Data & AI Mastery

👉 Discover how Cambridge Spark helps organisations build the data and AI capabilities needed to turn strategy into measurable impact: cambridgespark.com

In this special episode of Data & AI Mastery Dr Raoul-Gabriel Urma goes inside the Financial Conduct Authority to sit down with Jessica Rusu, Chief Data, Information and Intelligence Officer at one of the most influential regulatory bodies in the world.

The FCA oversees the conduct of more than 50,000 firms across UK financial services. Jessica sits at the centre of a question that every financial institution is grappling with right now: how do you move fast with AI while remaining genuinely accountable for outcomes?

In this episode, Jessica shares how the FCA's digital and regulatory sandboxes are cutting fintech development timelines from a year to three months, why the FCA has deliberately avoided writing new AI-specific rules, and what firms consistently underestimate when deploying AI at scale.

She also shares a practical framework for building a future-ready career in data and AI, drawing on her own journey from Ford Motor Company to eBay to the heart of UK financial regulation.

If you work in data, technology, or strategy inside a regulated industry, this is essential listening.

Be sure to follow the show wherever you get your podcasts to never miss an episode.

Enjoyed this conversation? Why not tune in to our episode with Edmund Towers, Head of Advanced Analytics & Data Science Units at the FCA:

Apple: https://podcasts.apple.com/gb/podcast/ai-regulation-and-trust-using-data-science-to-protect/id1779783413?i=1000750268699

Spotify: https://open.spotify.com/episode/3JD7g1B47xI8JJ71ROF1Vp?si=00dc012933554b40

YouTube: https://www.youtube.com/watch?v=379oyRKg-eE

Chapter Markers

(00:00) - Introduction and what responsible AI really means

(02:26) - Jessica's career journey from Ford to the FCA

(08:42) - Inside the FCA's regulatory and digital sandboxes

(14:40) - Scaling AI responsibly and what doing it badly looks like

(19:18) - Why the FCA chose not to write new AI-specific rules

(24:57) - Accelerators and blockers of AI adoption in fintech

(31:37) - The T-shaped skills framework for future careers

(35:04) - Key takeaways

Useful Links

Follow Dr Raoul-Gabriel Urma on LinkedIn: https://uk.linkedin.com/in/raoulurma

Connect with Jessica Rusu on LinkedIn: https://uk.linkedin.com/in/jessica-rusu-189134a 

Visit the Cambridge Spark Website: https://cambridgespark.com/

👉 Discover how Cambridge Spark helps organisations build the data and AI capabilities needed to turn strategy into measurable impact: cambridgespark.com

In this episode of Inside the Algorithm, Dr Jeremy Bradley sits down with Dr Gueorgui Mihaylov, Principal Data Scientist at Haleon and Visiting Research Fellow at King's College London, to explore what happens when rigorous mathematics meets the messy reality of a global consumer health supply chain.

Gueorgui walks through two of the most technically ambitious AI projects running inside Haleon today. First, the AI Inventory Planner, an ensemble of machine learning models, survival analysis, and stochastic simulation designed to reduce inventory holdings by double digits while maintaining or improving service levels. Second, the Golden Batch project, an attempt to bring real-time process control to pharmaceutical manufacturing using data-driven corridor modelling of a highly non-stationary, non-Newtonian fluid system.

The conversation covers global forecasting algorithms, Weibull-based delivery modelling, principal component analysis for process visualisation, and the long road from working prototype to enterprise adoption.

Follow Data & AI Mastery so you never miss a future episode of Inside The Algorithm.

If you want to learn more about how AI is revolutionising demand forecasting and supply chain optimisation, listen to the Data & AI Mastery episode between host Dr Raoul Gabriel Urma and Peter Laflin, Director of Data and Analytics at Morrisons: 

Apple: https://podcasts.apple.com/gb/podcast/bringing-art-to-science-using-ai-to-build-customer/id1779783413?i=1000677504555 

Spotify: https://open.spotify.com/episode/6HcwcdIGOguBZp1vADE1Z0 

YouTube: https://www.youtube.com/watch?v=NKdjiYVC9H8 

Glossary Terms:

Inventory Management: The systematic process of ordering, storing, tracking, and controlling a company’s goods to ensure the right items are available in the right quantity, place, and time.

Stochastic Phenomena: Events, processes, or systems that are inherently random, unpredictable, or probabilistic in nature, rather than deterministic.

Demand Forecasting: The process of predicting future customer demand for products or services using historical sales data, market trends, and analytical methods.  

Out-of-sample bootstrapping: A resampling technique used to estimate a model's performance on unseen data by generating multiple datasets through sampling with replacement from the original data.

Non-Newtonian Fluid: A substance whose viscosity changes when subjected to stress, agitation, or shear force, rather than remaining constant.  

IoT Device: A physical object embedded with technology, software, and sensors that allow it to connect, collect, and exchange data over the internet or networks without human intervention.

Chapter Markers

(00:00) - Episode Introduction and opening insight from Dr Gueorgui Mihaylov

(04:37) - Setting the scene: What is the AI Inventory Planner solving?

(07:17) - The challenge of supply chain unpredictability and stochastic buffering

(12:26) - Scenario simulation engine and constraint optimisation

(17:00) - Scaling the tool across a global enterprise

(19:17) - Introducing the Golden Batch project in pharmaceutical manufacturing

(25:00) - System architecture: data historian, execution environment and visualisation

(30:57) - From monitoring to closed-loop control: stages of adoption

(34:28) - Open problems at the frontier: geometric deep learning and LLM orchestration

(37:02) - Advice for practitioners entering industrial AI

Useful Links

Connect with Dr Gueorgui Mihaylov on LinkedIn: https://www.linkedin.com/in/gueorgui-mihaylov-891278197/ 

For more AI insights follow Jeremy on LinkedIn: https://uk.linkedin.com/in/jeremy-bradley

Explore Cambridge Spark’s AI upskilling programmes at https://www.cambridgespark.com

👉 Discover how Cambridge Spark helps organisations build the data and AI capabilities needed to turn strategy into measurable impact: cambridgespark.com

The AA has been keeping British drivers moving for 120 years. But behind that familiar brand, a quiet and ambitious transformation is under way.

In this episode, Dr Raoul-Gabriel Urma is joined by Nick Edwards, Group Chief Technology Officer, and Harj Johal, Managing Director of Customer Operations, to explore what the AA's guiding principle of digital convenience with human care actually means when applied to real operational decisions.

They cover how the AA deployed 1,500 ChatGPT Enterprise licences, built a 75-person champions network from the bottom up, launched an internal Dragons' Den innovation fund, and how they are now training their senior leadership in AI through a structured programme with Cambridge Spark. They also get specific about ROI measurement, managing internal AI demand, and why the most passionate technology adopters were not in the technology function.

This is an honest, practical conversation about transformation at scale and a compelling case study for any C-suite leader navigating the same journey.

Be sure to follow Data and AI Mastery on Apple Podcasts, Spotify or YouTube so you never miss an episode.

Chapter Markers

(00:00) - AI at the Roadside

(04:04) - How Nick and Harj Collaborate Across Technology and Operations

(07:45) - Managing Internal Resistance and the AAs Can-Do Culture

(11:32) - What Skills and Mindset the AA Looks for in People

(16:53) - What Good Technology Foundation Means for Frontline Teams

(21:36) - The Champions Network: A Bottom-Up Adoption Story

(25:16) - Future Opportunities and Risks: The Midnight Breakdown Scenario

(27:05) - Reimagining the Contact Centre: Haris Vision for the Next Decade

(29:56) - Advice for Executives Trying to Demonstrate AI ROI

(34:45) - Closing Reflections and What Makes the AAs' Transformation Distinctive

Useful Links

Follow Dr Raoul-Gabriel Urma on LinkedIn: https://uk.linkedin.com/in/raoulurma

Connect with Nick Edwards on LinkedIn: https://www.linkedin.com/in/nick-edwards-7a02b814/

Learn more from Harj Johal on LinkedIn: https://www.linkedin.com/in/harj-johal-42053328/

Visit the Cambridge Spark Website: https://cambridgespark.com/

👉 Discover how Cambridge Spark helps organisations build the data and AI capabilities needed to turn strategy into measurable impact: cambridgespark.com

Planning healthcare at scale is one of the most consequential challenges facing the NHS. In this inaugural episode of our new show, Inside The Algorithm, Cambridge Spark’s Chief AI Officer, Dr Jeremy Bradley, is joined by Dr Lucy Morgan, Head of Simulation at the NHS Strategy Unit, to explore how simulation modelling and AI are being used to tackle that challenge head-on.

Lucy led the development of a hybrid simulation model for renal replacement therapy, which began with the Midlands Kidney Network and is now being rolled out nationally. She breaks down how the model works, combining system dynamics with discrete event simulation to project future demand and model patient pathways through dialysis and transplant.

The conversation moves into the harder questions: how do you validate a model in a live healthcare environment, how do you rebuild trust with new organisations who weren't part of the original build, and where does AI fit into making models more portable and reproducible?

Lucy also shares her current research interest in using AI agents to help NHS staff query and interrogate analytical models directly, without needing deep modelling expertise themselves.

A rich, technically substantive episode for anyone working at the intersection of AI, simulation and real-world deployment.

Follow Data & AI Mastery so you never miss a future episode of Inside The Algorithm.

Liked this episode? Why not listen to the conversation Dr Raoul Gabriel Urma had with Ming Tang from the NHS on the Data & AI Mastery podcast: 

Apple: https://podcasts.apple.com/gb/podcast/transforming-healthcare-through-data-ai-human-centred/id1779783413?i=1000736381325

Spotify: https://open.spotify.com/episode/27wqHT0dnRMwKMedj2uoTw?si=5aabd4015dfa425d

YouTube: https://www.youtube.com/watch?v=JERGmZUumvA

Glossary Terms

Model reproducibility: the ability to obtain consistent computational results using the same input data, code, and environment

Neural Network: a method in artificial intelligence that teaches computers to process data in a way that is inspired by the human brain

Sequential Hybrid Simulation Model: a modeling approach that combines two or more distinct simulation paradigms (such as System Dynamics, Discrete-Event Simulation, or Agent-Based Simulation) by running them in a specific order, where the output of the first model acts as the input for the next

System Dynamics: a computer-aided modeling methodology used to understand, analyse, and manage complex, dynamic systems over time

Stock-flow System: a foundational system dynamics modelling concept mapping how quantities (stocks) accumulate over time, influenced by rates of change (flows)

Chapter Markers

(00:00) - Opening: The case for AI-assisted simulation in the NHS

(02:11) - About the NHS Strategy Unit and the backwards consultancy model

(05:04) - Tackling NHS waiting lists with queuing theory

(10:26) - Complexity of scheduling: theatre capacity, rotas and prioritisation

(13:42) - Introducing the renal replacement therapy planning model

(18:32) - Data sources, model calibration and validation

(23:00) - Rolling the model out nationally: trust, workshops and participative modelling

(26:47) - A call to the community: sharing best practices in model reproducibility

Useful Links

Connect with Dr Lucy Morgan on LinkedIn: https://www.linkedin.com/in/lucy-morgan-97072041/

For more AI insights follow Jeremy on LinkedIn: https://uk.linkedin.com/in/jeremy-bradley

Explore Cambridge Spark’s AI upskilling programmes at https://www.cambridgespark.com

👉 Discover how Cambridge Spark helps organisations build the data and AI capabilities needed to turn strategy into measurable impact: cambridgespark.com

On this week's episode of Data & AI Mastery, Dr Raoul-Gabriel Urma is joined by Sarah Self, AI Director at Aviva. Sarah brings a rare dual perspective to the conversation of data and AI, having spent nearly a decade in cybersecurity before moving into AI leadership. In this episode, she shares how those two disciplines share the same foundations: people, process and technology, and why that framework is central to delivering responsible, scalable AI.

Sarah discusses how Aviva built its own internal AI platform to embed guardrails from day one and why she views risk management and customer value not as a trade-off but as a single, unified objective. She also makes a compelling case for democratising AI across the workforce, using the term "organ rejection" to describe what happens when people are left behind in a transformation.

The episode closes with two standout production use cases: a claims summarisation solution that cut customer hold times by over 50% and a medical underwriting tool delivering 99% accuracy, both of which drive efficiency and customer satisfaction simultaneously.

Follow Data and AI Mastery on Apple Podcasts, Spotify or YouTube so you never miss an episode.

Chapter Markers

(00:00) - Opening Insight: Experimentation With Purpose

(02:44) - The Parallels Between Cybersecurity and AI

(05:46) - Balancing Risk and Customer Outcomes at Aviva

(10:29) - Democratising AI: Why Workforce Inclusion Matters

(14:28) - Identifying High-Value AI Use Cases

(17:27) - Balancing Experimentation With Production: The Portfolio Approach

(20:16) - Remaining Challenges and Keeping Perspective on the Hype

(23:48) - Quickfire Round: Sarah's AI Aha Moment

(25:21) - Raoul’s Reflections

Useful Links

Connect with Sarah Self on LinkedIn: https://www.linkedin.com/in/sarah-self-ba0b0642/

Follow Raoul for more AI insights on LinkedIn: https://www.linkedin.com/in/raoulurma/

Explore Cambridge Spark’s AI upskilling programmes at https://www.cambridgespark.com

👉 Discover how Cambridge Spark helps organisations build the data and AI capabilities needed to turn strategy into measurable impact: cambridgespark.com

Most AI commentary stops at the headline. This show starts where that ends.

Welcome to Inside the Algorithm, a brand new podcast from Cambridge Spark, hosted by Chief AI Officer Dr Jeremy Bradley.

Each episode, Jeremy sits down with leading researchers, data scientists and technical experts to get into the science, the breakthroughs and the ideas shaping the future of AI. No trend commentary. No surface-level takes. Just rigorous, substantive thinking made accessible to the people who need it most.

Inside the Algorithm publishes fortnightly in this feed, alternating with Data & AI Mastery, the show for AI strategy, leadership and business transformation.

If you want to go deeper into the science driving artificial intelligence forward, hit follow now.

Episode one drops 6th May.

Stay curious. Stay rigorous. Stay ahead of the algorithm.

Useful Links

For more AI insights follow Jeremy on LinkedIn: https://uk.linkedin.com/in/jeremy-bradley

Explore Cambridge Spark’s AI upskilling programmes at https://www.cambridgespark.com

👉 Discover how Cambridge Spark helps organisations build the data and AI capabilities needed to turn strategy into measurable impact: cambridgespark.com

On this week's episode of Data & AI Mastery, Mark Bramwell, Chief Digital and Information Officer at Oxford Said Business School, joins Dr Raoul-Gabriel Urma to share how one of the world's oldest universities is navigating one of its biggest challenges: deploying AI across a complex, multi-persona institution while simultaneously preparing students for an AI-driven workforce.

Mark unpacks Oxford's deliberate portfolio approach to AI tools, why they moved from per-user licensing to consumption-based models, and how they are measuring real business outcomes rather than treating AI as something categorically different from the rest of the tech stack.

From a faculty-led AI digital avatar teaching courses in any language, 24/7, to an AI assistant enhancing the MBA student experience, this conversation is grounded in genuine implementation rather than theory.

If you lead a complex organisation grappling with AI adoption, governance, and change management at scale, this episode is essential listening.

Follow Data and AI Mastery on Apple Podcasts, Spotify or YouTube so you never miss an episode.

Chapter Markers

(00:00) - Opening Insight: Treating AI Like Any Other Tool

(04:02) - Driving Innovation in a Centuries-Old Institution

(05:24) - Oxford's AI Strategy: The Portfolio Approach

(09:52) - Risks and Lessons Learned from the Consumption Model

(12:03) - Preparing Students for an AI-Driven Workforce

(17:44) - Governing AI Adoption at Scale

(22:58) - Change Adoption and Getting Everyone on the Journey

(25:51) - The Future of AI in Higher Education

(27:44) - Rapid-Fire Personal Questions

(30:06) - Raoul's Key Takeaways

Useful Links

Connect with Mark Bramwell on LinkedIn: https://www.linkedin.com/in/mark-bramwell-fbcs-308b4913/

Follow Raoul for more AI insights on LinkedIn: https://www.linkedin.com/in/raoulurma/

Explore Cambridge Spark’s AI upskilling programmes at https://www.cambridgespark.com

👉 Discover how Cambridge Spark helps organisations build the data and AI capabilities needed to turn strategy into measurable impact: cambridgespark.com

On this week's episode of Data & AI Mastery, Luke Pearce, Chief Data and AI Officer at Santander UK, joins Dr. Raoul-Gabriel Urma to discuss what it actually takes to drive meaningful AI adoption inside one of the UK's largest banks.

Luke shares how Santander UK moved beyond a governance-heavy data culture to build genuine C-suite and board-level sponsorship for AI. He challenges the conventional cost-saving narrative around AI ROI, making the case for customer and colleague delight as the more powerful North Star.

The conversation covers how Santander UK structured its AI rollout using a domain-based approach, why cross-functional teams are critical to success, and how to have productive governance conversations with a board that is both excited and cautious about AI.

Luke also offers a genuinely contrarian view on the future of the CDO role and what he would change about the industry if he could.

A practical and candid episode for any senior data or AI leader navigating organisational complexity.

Follow the podcast on Apple Podcasts, Spotify or YouTube so you never miss an episode.

Chapter Markers

(00:00) - Introduction and Luke Pearce's Career Journey

(04:51) - How Industry Experience Shapes Data Expectations

(07:24) - Organisational Structures That Support Data and AI

(10:19) - Redefining AI ROI Beyond Cost Reduction

(14:13) - Board and C-Suite Expectations: Navigating the Difference

(18:25) - Lessons for Organisations Just Starting Their AI Journey

(22:29) - Picking the Right Domains and Managing AI Momentum

(26:21) - Quickfire Round: Contrarian Views and Personal Insights

(30:13) - Episode Wrap-Up and Key Takeaways

Useful Links

Connect with Luke Pearce on LinkedIn: https://uk.linkedin.com/in/luke-pearce-23121522

Follow Raoul for more AI insights on LinkedIn: https://www.linkedin.com/in/raoulurma/

Explore Cambridge Spark’s AI upskilling programmes at https://www.cambridgespark.com

👉 Discover how Cambridge Spark helps organisations build the data and AI capabilities needed to turn strategy into measurable impact: cambridgespark.com

On this week's episode of Data & AI Mastery, Miryem Salah, Director of Digital, Data and Transformation at VodafoneThree, joins Raoul Gabriel-Urma to share the story behind one of the most ambitious AI strategies in UK telecoms.

Miryem breaks down how her team approached building a forward-looking AI strategy from first principles, why most organisations fall into the FOMO trap, and how VodafoneThree is thinking about the balance between humans and AI in a post-merger business.

She also shares her thinking on governed agility, the importance of data literacy at every level of leadership, and why getting foundations right matters more than chasing the next shiny tool.

The conversation also touches on diversity in data and tech, Miryem's Women in Data network spanning 100,000 employees across VodafoneThree; and her genuine excitement about the rise of physical AI.

A frank, experience-led conversation for senior data and AI leaders navigating large-scale transformation.

Be sure to follow Data & AI Mastery wherever you listen to your podcasts to never miss an episode. 

Chapter Markers

(00:00) - Introduction and Miryem's role at VodafoneThree

(02:00) - Inside the Vodafone and Three UK merger 

(06:00) - Misconceptions about data teams and data ownership 

(10:00) - Operating model, human versus AI, and the sell-build-run framework 

(15:00) - Measuring success in early-stage AI deployment 

(19:00) - Risk management and when to put AI in front of customers 

(24:00) - Quickfire round: diversity, STEM, music and the magic wand question 

(27:00) - Raoul on AI and the future of education 

(28:30) - Key takeaways

Useful Links

Connect with Miryem Salah on LinkedIn: https://uk.linkedin.com/in/miryem-salah-7a3ba633 

Follow Raoul for more AI insights on LinkedIn: https://www.linkedin.com/in/raoulurma/

Explore Cambridge Spark’s AI upskilling programmes at https://www.cambridgespark.com

👉 Discover how Cambridge Spark helps organisations build the data and AI capabilities needed to turn strategy into measurable impact: cambridgespark.com

In this episode of Data & AI Mastery, host Dr. Raoul-Gabriel Urma sits down with Indhira Mani, Chief Data Officer at Intact Insurance UK, to explore what it really takes to transform a legacy organisation into a data-driven, AI-enabled business.

Indhira shares her journey from embracing intellectual challenges to leading a full-scale data transformation, not by starting with technology, but by starting with people.

Together, they unpack how to move data from a back-office function to a strategic lever, how to build cross-functional squads, and why winning hearts and minds is the hardest and most rewarding part of transformation.

Listeners will learn why data transformation must begin with culture, trust, and relationships; why giving more data doesn’t always lead to better decisions; and how AI should augment human intelligence, not replace it.

This episode is essential listening for CDOs, CIOs, transformation leaders, and executives navigating cultural change in complex, regulated industries.

Be sure to follow Data & AI Mastery wherever you listen to your podcasts to never miss an episode. 

Chapter Markers

(02:00) — Indhira’s journey to Chief Data Officer

(05:00) — Moving data from back-office to strategic lever

(10:00) — The rewards of transformation

(16:30) — Making data usable, not perfect

(19:00) — Decision paralysis and too much data

(23:00) — Raoul’s reflections 

Useful Links

Connect with Indhira on LinkedIn

Follow Raoul for more AI insights on LinkedIn

Explore Cambridge Spark’s AI upskilling programmes at cambridgespark.com