Big Data LDN is the UK’s biggest gathering of data, analytics, and AI minds at Olympia London. This year, the message across the floor was loud and clear: the era of AI experimentation is over. The industry’s focus now is on building the solid data foundations needed to actually deliver value.

At CI&T, we believe that great AI is only ever as good as the data underneath it. That’s why we took to the stage alongside two of our partners - data leaders from Experian and ASOS.com. Together, we delved into how cultural shifts, AI-assisted discovery, and smart execution can turn complex legacy systems into modern growth engines. 
Below are our key takeaways, along with full videos of each session. 

Day 1: Building a Data-Driven Organisation, Not Just a Data Platform (Experian)

On the first day of the conference, CI&T’s Lauren Bowen (Senior Delivery Director) sat down with Neil O'Connor (CTO of Experian Consumer Services UK&I) to unpack how Experian turned a standard platform upgrade into a company-wide shift toward becoming genuinely data-driven.

Key tekaways

Unlocking Insights for 16 Million UK Consumers: Experian Consumer Services touches the financial lives of nearly 16 million people in the UK. The goal wasn't just collecting more data, but using it to power hyper-personalised journeys, like helping people navigate buying their first home or recommending 'smart money moves' that actually improve their financial health.

An Embedded Co-Delivery Model: Technology upgrades fall flat without adoption. Instead of acting as a distant consultancy, CI&T embedded directly alongside Experian’s internal domain teams from day one. This co-delivery setup brought in specialised data engineering expertise and delivery rigour while building long-term capability in-house.

Sparking 'Penny Drop' Moments: Rather than forcing change from the top down, the team focused on showing, not telling. Live demos showing how self-service tools could answer everyday questions in plain English created instant "penny drop" moments across marketing, finance, and product teams. Turning initial resistance into active enthusiasm.

Treating Data as a Product: By decentralising data ownership across product domains, data is no longer seen as something "owned by IT."  Today, building on the platform has quickly become second nature for any new feature launch at Experian.

Clean Data Makes Safe AI: AI capabilities are only as good as the data feeding them. By creating a reliable, well-governed context layer, Experian established the exact bedrock needed for future AI tools to make safe, contextual and accurate recommendations for UK consumers.

"For us, data is the foundation for good AI experiences. An autonomous agent cannot deal with information without the right context—building that context layer sets us up to deliver personalised journeys that genuinely improve financial outcomes for our users."

— Neil O'Connor, CTO of Experian Consumer Services UK&I

Day 2: Shattering the Data Deadlock: 12-Month Migration in 20 Weeks (ASOS)

On day two, CI&T’s Head of Data & AI, Abhay Bagai hosted a fireside chat with Filippo Chiari (VP of Data & AI, ASOS) and Mike Lombardi (Head of Data Products, ASOS) to reveal how ASOS tackled a massive legacy estate and wrapped up a year-long migration in just 20 weeks.

Key Takeaways:

Flipping the Script on Migration Costs: ASOS faced a hard platform support deadline, over 700 legacy code repositories, and 27,000 legacy reports. Traditional multi-year, multi-million-pound migration models no longer made commercial sense. Leveraging AI changed the math entirely by automating hours of tedious discovery, code analysis, and lineage mapping.

AI-First Discovery in Practice: Using CI&T's AI-driven knowledge graph tools, ASOS mapped out its entire legacy environment in weeks. That cut what usually takes two to three months of manual digging down to just 4–5 weeks.

Focusing on Parity, Not Rebuilding Debt: Instead of wasting time and resources rebuilding 27,000 reports (many of which were obsolete), ASOS worked closely with business stakeholders to focus on functional parity. They identified the core value streams needed for business decisions, stripping away technical debt and streamlining what actually mattered.

Speed Means Nothing Without Trust: Accelerating delivery is great, but only if the data remains rock-solid. ASOS built automated testing, documentation, and business context directly into the delivery pipeline so that governance happened automatically along the way.

Moving quickly only adds value if the underlying data remains trustworthy. ASOS embedded automated testing, metadata management, and business context directly into pipeline delivery,  so that governance happened automatically along the way.

Filippo’s Top Rules for Data Leaders:

Fix your data before throwing agents at it: AI agents perform only as well as the underlying data foundations allow.

Reframe the business case: Pitch your data modernisation as an enterprise AI readiness programme, rather than a back-office IT migration.

Build joint ownership: Align engineering timelines directly with business outcomes and establish clear 'kill-switch' criteria for legacy systems.

Never compromise on trust: Moving fast without data governance will quickly damage user confidence.

"The question is no longer 'Can we afford to do it?' The question is 'Can we afford NOT to do it?' AI has completely redefined the economics of data modernisation."

— Filippo Chiari, VP of Data & AI, ASOS

Back at our stand

Over at our booth, our team spent both days having brilliant chats about all things Data and AI, watching some healthy competition in our interactive game as people competed for the chance to win an Oura ring, and handing out plenty of Tony's Chocolonely chocolates.

Looking Ahead

Big Data LDN 2026 proved that real progress happens when you connect tech upgrades directly to business culture and user outcomes. Whether through embedding data ownership across teams at Experian or using AI to slash migration timelines at ASOS, the secret is building trusted, modern data foundations that make fast, smart decisions possible.

A huge thank you to Neil O'Connor, Filippo Chiari, Mike Lombardi, Lauren Bowen, and Abhay Bagai for sharing their stories, and to everyone who stopped by the CI&T stand!

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