A Class Act: AI, Data & Leadership

Most organisations adopting AI are bolting agentic AI onto the same old processes, then wondering why nothing actually changes.

In this season 2 finale of A Class Act, Michael Young sits down with Stuart Bell, Head of AI & Innovation M&G who went from Java developer to shaping how some of the biggest regulated financial-services firms adopt agentic AI at enterprise scale. 

It’s a straight-talking, practical conversation about why the gap between a slick demo and real production is a strategy gap, why you should treat AI agents as products rather than one-off projects, and the question Stuart says every leader should be asking, and almost nobody is.

What you’ll discover⬇️

☑️Why starting from your existing process only ever gives you incremental AI
☑️Why the demo-to-production gap is really a strategy gap (and the three reasons slick demos die)
☑️What changes when you treat AI agents as products, not one-off projects
☑️How to reframe guardrails from risk controls into UX metrics your teams actually want to hit
☑️How to decide what to actually build when every business unit swears their use case comes first
☑️The value-vs-complexity and risk-vs-reuse framework Stuart uses 
☑️Why experimenting up front and benchmarking models protects you when the model underneath changes
☑️What “responsible AI” really looks like when it’s working
☑️Why governance done right lets you move faster, not slower
☑️Stuart’s closing advice for any leader who wants to build agentic AI capability

Guest Information⬇️
Stuart Bell is Head of AI & Innovation at M&G, a senior AI leader shaping how large, regulated financial-services organisations adopt agentic AI at enterprise scale. He began his career as a Java developer before moving through software architecture into CTO positions across private-equity-backed and venture-backed businesses as well as large corporates, including a spell at Sky over a decade ago.
Today he focuses on getting agentic AI out of the demo and into production, safely, inside a regulated environment.

Connect with Stuart Bell on LinkedIn⬇️
https://www.linkedin.com/in/stuart-bell-a355283/

Please note: The views expressed by the guest in this episode are their own and do not reflect those of their current or former employers.

About Your Host ⬇️
Michael Young is the Founder & CEO of MBN Solutions and host of A Class Act: Conversations in Data & Leadership. With nearly two decades of experience helping organisations build high-performing data, analytics, and AI teams, he brings frontline insight into what makes exceptional talent and leadership.

Connect with MBN Solutions
If you’re hiring for data or AI leadership roles, scaling AI capability, or rethinking how talent supports your AI strategy, the team at MBN partners with organisations to build data and AI teams that actually deliver.

MBN Solutions on LinkedIn ⬇️ 
Explore industry updates, groundbreaking projects, and the latest in data and analytics talent. Join the conversation and discover how MBN Solutions is shaping the future of data leadership. Visit the company page here: https://www.linkedin.com/company/mbn-recruitment-solutions/

For questions, guest recommendations, or to connect:
Email: michael@mbnsolutions.com
Visit MBN Solutions website at www.mbnsolutions.com

Subscribe & Follow⬇️

Enjoying the series? Don’t miss an episode. Follow A Class Act wherever you get your podcasts and leave us a review to help more listeners discover these conversations in data and leadership.

In this episode of A Class Act, Michael Young sits down with Stuart McMeechan, EMEA Deployment Engineering Leader at OpenAI. 

Stuart leads the team that OpenAI sends into the biggest enterprises in Europe to help them get AI into production and he’s seen first-hand why most never make it past the pilot.

In this conversation, they get into👇

☑️ What OpenAI’s AI deployment engineering team actually does and the two objectives behind every project
☑️ The three types of customer OpenAI works with
☑️ The difference between organisations actually scaling enterprise AI versus those staying stuck in experimentation
☑️ What’s really blocking the move from pilot to production (most of it isn’t technical)
☑️ What separates organisations genuinely ready for AI from those just experimenting
☑️ The culture changes required to make AI implementation actually work and how to find the “wizards” already driving AI inside your teams
☑️ Where humans stay irreplaceable, and how roles are already being redrawn
☑️ Is AI moving faster than organisations can adapt?
☑️ Why OpenAI’s release cadence went from 15 months to six weeks and what that means for planning

Guest Information👇

Stuart McMeechan is EMEA Deployment Engineering Leader at OpenAI, where he leads a team of AI architects and engineers helping Europe’s largest enterprises adopt AI at scale. His team works directly with organisations to define AI strategy, design target architectures, build implementation approaches, and develop evaluation frameworks - turning OpenAI’s capabilities into real business impact.

Connect with Stuart McMeechan on LinkedIn:
https://www.linkedin.com/in/stuartmcmeechan/

Please note: The views expressed by the guest in this episode are their own and do not reflect those of their current or former employers.

About Your Host👇

Michael Young is the Founder & CEO of MBN Solutions and host of A Class Act: Conversations in Data & Leadership. With nearly two decades of experience helping organisations build high-performing data, analytics, and AI teams, he brings frontline insight into what makes exceptional talent and leadership.

Connect with MBN Solutions👇

If you’re hiring for data or AI leadership roles, scaling AI capability, or rethinking how talent supports your AI strategy, the team at MBN partners with organisations to build data and AI teams that actually deliver. Visit MBN Solutions website at www.mbnsolutions.com

MBN Solutions on LinkedIn – Join the conversation and discover how MBN Solutions is shaping the future of data leadership. Visit the company page here: linkedin.com/company/mbn-recruitment-solutions

For questions, guest recommendations, or to connect:
Email: michael@mbnsolutions.com

Subscribe & Follow👇

Enjoying the series? Don’t miss an episode. Follow A Class Act wherever you get your podcasts and leave us a review to help more listeners discover these conversations in data and leadership.

In this episode of A Class Act, Michael sits down with Andy McMahon, Director of AI & MLOps Engineering at Barclays, Oxford lecturer, and author of Machine Learning Engineering with Python.

Andy went from a physics PhD at Imperial College to leading AI engineering at one of the world’s largest banks, and he’s got a sharp take on why most AI never makes it out of the demo.

In this conversation, they get into⬇️ 
✔️Why the gap between AI that demos well and AI that works in production has never been wider
✔️The 'trust infrastructure' most teams skip and why Andy calls them zero-regret investments
✔️What changed when AI engineering replaced MLOps as the paradigm and what stayed exactly the same
✔️How to spot genuinely good AI talent
✔️Why imposter syndrome is a signal you're in the right place
✔️The shift from data science to AI engineering and what that means for hiring and team structure
✔️Andy's take on what people are getting wrong about AI right now
✔️Responsible AI in practice: how to make it real and not a tick-box exercise
✔️Building a career portfolio that outlasts any single role

Guest Information

Andy McMahon is Director of AI & MLOps Engineering at Barclays, where he leads teams building production-grade AI systems across the bank. He holds a PhD in theoretical physics from Imperial College London and is the author of Machine Learning Engineering with Python (Packt), now writing the third edition — a rewrite shifting focus from MLOps to AI engineering. Andy lectures at the University of Oxford, has been named one of Computing Magazine's Top 100 Leaders in IT (2026), and co-writes Forward Deploy, a Substack on practical AI engineering with Matthew Higgs.

Connect with Andy McMahon on LinkedIn:
https://www.linkedin.com/in/andy-mcmahon/

Read Forward Deploy on Substack:
Forward Deploy Substack

Paper mentioned: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=6843118

Podcast - https://linktr.ee/airightpodcast

Please note: The views expressed by the guest in this episode are their own and do not reflect those of their current or former employers.

About Your Host

Michael Young is the Managing Director of MBN Solutions and host of A Class Act: Conversations in Data & Leadership. With nearly two decades of experience helping organisations build high-performing data, analytics, and AI teams, he brings frontline insight into what makes exceptional talent and leadership.

Subscribe & Follow
Enjoying the series? Don’t miss an episode. Follow A Class Act wherever you get your podcasts and leave us a review to help more listeners discover these conversations in data and leadership.

Connect with MBN Solutions
If you’re hiring for data or AI leadership roles, scaling AI capability, or rethinking how talent supports your AI strategy, the team at MBN partners with organisations to build data and AI teams that actually deliver.

MBN Solutions on LinkedIn – Explore industry updates, groundbreaking projects, and the latest in data and analytics talent. Visit the company page here: linkedin.com/company/mbn-recruitment-solutions

For questions, guest recommendations, or to connect:
Email: michael@mbnsolutions.com
Visit MBN Solutions website at www.mbnsolutions.com

If you run a data team, you already know that the hardest part of being a great data leader isn’t always the technology.
In this episode of A Class Act, host Michael Young chats with Asia Faulds, Head of Data Science at Booksy. 
Asia has built data science teams from the ground up at the BBC, Trustpilot, and now Booksy, and she’s seen first-hand why brilliant technical teams still fail when prioritisation breaks down.
In this conversation, they get into:
Why most data teams don’t fail technically
What it’s actually like building a data science function from zero at Booksy
How Gen AI has expanded the scope of the data science role and what hasn’t changed
Why producing 200 dashboards instead of 2 doesn’t mean your team is more productive
The difference between activity and progress, and how to tell which one your team is doing
Why sometimes a well-written SQL script beats a neural network
How to protect your team’s energy and focus as a data leader
The one thing Asia says every listener should do this week

Guest Information
Asia Faulds is Head of Data Science at Booksy, the two-sided marketplace connecting beauty and wellness providers with consumers. She’s building the company’s first data science and applied AI function from scratch, defining the strategy, hiring the team, and establishing ML infrastructure.
Before Booksy, Asia spent five years at Trustpilot, progressing from individual contributor to management across product and go-to-market data science. Before that, she built recommendation engines for BBC Sounds at the BBC. She holds a Master’s in Physics from the University of Edinburgh and writes The Data Pragmatist on Medium.
Connect with Asia Faulds on LinkedIn:
https://www.linkedin.com/in/asia-data/
Read The Data Pragmatist on Medium:
medium.com/@thedatapragmatist

About Your Host
Michael Young is the Managing Director of MBN Solutions and host of A Class Act: Conversations in Data & Leadership. With nearly two decades of experience helping organisations build high-performing data, analytics, and AI teams, he brings frontline insight into what makes exceptional talent and leadership.
Please note: The views expressed by the guest in this episode are their own and do not reflect those of their current or former employers.

Subscribe & Follow
Enjoying the series? Don’t miss an episode. Follow A Class Act wherever you get your podcasts and leave us a review to help more listeners discover these conversations in data and leadership.

Connect with MBN Solutions
If you’re hiring for data or AI leadership roles, scaling AI capability, or rethinking how talent supports your AI strategy, the team at MBN partners with organisations to build data and AI teams that actually deliver.

MBN Solutions on LinkedIn – Explore industry updates, groundbreaking projects, and the latest in data and analytics talent. Join the conversation and discover how MBN Solutions is shaping the future of data leadership. Visit the company page here.

For questions, guest recommendations, or to connect:
Email: michael@mbnsolutions.com
Visit MBN Solutions website at www.mbnsolutions.com

In this episode of A Class Act, Michael chats with Stu Kennedy, an Edge, Realtime & AI Systems Consultant, core HTMX contributor, and former film composer who worked alongside David Arnold on the Chronicles of Narnia and BBC’s Sherlock. 
Today, Stu builds real-time voice AI pipelines, contributes to the WebSocket layer in HTMX 4, and has helped companies like Anam and Pyannote push the boundaries of streaming diarisation and video avatars. 
In this conversation, they get into:
✔ How a career in maths, music, and film led to building production voice AI systems
✔ Why voice AI is fundamentally an audio problem before it’s an ML one
✔ Why platforms like VAPI, OpenAI Realtime, and others break outside demo
✔ How Stu cut ASR latency from two seconds to 350 milliseconds 
✔ Why a single senior engineer with the right tools can now outship a six-month procurement cycle
✔ LLMs and the parallels between constraining a model and constraining an orchestra
✔ An experiment where professional composers couldn’t tell a real orchestral recording from a fake one and what that really means for AI adoption
✔ A real benchmark for production readiness

Guest Information

Stu Kennedy is an Edge, Realtime & AI Systems Consultant specialising in Cloudflare-native, real-time, and AI-driven platforms. He has spent 25 years at the intersection of mathematics, music, and software, from a PhD in fluid mechanics and chaos theory to composing for film alongside David Arnold (James Bond, Narnia, Sherlock), to building music technology platforms, and now engineering production voice AI pipelines. 
He is a core contributor to HTMX, building the WebSocket implementation for HTMX 4, and has worked with companies including Anam (real-time video avatars) and Pyannote (streaming diarization). Stu has also built products including Callwell, a real-time AI sales call assistant, and Medascend, an AI-powered medical training platform built with students from Dundee University. He operates via his Ltd company on scoped, outcome-based engagements.
Connect with Stu Kennedy on LinkedIn:
https://www.linkedin.com/in/stu-kennedy/
Website: https://stukennedy.com
Also built: html.surf

About Your Host

Michael Young is the Managing Director of MBN Solutions and host of A Class Act: Conversations in Data & Leadership. With nearly two decades of experience helping organisations build high-performing data, analytics, and AI teams, he brings frontline insight into what makes exceptional talent and leadership.
Please note: The views expressed by the guest in this episode are their own and do not reflect those of their current or former employers.

Subscribe & Follow

Enjoying the series? Don’t miss an episode. Follow A Class Act wherever you get your podcasts and leave us a review to help more listeners discover these conversations in data and leadership.

Connect with MBN Solutions

If you’re hiring for data or AI leadership roles, scaling AI capability, or rethinking how talent supports your AI strategy, the team at MBN partners with organisations to build data and AI teams that actually deliver.
MBN Solutions on LinkedIn – Explore industry updates, groundbreaking projects, and the latest in data and analytics talent. Join the conversation and discover how MBN Solutions is shaping the future of data leadership. Visit the company page here.
For questions, guest recommendations, or to connect:
Email: michael@mbnsolutions.com
Visit MBN Solutions website at www.mbnsolutions.com