Big Data & AI World World Day 2 Highlights

Racing Into Intelligence: The Future of AI in Motorsport

Ben Buckley, Head of the Technology and Innovation Group - Atlassian Williams F1 Team
Ifeoluwa Ogunbufunmi, Founder & Chief Strategist - SWIF

Motorsport has always pushed the limits of innovation - and AI is set to drive one of its next great leaps. This session explored how data, automation, and intelligent systems will shape the sport over the next three to five years. Discover Atlassian Williams Racing's bold vision for the future of AI in high-performance, data-driven environments.

How to Make AI Stick: Scaling from Curiosity to Capability at Travelopia

Chris Storey, Technology Director - travelopia

AI adoption doesn’t fail because of technology, it fails because of difficulty around scaling. In this session, Chris shares how Travelopia moved from early AI experimentation to embedding tools like Copilot and ChatGPT into everyday work. The presentation explored the challenges of scaling AI responsibly, the shift from generic tools to more role-specific applications, and how widespread adoption is changing the way teams work, decide and deliver value.

How Can the Tech Sector Build Earlier, More Inclusive Talent Beyond Graduate Hiring?

Christine Kinnear, Founder & CEO - With Insight Education

Drawing on work with schools, universities, and corporate partners, this session explores how early intervention can widen participation and strengthen future talent pipelines. It shared insights from young people on what they need to enter and sustain careers, alongside practical, proven models for employer engagement, mentoring, and skills exposure.

Grounded in direct delivery, student voice, and data-led insight, the session is designed for employers and policymakers seeking actionable approaches to diversity, skills development, and future workforce planning.

Making AI Work: Best Route for ROI and Real-World Use Cases Transforming Financial Service Operations

Hamid Raza, Head of Data & BI - Just

The session focused on the AI use cases that generate the quickest ROI with the least operational risk, based on real solutions already delivered in live financial services environments. Drawing on proven implementations across insurance operations including claims, underwriting, fraud, and service. It covered how organisations move beyond pilots to measurable impact. Attendees learned which use cases scale, why others stall, and how to sequence AI adoption to build confidence, trust, and value without disrupting core workflows. A practical, experience-led guide to making AI pay back sooner rather than later.

The Magic Ingredient for High Performing AI Teams

Michail Vamvakaris, Head of Data Science and MLOps - William Hill

This session explores how you can transform the role of data science inside the enterprise. From embedding data scientists closer to product teams, to creating governance structures that align with the AI Act and enterprise-wide risk frameworks, the talk will expose how structural change is just as critical as technical innovation. Attendees learned why successful enterprises are treating data science not as a standalone unit, but as a distributed capability with clear metrics, stronger business alignment, and operating models designed for speed and accountability.

What Does ‘Human-Centred’ Mean Globally? Culture, and AI Beyond the West

Mario Chatzidamianos, EU Cultural Ambassador and R&D Strategic Partner - Cultural Infusion
Anna Zelno, Founder - Academy for Diversity & Innovation
Anais Aguerre, Founder & Director - Culture Connect Ltd
Waqas Ahmed, Founder - The DaVinci Network

Drawing on decades of work across intercultural understanding, cultural analytics, and ethical technology, Peter Mousaferiadis explored what it means to design AI systems that fully reflect the world’s cultural diversity rather than a small subset of it. From data bias and algorithmic homogenisation to cultural knowledge gaps and assumptions embedded in global AI governance, Peter unpacks how culture fundamentally shapes the way technology is built, interpreted, and deployed.

Building a Modern Real-Time Data Platform at Fresha

Anton Borisov, Principal Data Architect - Fresha

We’ll cover what actually worked, what didn’t, and how we unified CDC streams, historical lakehouse data and sub-second dashboards behind a single SQL layer. Attendees received a pragmatic blueprint for modernising analytics at scale, plus the operational lessons they learned running it in production.

Turning Enterprise Data into Products with an AI-Powered Data Catalogue

Stephen Nwoye, PhD, Senior Data Engineer - NHS England

As enterprise data estates grow, the challenge for data engineers is shifting from moving data to productising it. This session explored how an AI-powered, centralised data cataloguing framework designed to help large organisations turn data into discoverable, trusted data products.
Focusing on a data engineering perspective, the session covered the theoretical foundations of the framework alongside real-world implementation lessons from deployments across multiple NHS trusts.