Main Day 2 - Thursday 22nd January

By structuring a strategy into foundational, consolidated, and finished layers, businesses can unlock data product capabilities the organisation has never had before, quickly, and compliantly. This use-case based presentation by Adrian Pinder, Head of Digital and Data at DS Smith, will outline his team’s thought process when integrating Gen AI into their internal procurement data product. Their implementation strategy relied on:

• Strategically determining where to incorporate Gen AI into their data product and assessing the value it would bring.
• Putting in place a strong governance framework from the get-go.
• Making sure their tools and structure were agile enough to manoeuvre through challenges that arose.

Adrian Pinder

Co-Founder and former Head of Digital and Data
Former DS Smith PLC

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As AI becomes embedded in business decisions, many organisations struggle to explain, govern, and stand behind the outcomes. The issue is rarely the model itself, but fragmented data, unclear ownership, and hidden quality risks.

In this session, Jean-Georges “jgp” Perrin outlines practical frameworks for turning fragmented data into governed data products that give organisations a lasting advantage as AI scales. Using open standards such as ODCS and ODPS, data products define ownership, quality, and usage boundaries early — making AI governable, auditable, and defensible without slowing innovation or forcing centralised rebuilds. You’ll learn:

• How data products make AI more accurate, explainable, and reusable.
• Why AI risk is now a data governance problem, not a model problem.
• How data products create clear accountability and auditability for AI decisions.
• What boards should demand now to ensure AI remains a strategic asset, not a liability.

You don’t govern AI. You govern the data products behind it.

Jean-Georges Perrin

Distinguished Data & AI Strategist
Actian

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AI and Machine Learning have become the go-to buzzwords in boardrooms, but not every data product needs a neural network to deliver value. This panel will explore examples of enterprise leaders separating genuine opportunity from costly overengineering, helping teams identify where AI/ML truly enhances functionality and adds value. Dive deeper into:

• Evaluating the functional and financial impact of AI/ML before implementation.
• Aligning executive enthusiasm with realistic, cost-effective AI strategies.
• Identifying high-impact use cases where AI/ML drives measurable product value.

Stefania Bonà

Senior Director, Open Banking Payment Products
VISA

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Mike Shebalkov

Product Director
Wise

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Anshul Garg

Senior Data Product Owner
A.P. Moller - Maersk

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Jonathan Sunderland

Data Strategy Advisor
Ab Initio

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Nick Zervoudis

Data Product Management Consultant & Founder
Value from Data & AI

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The core argument and the narrative is built around a central paradox: AI Agents are operational systems, but they automate reasoning. Therefore, they cannot be managed solely by software engineering rules; they require analytics principles. During this session, Andriy will argue that as the ROI of AI Agents depends more on Data Governance principles (like quality and lineage) than model performance, this creates a new mandate for the data ecosystem. Walk away with a deeper look into:

• Data Products as "Grounding": Moving beyond assets to become the source of Context (ensuring the AI behaves as intended).
• Data Platform as "Evaluation": Moving beyond infrastructure to become the source of Verification (ensuring the AI behaves as expected).
• A set of "Axioms" for the Agentic Age, not dogmatic answers, which will provide a framework to help navigate uncertainty.
• Seeing your Data Platforms, not just as a storage layer, but as the "Lighthouse" that keeps the business safe in a sea of incertitude and rapid change.

Andriy Mandyev

Head of Data Factory
Decathlon Digital

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In this insightful case study, Ana Sotelo, Technical Data Product Director at PepsiCo, shares how the company is transforming its legacy data estate by prioritising quality and governance while migrating to the cloud. Over the past three years, PepsiCo has experienced great ROI, by:

• Establishing a data product framework that supports scalable migration and measurable business value.
• Putting in the initial grunt work that ensures data is compliant and quality from the get-go.
• Building cross-functional teams to quantify ROI and align data efforts with strategic goals.

Ana Sotelo

Technical Data Product Director
PepsiCo

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Explore the grey battlefield of the AI wars, where governments, hyperscalers, regulators, and enterprises collide. Moving beyond today’s generative AI narrative, Antony examines agentic systems, autonomous decision-making, and the strategic implications of operating in a world of AI arms races, digital protectionism, and trust erosion. Expect a bold, grounded perspective on how leaders can build AI-ready platforms, governance, and operating models resilient enough to thrive amid uncertainty, before the next wave breaks.

Antony Elliott

Vice President
Strategy

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As platform engineering evolves, the focus is shifting from simply reducing technical overhead to delivering strategic, measurable value across the organisation. This session will highlight a compelling case study on how adopting a Product Operating Model can reposition internal platforms from a cost centre to a business-enabling product. Learn more about how companies are:

• Defining platform users and roadmaps to guide product evolution.
• Segmenting internal audiences to tailor engagement and adoption.
• Building feedback loops to continuously improve developer experience and value.

Adopting a data mesh model isn’t just a technical shift—it’s a cultural one. This session explores how enterprises can tailor mesh principles to their unique platform architecture by aligning business goals, fostering cross-functional collaboration, and building platform teams that ask the right questions. Learn how to balance:

• Integrating business context into platform decisions to ensure mesh models and chosen platforms deliver value.
• Including non-technical voices in platform teams to improve communication and outcomes.
• Asking the right questions to translate cross-team requests into meaningful data solutions.

Amy Bulman

Internal Data Consultant
WEPA

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Despite its growing importance, the term “data product” still lacks a universal definition across industries which creates confusion, misalignment, and missed opportunities. This session explores how enterprises can clarify the relationship between data products and business outcomes, and why internal roles like platform architects, product managers, and data engineers are essential to building and sustaining them. Gain a more in-depth understanding of:

• Establishing the definition of ‘data product’, cross-industry.
• Building cross-functional roles and teams that support the full lifecycle of data.
• Connecting data products to business strategy to maximise impact, value, and relevance.

Nick Zervoudis

Data Product Management Consultant & Founder
Value from Data & AI

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Joanna Dabrowska

Independent Consultant
Independent Consultant

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Russell Measor

Head of Data Products AI & Innovation
Axis CLC

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Enjoy a relaxed afternoon tea as you connect with fellow delegates and speakers to reflect on the past two day’s discussions. This 45 minute closing session offers a final chance on site to exchange perspectives, revisit key insights, and continue conversations sparked throughout the Summit.