deeply personal journey from appearing happy and successful on the outside while struggling with anxiety and suicidal thoughts, to rebuilding genuine inner peace through applied psychology, neuroscience, and nervous system regulation. Together, they explore why high achievers in tech are especially vulnerable to burnout, how modern work breaks our natural energy cycles, and how humans can build a healthier relationship with technology.

In this episode, you will learn:

◼️ Why high achievers often struggle silently with anxiety ◼️ The hidden mental health cost of fast-moving tech environments ◼️ How constant stimulation disrupts the nervous system ◼️ Why modern work breaks the natural cortisol cycle ◼️ The difference between feeling tired and being truly rested ◼️ How stress becomes addictive for high performers ◼️ What nervous system reprogramming really means ◼️ How subconscious “if this then that” patterns drive behavior ◼️ Why traditional productivity tools often fail ◼️ How RoboHumanism reframes humans as biological systems ◼️ Using engineering language to understand emotions and stress ◼️ Building a healthy relationship between humans and technology ◼️ Why finishing the energy loop is critical for mental health ◼️ How technology can support well-being instead of draining it

Key Learnings

✔ High performance without recovery leads to burnout ✔ Anxiety often hides behind external success ✔ The nervous system needs completion, not distraction ✔ Stress can become an unconscious identity ✔ Humans are biological systems with limits ✔ Productivity improves when stress decreases ✔ Technology should support humans, not override biology ✔ Awareness of subconscious patterns enables change ✔ Inner peace is a trainable skill ✔ Sustainable success requires nervous system regulation

💬 Most Powerful Quotes

“I looked happy and successful, but inside I was falling apart.” “Stress becomes addictive when we link it to productivity.” “Scrolling feels like rest, but it never completes the energy cycle.” “We are biological machines with hardware, software, and an operator.” “Technology should help us finish the loop, not trap us in it.”

Follow Ondra Němčík (Guest)

• Website: https://robohumanist.com/
• LinkedIn: https://www.linkedin.com/in/robohumanist/
• Facebook: https://www.facebook.com/ondra.robohumanist

 Follow Matt Zembruski (Host)

• Website: https://leadingaiagility.com
• LinkedIn: https://www.linkedin.com/in/mattzembruski/
• Email: matt@leadingaiagility.com
• Phone/Text/WhatsApp: +1 978-618-5778
• Facebook: https://www.facebook.com/mzembruski
• Instagram: https://www.instagram.com/thelifeofmattz/

In this episode of the AI Accelerator Podcast, host Matt Zembruski sits down with Daniel Cohen-Dumani, a technologist with over 30 years of experience leading digital transformation across industries.

Daniel shares why this AI moment is fundamentally different from past technology cycles, why many professional services firms are facing an existential challenge, and why simply adding AI tools without rethinking business models is not enough. Together, they explore how leaders can adopt AI responsibly while preserving judgment, empathy, and human connection.

In this episode, you will learn:

◼️ Why AI represents a fundamentally different technology moment ◼️ How professional services firms are facing an existential challenge ◼️ Why focusing on tools instead of problems leads to failed AI initiatives ◼️ The limits of productivity gains without clear outcomes ◼️ Why billing by the hour breaks down in an AI-driven world ◼️ How business models must shift toward value and outcomes ◼️ The emotional and identity challenges AI creates for knowledge workers ◼️ Why human judgment, empathy, and trust still matter ◼️ How leaders can reduce fear while encouraging experimentation ◼️ The danger of top-down AI rollouts without cultural readiness ◼️ Why bottom-up experimentation leads to better AI adoption ◼️ How AI can amplify humans rather than replace them ◼️ What AI-native professional services firms may look like ◼️ The future of institutional memory and domain-specific AI ◼️ Why transparency and trust are critical in AI systems

Key Learnings

✔ AI adoption must start with the problem, not the tool ✔ Professional services business models are under pressure ✔ Billing by time breaks down when work compresses into minutes ✔ Human judgment and empathy remain irreplaceable ✔ AI should amplify people, not erase them ✔ Fear and resistance are natural parts of AI transformation ✔ Bottom-up experimentation drives better outcomes ✔ Trust, transparency, and accuracy are essential in AI systems ✔ Firms that delay rethinking their model risk falling behind

💬 Most Powerful Quotes

“This is not just another technology cycle. This one is fundamentally different.” “AI compresses weeks of work into minutes, and that breaks old business models.” “The problem is not the tool. The problem is what you are trying to solve.” “AI should amplify humans, not replace them.” “The future of professional services is value, not hours.”

Follow Daniel Cohen-Dumani (Guest)

• Website: https://www.experiolabs.ai/
• LinkedIn: https://www.linkedin.com/in/dcohendumani/
• Company LinkedIn: https://www.linkedin.com/company/experio-labs/
• X: https://x.com/dcohendumani
• Instagram: https://www.instagram.com/experiolabs/

 Follow Matt Zembruski (Host)

• Website: https://leadingaiagility.com
• LinkedIn: https://www.linkedin.com/in/mattzembruski/
• Email: matt@leadingaiagility.com
• Phone/Text/WhatsApp: +1 978-618-5778
• Facebook: https://www.facebook.com/mzembruski
• Instagram: https://www.instagram.com/thelifeofmattz/

In this episode of the AI Accelerator Podcast, host Matt Zembruski sits down with Chaminda Tennakoon, CEO of CT Marketing, to explore how practical AI adoption is transforming marketing execution, team efficiency, and client results.

Chaminda shares his journey from accountant to founder, the hard lessons learned from a failed startup, and how those experiences shaped a fundamentally different approach to building a marketing firm. Together, they break down how AI is being embedded into real workflows to reduce errors, improve quality, scale delivery, and allow people to focus on strategic work instead of repetitive tasks.

In this episode, you will learn:

◼️ How a failed startup led to a complete rethink of marketing and execution ◼️ Why many agencies struggle due to lack of systems, not lack of effort ◼️ How AI training rapidly changed team effectiveness ◼️ Reducing team size while increasing output and quality ◼️ Why AI should support people rather than replace them ◼️ Practical examples of AI used in day-to-day marketing operations ◼️ Using AI to qualify leads more accurately ◼️ How AI improves consistency and brand voice ◼️ Why prompting skill matters more than tools ◼️ Hiring talent with AI capability as a growth advantage ◼️ Automating onboarding, recruitment, and internal workflows ◼️ Shifting teams toward higher-value, strategic work ◼️ Why businesses delaying AI adoption are falling behind ◼️ The mindset shift leaders need to unlock AI’s full value

Key Learnings

✔ AI delivers the greatest impact when paired with skilled people ✔ Systems drive results more than individual effort ✔ Prompting skill is a competitive advantage ✔ AI improves accuracy and consistency ✔ Teams should focus on thinking, not repetition ✔ Hiring AI-capable talent accelerates growth ✔ Automation enables better strategic decisions ✔ Businesses that delay AI adoption risk losing ground

💬 Most Powerful Quotes

“AI does not replace people. It allows them to do what they are meant to do.” “The issue is not the AI. It is how people use it.” “Once the team understood AI, everything changed.” “Companies using AI properly are already ahead.” “You cannot afford to ignore AI anymore.”

Follow Chaminda Tennakoon (Guest)

• Website: https://www.ct.marketing/
• LinkedIn: https://www.linkedin.com/in/ctennakoon/

 Follow Matt Zembruski (Host)

• Website: https://leadingaiagility.com
• LinkedIn: https://www.linkedin.com/in/mattzembruski/
• Instagram: https://www.instagram.com/thelifeofmattz/

In this episode of the AI Accelerator Podcast, host Matt Zembruski sits down with Dr. Felicia Newhouse, Founder of AI-Powered Women, to explore the deeper human, psychological, and leadership implications of the AI era.

With a rare background spanning transformational psychology, product leadership, mindfulness, and emerging technologies, Felicia brings a powerful perspective on human-centered AI, regenerative leadership, and why slowing down may be the most important leadership skill in a world obsessed with speed. Together, they examine how AI is reshaping identity, work, leadership, and the future of knowledge itself — and why inclusion, consciousness, and inner resilience are no longer optional.

In this episode, Felicia reveals:

◼️ Why AI is fundamentally different from previous technology shifts ◼️ How AI is reshaping not just work — but identity and purpose ◼️ Why “soft skills” are becoming tomorrow’s hardest leadership skills ◼️ The risks of speed without reflection in AI-driven organizations ◼️ How chronic acceleration degrades judgment, trust, and creativity ◼️ Why psychological safety is critical in the AI era ◼️ How AI is changing the way knowledge is created and validated ◼️ The hidden dangers of bias and missing perspectives in AI systems ◼️ Why women and underrepresented voices are essential to responsible AI ◼️ What regenerative leadership really means in practice ◼️ How leaders can intentionally slow down to make better decisions ◼️ Why AI presents both an existential risk and an evolutionary opportunity ◼️ How awe, mindfulness, and consciousness counterbalance AI-driven burnout ◼️ What the future of leadership demands from humans — not machines

Key Learnings

✔ AI adoption is as much a human challenge as a technical one ✔ Speed without recovery degrades leadership effectiveness ✔ Psychological safety is essential in AI-driven workplaces ✔ Human-centered AI requires inclusion and diverse perspectives ✔ Regenerative leadership focuses on long-term systemic impact ✔ Conscious leadership balances pace, purpose, and responsibility ✔ AI reshapes how knowledge is created — and who gets to create it ✔ The future of work depends on inner resilience as much as skill

💬 Felicia’s Most Powerful Quotes

“Yesterday’s soft skills are tomorrow’s hard skills.” “If everything is urgent, nothing is wise.” “AI gives us the opportunity to step more deeply into our humanity.” “Speed without reflection degrades judgment, trust, and creativity.” “This moment requires a completely new leadership paradigm.”

Follow Dr. Felicia Newhouse (Guest)

• Website: http://www.aipoweredwomen.com/
• Instagram: https://www.instagram.com/aipoweredwomensummit
• LinkedIn Group: https://www.linkedin.com/groups/15604043/

Follow Matt Zembruski (Host)

• Website: https://leadingaiagility.com
• LinkedIn: https://www.linkedin.com/in/mattzembruski/
• Instagram: https://www.instagram.com/thelifeofmattz/

AI is often framed as a way to save time — but when applied thoughtfully, it can also unlock clarity, reduce complexity, and help leaders make better decisions.

In this episode of the AI Accelerator Podcast, host Matt Zembruski sits down with Joe Anderson, Founder of Connex E-Commerce, to explore how automation, AI, and disciplined systems design can transform financial operations without losing the human element.

Joe shares his rare journey from building his first website at age 11 to growing a bootstrapped software company from a $20 investment to over $8 million in gross revenue. Together, they unpack how AI can remove low-value work, improve financial visibility, and give business owners back their most valuable resource — time.

In this episode, Joe reveals:

◼️ How building his first website at age 11 shaped his problem-solving mindset ◼️ Why finding “workarounds” is a core entrepreneurial skill ◼️ Growing a software company without investors or formal technical training ◼️ Why customer service — not flashy marketing — fueled long-term growth ◼️ The real cost of manual financial reconciliation ◼️ How automation freed up 40+ hours per month ◼️ Using AI to improve financial clarity and decision-making ◼️ How AI identifies revenue concentration and operational inefficiencies ◼️ Why more products and channels often add complexity instead of growth ◼️ What AI should automate — and what must remain human ◼️ Why accountability and judgment cannot be delegated to machines ◼️ Common mistakes businesses make when adopting AI ◼️ Practical first steps for SMBs feeling behind on AI ◼️ The importance of growth mindset in automation and systems change ◼️ Where AI will — and will not — transform accounting and finance

Key Learnings

✔ AI delivers value when paired with human judgment ✔ Automation should remove low-value, repetitive work ✔ Financial clarity improves decision-making at every level ✔ Complexity often hides inside growth ✔ AI is best used as an advisor — not a decision-maker ✔ Accountability must always remain human ✔ Growth mindset is essential for effective automation ✔ Time saved through systems creates space for leadership and well-being

💬 Joe’s Most Powerful Quotes

“There are workarounds everywhere — you just have to look for them.” “Automation gave me back 40 hours a month.” “AI is great at insight, not accountability.” “More products often add complexity, not growth.” “If a task requires empathy and judgment, it belongs to people.”

Follow Joe Anderson (Guest)

• LinkedIn: https://www.linkedin.com/in/joseph-anderson-a911125/
•  Website: http://connexecommerce.com/

 Follow Matt Zembruski (Host)

• Website: https://leadingaiagility.com
• LinkedIn: https://www.linkedin.com/in/mattzembruski/
• Instagram: https://www.instagram.com/thelifeofmattz/

In this episode of the AI Accelerator Podcast, host Matt Zembruski, Founder & CEO of AI Agility, sits down with Maurice Hampton, Designated Managing Broker and CEO of Centered International Realty Corporation.

Maurice shares how a people-centered, community-driven philosophy shapes his work in real estate — and how AI has become a powerful partner in helping clients make confident, informed decisions. From first-time homebuyers to senior executives, this conversation explores how technology can support trust, reduce risk, and elevate service without replacing human judgment

In this episode, Maurice reveals:

◼️ Why homeownership is more than a financial investment — it’s an investment in community

◼️ How a people-centered mindset shapes leadership in real estate

◼️ Maurice’s journey into real estate and founding Centered International Realty

◼️ The emotional and practical challenges faced by first-time homebuyers

◼️ How AI became a practical tool in Maurice’s daily workflow

◼️ Using AI to synthesize complex research and large data sets

◼️ How AI helps tailor information to different learning styles

◼️ Practical ways AI improves client communication and decision-making

◼️ Why AI should augment professional judgment, not replace it

◼️ Using AI for compliance, accuracy, and risk reduction in regulated industries

◼️ How AI helps small brokerages compete with larger firms

◼️ The future of real estate professionals in an AI-enabled industry

◼️ Why execution, discipline, and human oversight remain essential

Key Learnings

✔ AI delivers the most value when paired with human judgment

✔ People-centered leadership remains essential, even with advanced technology

✔ AI helps professionals process complex data more effectively

✔ Tailored communication builds trust and confidence

✔ Compliance and accuracy are critical in regulated industries

✔ AI enables smaller teams to compete at a higher level

✔ Learning by doing accelerates confidence and capability

✔ Technology should serve people — not the other way around

💬 Maurice’s Most Powerful Quotes

“Homeownership is not just a financial investment — it’s an investment in community.”

“AI is not going to replace me; it needs me as the human source of judgment.”

“AI allows me to customize information to how people actually learn.”

“A missed detail in real estate can cost thousands — accuracy matters.”

“Technology is here to serve people, not the other way around.”

Follow Maurice Hampton (Guest)

Website: https://circg.com/

Youtube: https://www.youtube.com/channel/UCBWJApNcUpfolyGBRyfo8dg

Facebook: https://www.facebook.com/maurice.hampton.31

Instagram: https://www.instagram.com/centered_realty/

Follow Matt Zembruski (Host)

Website: https://leadingaiagility.com

LinkedIn: https://www.linkedin.com/in/mattzembruski/

Email: matt@leadingaiagility.com

Phone/Text/WhatsApp: +1 978-618-5778

Facebook: https://www.facebook.com/mzembruski

Instagram: https://www.instagram.com/thelifeofmattz/

In this episode of the AI Accelerator Podcast, host Matt Zembruski sits down with Bhrugu Giri, CTO of PraxisPro, to explore how AI can augment creativity, storytelling, leadership, and real-world work — especially in highly regulated industries.

Bhrugu brings a rare blend of deep technical rigor and human-centered thinking, explaining why AI is best understood as a force multiplier — one that levels the playing field, unlocks human potential, and enables people to do their most meaningful work more effectively. From enterprise AI systems to everyday workflows, this conversation bridges the gap between technology and humanity.

In this episode, Bhrugu reveals:

◼️ Why AI is a mirror of human ingenuity — not a replacement for it ◼️ How AI levels the playing field for non-native English speakers and underrepresented voices ◼️ Why storytelling is critical to successful AI adoption ◼️ How AI reduces fear by making complex systems more relatable ◼️ The difference between using AI tools and building real AI systems ◼️ Why most resistance to AI comes from uncertainty — not reality ◼️ How AI agents work in practice using real-world analogies ◼️ Why regulated industries need discipline, not shortcuts, in AI adoption ◼️ How AI enables real-time learning, practice, and performance improvement ◼️ Why learning by doing is the fastest way to grow with AI

Key Learnings

✔ AI is an amplifier of human creativity — not a substitute ✔ Storytelling makes AI accessible and reduces resistance ✔ You don’t need technical expertise to benefit from AI ✔ Regulated industries require disciplined AI architecture ✔ Real-time practice beats traditional training models ✔ Fear of AI comes from not understanding how it works ✔ Learning by doing is the fastest way to adopt AI ✔ Human judgment remains essential — AI enhances it

💬 Bhrugu’s Most Powerful Quotes

“AI is a mirror that reveals the essence of human ingenuity.” “AI is a force multiplier — it amplifies ideas that already exist.” “AI should augment our most meaningful work, not replace it.” “Storytelling brings down objections and builds trust with AI.” “There is no substitute for learning by doing.”

Follow Bhrugu Giri (Guest)

LinkedIn: https://www.linkedin.com/in/bhrugu/ Email: bhrugu@praxispro.ai Website: https://www.praxispro.ai/

Follow Matt Zembruski (Host)

Website: https://leadingaiagility.com LinkedIn: https://www.linkedin.com/in/mattzembruski/ Email: matt@leadingaiagility.com Phone/Text/WhatsApp: +1 978-618-5778 Facebook: https://www.facebook.com/mzembruski Instagram: https://www.instagram.com/thelifeofmattz/

In this episode of the AI Accelerator Podcast, host Matt Zembruski sits down with Pini Reznik, CEO & Co-Founder of RE:CINQ to explore what it really means for organizations to become AI Native.

Drawing on his experience leading Cloud Native transformations — and authoring two influential books — Pini explains why AI adoption is as much about culture, mindset, and operating models as it is about technology. Together, they unpack how leaders, teams, and even students can use AI today to become dramatically more effective — without losing the human edge.

In this episode, Pini reveals:

◼️ What AI Native actually means — and why it’s more than just adding AI features ◼️ How Cloud Native lessons apply directly to AI transformation ◼️ Why most AI proof-of-concepts fail (and how to avoid it) ◼️ The difference between cost reduction and true value creation with AI ◼️ How executives can use AI as a daily thinking partner ◼️ Why AI is leveling the playing field for non-technical professionals ◼️ How students and young professionals are becoming “unfairly productive” with AI ◼️ The importance of asking better questions — not just better prompts ◼️ Why resistance to AI mirrors every major technology shift in history ◼️ How to start using AI today — even if you feel behind or intimidated

Key Learnings

✔ AI Native is a fundamental shift, not a feature upgrade ✔ You don’t get AI benefits without changing culture, structure, and processes ✔ AI excels at editing, structuring, and pattern recognition — humans bring originality ✔ Asking the right questions matters more than the tool you use ✔ AI dramatically accelerates learning and productivity ✔ Non-technical professionals can now create at a technical level ✔ Resistance to AI is normal — and always temporary ✔ The fastest way forward is to start doing, not over-planning

💬 Pini’s Most Powerful Quotes

“You don’t get the benefits of AI unless you change how you work.” “AI doesn’t create original ideas — humans do. AI makes them better.” “If you’re not using AI, everything simply takes much longer.” “AI Native is not about optimization — it’s about value creation.” “There is no alternative to starting. Just do something.”

Follow Pini Reznik (Guest)

• LinkedIn: https://www.linkedin.com/in/pinireznik/
• Instagram: https://www.instagram.com/pinireznik/
• Facebook: https://www.facebook.com/pini.reznik/

 Follow Matt Zembruski (Host)

• Website: https://leadingaiagility.com
• LinkedIn: https://www.linkedin.com/in/mattzembruski/
• Email: matt@leadingaiagility.com
• Phone/Text/WhatsApp: +1 978-618-5778
• Facebook: https://www.facebook.com/mzembruski
• Instagram: https://www.instagram.com/thelifeofmattz/

A survivor herself, Anne has taken her pain and turned it into a mission: to teach millions how to recognise manipulation, reclaim their power, and “become more” of who they are meant to be.

Anne is also a pioneer in using AI inside the creative process, building custom GPTs for art, writing, grant funding, idea development, and scaling social impact.

In this episode, Anne reveals:

◼️ How she went from art collector to world-exhibiting artist ◼️ The truth about manipulation — and why most people never see it coming ◼️ How Wonder Woman Now educates through immersive storytelling ◼️ Why she built a women-empowerment app using AI ◼️ The exact way she uses custom GPTs daily (grants, marketing, concept design & more) ◼️ Why AI is the greatest tool for non-technical creatives ◼️ How art + AI can reach people who will never walk into a gallery ◼️ Her new portrait series “Becoming More” — and the message behind it ◼️ Why purpose, not talent, is the true driver of creative success

Key Learnings

✔ AI is not technical — it’s a language anyone can learn ✔ Custom GPTs become “a team of smart assistants” for creators ✔ Abuse is often invisible — art makes the invisible visible ✔ Purpose accelerates mastery more than talent does ✔ Empowerment begins with awareness and education ✔ Creativity + AI can reach millions more than art alone ever could

💬 Anne’s Most Powerful Quotes

“If pain isn’t transformed, it is transmitted.” “AI became my creative partner — a team of super-smart assistants.” “If I can learn AI, anyone can. It’s just another language.” “Not everyone goes to galleries, but everyone deserves empowerment.” “I want to help women become more of who they truly are.”

Follow Anne Plaisance (Guest)

Website: https://www.anneplaisance.com/ Instagram: https://www.instagram.com/anneplaisance/?hl=en Facebook: https://www.facebook.com/anne.plaisance/ LinkedIn: https://www.linkedin.com/in/theanneplaisance/

Follow Matt Zembruski (Host)

Website: https://leadingaiagility.com LinkedIn: https://www.linkedin.com/in/mattzembruski/ Email: matt@leadingaiagility.com Phone/Text/WhatsApp: +1 978-618-5778 Facebook: https://www.facebook.com/mzembruski Instagram: https://www.instagram.com/thelifeofmattz/