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

This week, Dr Judit Guimera Busquets, Head of Data Science at Datasparq, joins Dr Jeremy Bradley to trace the journey from her PhD on air traffic network forecasting through to leading data science teams delivering real-world AI projects.

Judit explains why forecasting inside a complex network is fundamentally different from standard demand prediction: when a single airport pair is removed, the cascade effect ripples across an entire system. She walks through the multi-stage modelling framework she developed, covering city pair demand generation, network evolution, itinerary assignment, and long-term scenario planning.

The conversation then turns to what actually happens when structural shocks like a pandemic break a model's core assumptions and why human-in-the-loop design is not optional. Judit also sets out what she looks for in data scientists: pragmatism over perfection, simplicity over complexity, and a production-first mindset from day one.

She closes with her view on where applied AI is heading, including the rise of small, fine-tuned specialist models and why AI governance remains the most overlooked challenge in the field.

Follow Data & AI Mastery on Apple Podcasts, Spotify, or YouTube to stay ahead of the algorithm.

If you enjoyed this episode, why not check out the Data & AI Mastery episode with Richard Masters, VP of Data and AI at Virgin Atlantic. You will learn more about how the airline leverages AI and data-driven strategies to enhance operations, optimise pricing, and deliver premium customer experiences:

Apple: https://podcasts.apple.com/gb/podcast/mastering-data-ai-insights-from-virgin-atlantics-vp/id1779783413?i=1000697801419

Spotify: https://open.spotify.com/episode/1MY3AZCvDr5eS1HlfBudHy?si=ca5ec9b2fe6d44b1

YouTube: https://www.youtube.com/watch?v=DQ3mTwTzJvA

Glossary Terms

Hub-and-spoke Model: a centralised organisational architecture where a central core connects to multiple peripheral nodes. Traffic, communication, or inventory flows through the hub rather than directly between spokes.

Network Theory: a multidisciplinary framework used to analyse complex systems by representing them as mathematical graphs

Econometrics: the application of statistical and mathematical models to economic data

Human-in-the-Loop: a collaborative AI approach where humans actively participate in an automated system's training, refinement, or operation.

Linear Regression Model: a fundamental statistical and machine learning algorithm that models the relationship between a dependent variable and one or more independent variables by fitting a straight line to the data.

Chapter Markers

(00:00) - What makes network forecasting different from standard demand prediction

(05:54) - How historical data fails when the network itself evolves

(10:05) - Modelling link addition and removal as classification problems

(13:26) - Designing for medium and long-term policy evaluation, not daily operations

(17:57) - What happens to a model when a structural shock like a pandemic hits

(22:22) - Human-in-the-loop: adjusting elasticities and running what-if scenarios

(27:20) - What great data scientists actually look like in a consulting environment

(30:03) - Getting stakeholders to use AI: champions, end users and change readiness

(32:00) - Where applied AI is heading: small specialist models and the governance gap

Useful Links

Connect with Dr Judit Guimera Busquets on LinkedIn: https://uk.linkedin.com/in/judit-guimera-busquets-696ab74a

Learn more about Judit’s PHD here: https://openaccess.city.ac.uk/id/eprint/24689/1/Busquets%2C%20Guimera.pdf

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

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

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

In this episode, Richard Moule, Chief Data and AI Officer at Haleon, joins Dr Raoul-Gabriel Urma to discuss one of the most pressing challenges facing large organisations today: how do you build genuine AI literacy across an entire workforce, starting at the very top?

Richard shares how Haleon partnered with Cambridge Spark to deliver an in-depth AI education programme to its executive team, why the CEO set a clear ambition to lead the best-educated leadership team in the FTSE 100 on AI, and how that investment is reshaping the quality of business conversations across the organisation.

The conversation covers the difference between agentic AI and generative AI, why Richard pushes back on teams that ask for specific technologies before defining their business need, and how Haleon is balancing foundational data infrastructure with the pressure to show early value.

Richard also shares his approach to AI governance, the limits of automation when human negotiation sits at the heart of a process, and what he looks for in talent in an era of AI augmentation.

A sharp, practical episode for senior data and AI leaders navigating enterprise-scale transformation.

Follow Data and AI Mastery to stay ahead of the conversations shaping the future of data and AI.

If this episode sparked your interest in how AI is being applied inside Haleon, then check out the conversation Dr Jeremy Bradley had with Dr Gueorgui Mihaylov, Principal Data Scientist at Haleon, on Inside the Algorithm:

Apple: https://podcasts.apple.com/gb/podcast/daim-inside-the-algorithm-ai-in-industrial/id1779783413?i=1000768691684

Spotify: https://open.spotify.com/episode/3zJJxysXLBJcMi336RNmDZ?si=cca6acb90b7b4e0b

YouTube: https://www.youtube.com/watch?v=Hz1OtBYMf0U

Chapter Markers

(00:00) - Introduction and welcome

(04:30) - Agentic AI, generative AI and why they are part of the same continuum

(08:27) - Building an enterprise-wide AI education programme with Cambridge Spark

(11:17) - AI strategy, tech infrastructure and the foundational work most businesses underestimate

(16:12) - Balancing governance with speed: raising the floor and raising the ceiling

(20:32) - Process mapping, automation ROI and where agentic AI delivers real value

(22:09) - Where AI is not yet ready: processes built on human negotiation

(24:50) - Quickfire round: hiring for augmentation, staying current, career advice and personal interests

(29:17) - Closing reflections

Useful Links

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

Connect with Richard Moule on LinkedIn: https://www.linkedin.com/in/richard-moule/

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 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

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/