Waseem explains why the gap is often misunderstood. Many companies focus on technical hiring or new tools, but the real issue is confidence and capability across the wider business. People need to understand how data helps them make better decisions, not just how a platform works. That shift takes leadership focus, clear communication and continuous learning, not one-off training sessions.

The conversation breaks down:

• How organisations can combine upskilling, coaching and literacy programmes to build capability at scale.
• Why celebrating early wins and visible examples creates momentum and buy-in.
• How leaders can balance hiring specialist talent with developing the people they already have.
• What happens when centralised teams try to hold everything, and why federated decision-making often speeds up impact.
• Real lessons from clients who improved decision-making and adoption by focusing on communication, context and consistent leadership support.

Waseem also looks ahead at how AI is changing expectations of data teams. Coding remains important, but problem framing, critical thinking and asking better questions are becoming central skills as automation improves.

He closes with practical steps leaders can take today: get clear on the decisions that matter, train executives first, remove friction around data access and spend time listening to the business before rolling out solutions. Subscribe for more conversations with data and AI leaders, and explore the full series at harnham.com.

Ashish reflects on the breakthroughs that brought us here: from seq2seq models to Transformers and self-supervised learning, and why cost, scale and reliability still determine which ideas make it into production. He explains the common stumbling block teams face with GenAI: it’s easy to get to a promising proof of concept, but closing the gap to a production-ready system demands stronger engineering, cleaner data, and a clear product mindset.

The conversation looks ahead to what’s next:

• Smarter, in-product support that avoids the “please hold” loop.
• AI and robotics shifting from virtual experiments to physical tasks.
• Education reimagined with affordable tutors that encourage curiosity.
• Why GenAI is probabilistic, not deterministic, and why that matters.

On skills, Ashish is direct: embrace new tools, but go beyond them. The advantage now lies in pairing technical depth with communication, product sense, and a growth mindset. As founder of StarSpark, the first AI math teacher designed for K–12 mastery, Ashish shares how education can be transformed. StarSpark uniquely combines alignment with state standards, adaptive grade-level progression, and 100% solving accuracy with personalized, proactive teaching that no other platform delivers.

Whether you’re testing your first agent, scaling a platform, or planning your next role, this episode offers a clear-eyed view on turning GenAI from demo into lasting value.

Matt explains why effective measurement now relies on combining three approaches: attribution, Marketing Mix Modelling (MMM) and incrementality. Together, they give a clearer view of performance and help businesses build trust in their numbers.

Highlights include:

• Why moving beyond “just another dashboard” is key to linking marketing data with business growth.
• How MMM, attribution and incrementality create a common language with CFOs and senior leaders.
• The mix of technical depth, commercial awareness and clear storytelling that defines today’s analytics roles.
• Real-world results: Imperial London Hotels achieved a 73% revenue uplift, while Les Mills drove a 570% increase in new customers through a long-term measurement framework.

Looking ahead, Matt reflects on how AI is already embedded in measurement tools and why the future lies in more continuous, real-time models. He also shares advice for clients on how to get started, and for candidates on combining technical know-how with strong communication to stand out.

Catch up on this episode and explore the full podcast series here: https://thedataandaipodcast.podbean.com/ 

Nathalie shares insights on:

• Why governance and GenAI tooling are reshaping the consulting space
• How FTI Consulting built AI tools like Ariadne to solve complex, real-world problems
• What hiring data talent really looks like today—and what often gets missed
• Why soft skills like communication and adaptability matter as much as technical know-how
• The pros and cons of in-house vs off-the-shelf AI solutions, and how firms can avoid vendor lock-in

Whether you’re building an AI team from scratch or scaling existing efforts, this episode offers straight-talking insights from someone shaping the future of AI in consulting.

To mark Harnham’s 15,000 placements, Elizabeth and Charlie reflect on how data talent, technology, and customer expectations have evolved over the past two decades, and what that means for the future of work and experience design.

They cover:

• What it takes to get personalisation right at scale
• How AI is reshaping the workplace and decision-making
• The role of experimentation in creating human-centric experiences
• Why customer experience optimisation is more critical now

If you're navigating the intersection of data, AI, and customer experience, or just want to hear what the latest in innovation looks like, this episode is for you.

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Want to learn more about what 15,000 placements at Harnham means for data & ai hiring landscape?

Check out key insights from Harnham’s CEO, here: https://www.harnham.com/15000-placements-global-data-ai-insights/

Abi shares insights from her 20+ years in the industry, discussing why relying solely on data can lead to poor decisions and how combining analytics with a deep understanding of user behaviour can drive better outcomes.

They cover:

• The risks of data-only decision-making
• How to blend data with user research
• Real-world examples where human insight improved business performance
• The importance of storytelling in data analysis

If you want to learn how to improve customer experience, retention, and revenue by looking beyond the numbers, this episode is for you.

With over 25 years in the market research industry, Abhijeet shares how businesses invest heavily in product launches and advertising but often overlook the real-world customer experience. He explains why the traditional approaches to market research don’t always capture genuine consumer behaviour, and how social listening, AI, and new methodologies are helping to close the gap.

Highlights include:

• Why brands’ marketing messages don’t always match the reality of customer experience.
• The risks of ignoring the say-do gap and how it impacts brand loyalty.
• How AI can streamline research but still needs human insight for meaningful storytelling.

Abhijeet also exposes eye-opening real-world examples, from festive ad campaigns to influencer marketing fails. Keen to learn more? Tune in to the episode to find out.

Catch up on this episode and explore the full podcast series here: https://www.harnham.com/data-and-ai-podcast/ 

From the early days of small A/B tests to today's expansive, journey-wide experimentation, Chris reflects on how this scientific approach has transformed not just decision-making, but creativity itself. Highlights include:

• Why experimentation isn’t just about tweaking button colours but about unlocking bold, strategic ideas.
• Success stories that delivered significant wins for both customers and businesses.
• A look at the future of experimentation, including its role in tackling AI-driven user interactions and bridging online-offline journeys.

Curious about what makes experimentation so powerful or simply keen to learn what metrics Chris wishes he could measure? Tune in to this episode to find out.

Rob shares his journey from the early days at Santander to leading 4most, a global consultancy firm with 300 employees across multiple countries. They dive into the evolution of hiring in data, the importance of keeping a strong company culture during periods of accelerated growth, and how to effectively reward and retain top talent.

Rob also talks about the future impact of AI on consulting and the significance of regulatory measures like the FCA's consumer duty. Tune in to hear practical insights on leading a company centred around people while navigating the challenges of growth in the competitive data and AI landscape.

From the early days at Capital One to the disruptive impact of payday lending, fintech innovations, and the rise of Buy Now, Pay Later schemes, Tim shares invaluable insights into the challenges and transformations in the Credit Risk sector.

Sam & Tim discuss the shift from traditional SAS technology to open-source solutions, the impact of AI on consumer lending, and strategies for attracting top talent in this dynamic field. Join us as we delve deep into the past, present, and future of credit risk, exploring the pivotal moments and trends that shape today's financial world.

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Envisso (formerly Kinetic) turns merchant risk into a growth strategy for payments companies. Through a deep understanding of financial risk and the power of AI, their solutions enable clients to identify and mitigate credit, fraud, compliance and overall merchant risk with unprecedented clarity. They also effectively replace outdated practices like manual assessments and collateral requirements with truly merchant-centric solutions, including automated onboarding, real time monitoring of credit, fraud and compliance risks; and embedded protection via insurance. Find out more at: https://envisso.com/

Whether you're a professional in the field or simply an AI enthusiast, this episode promises to be an engaging journey through the evolving world of AI and ML. The conversation features insights on the latest advancements, considerations, and transformative potential of AI across various use cases. Join us and ponder the possibilities of what AI might achieve next.

Our experts share their expertise and explore the latest trends in the data sphere. This engaging conversation offers something for everyone, from seasoned professionals to those just beginning their journey in data.

Give it a listen and subscribe for the latest episodes.

From the evolution of the market to the balance between well-rounded and specialised skillsets, the conversation explores the critical role of data in decision-making. Our hosts also touch on the AI hype cycle, the future of AI, emerging roles in the field, and the delicate balance between regulation and innovation. The conversation then goes on to predictions for the next few years in the data and AI space.

Intro 00:00-01:32

What inspired you to start a career in data 01:32-08:40

Were there challenges for you transitioning into data 08:40-16:35

How did you go about learning the technical aspect 16:35-22:40

What are your responsibilities as a leader in data? What are the fields in data one can focus on? 22:40-31:22

What is a fun fact you found in the data industry that changed your life? 31:22-35:22

Most challenging bit of your career to date? 35:22-40:55

Any tips to overcome imposter syndrome? 40:55-45:00

How do you think employers/data industry could encourage more people from a non STEM background to join the industry?  45:00-50:33

Any advice for a non STEM grad looking to get into data? 50:33-53:27

Wrapping up 53:27-54:06

00:09-1:10 – India introducing Anita and asks her to summarise her career.

1:10-4:45 – Anita explains her career journey.

4:45-7:36 – What was your first leadership role?

07:36-11:34 - How did you end up going for the position of Global Co Chair of the Women’s Inclusion Network.

11:34 – 15:05 –How were your diversity and inclusion initiatives received at the time?

15:05-15:42 –When in your career were these initiatives taking place?

15:42 – 22:13 – What was the biggest challenge you faced in your career?

22:13 – 26:43 – What’s been the biggest success of your career?

26:43 – 31:51 – What are some of the biggest changes you’ve seen throughout your career?

31:51 – 34:33 - How inclusive policies can start important conversations, and how can we move beyond them in the future?

34:33 – 39:41 - Any advice for someone who is new to the leadership space?

39:41-41:33 - What can leaders do to facilitate diversity and inclusion?

41:33-End -Thank you’s and outros.

00:00-03:40   Intro.

03:40- 12:00 Job security in the data industry.

12:00- 19:45 Does company culture matter more than compensation for candidates leaving their current role?/What are the main reasons people leave?

19:45 – 20:33 Are you seeing hiring trends for hiring chief ML/AI management positions?

20:33-22:07 Who’s seeking jobs right now, are middle management positions or entry/senior level positions more sought out?

22:07- 24:28 Do you think hybrid/remote work models are here to stay long term?

24:28-27:06 With the rise of AI/ML are there fewer core analytics roles?

27:06-28:42 How has the current recession impacted the data industry?

28:42- 33:27 What’s driving movement and attracting talent in the marketplace?

33:27-35:57 Is equity not a prime factor?

35:57 41:30 AI

41:30- 45:15 Top 5 technologies used by data professionals.

45:15- 47:47 Do you think diversity of tools used in the data industry is a challenge for job seekers?

47:47-49:32 Within data and tech, are you seeing a trend of employees needing to do ‘everything’ (data architecture, data engineering etc.)?

49:32-53:10 What skills should be considered for a candidate ‘upskilling’ themselves?

53:10-54:32 How do you differentiate the requirement in learning Excel and PowerBI? Which one is more powerful?

54:32- 56:41 Wrapping up.

- What’s driving people to change roles

- What skills and data tools are in high demand

- The “AI storm”, and how it’s impacting the sector as a whole

- Average salary increases between roles

- And much more!

00:00-03:05 Intro

03:05-08:50 Stability through uncertainty for the data industry and pay increases 08:50-16:00 Return to office

16:00-18:05 More JD requiring more technical data skills even in insight-focused roles

18:05-27:39 Main reasons for people leaving their roles and top benefits of attracting candidates

27:39-30:00 Importance on softer skills and how to make sure your CV covers this aspect

30:00-36:19 Top benefits for attracting talent

36:19-44:00 AI and how its affecting jobs in the data & tech industry

44:00-46:00 Most popular technology used in data space

46:00-49:40 How important is cloud and which one is preferred by brands? Is AWS preferred over Azure and Google?

49:40-55:35 Are there any up-and-coming tools expected to be important next year

55:35-57:07 wrapping up

Download the UK Salary Guide here: https://datasalaryguide.harnham.com/

 If you want to learn even more about the topics discussed in this episode then pick up David's book ‘Becoming Data Literate’ here.

00:00-04:00 - Introduction to David

04:00-06:08 - What is data literacy?

06:08-27:20 - Proving the value of putting data literacy at the forefront of your data strategy?

27:20-41:15 - Discussion around AI and how it’s impacting data roles and society as a whole.

41:15-46:00 - What role do data leaders have to play in terms of increasing data literacy – the benefits of

education and upskilling in the face of AI.

46:00-50:15 - How is the role of the data leader evolving?

50:15-52:15 - Three tips for new data leaders.

52:15-54:38 - David’s question for the next guest – how do you cope with the breadth of the domain?

54:38-End - Wrapping up.

In the first ever episode of The Data & AI Podcast, Rockborne’s CEO Waseem Ali sits with Craig Civil (Director of Data Science & AI @ BSI) to talk about quantifying the benefit of data and your data team, gaining stakeholders’ trust as a data leader and his thoughts on ChatGPT. 

To access Rockborne’s whitepaper ‘Quantifying the Benefit of Data’, download here: https://rockborne.com/campaigns/whitepaper-quantifying-the-benefit-of-data/

If your company is having difficulty finding skilled data professionals, you can rely on the global leader in data & AI recruitment, staffing and talent development to assist you with your hiring needs. Find out more at www.harnham.com