TLC Connect - Data & AI Series

4th December 2025

Bankside Hotel, London

4th December 2025

Data & AI Summit

The TLC Connect Global Data & AI Summit offers a high value, actionable conference programme designed to foster collaboration between senior data and AI leaders and offer the tools needed to successfully navigate a demanding data and AI environment. 

Days
Hours
Minutes
Seconds
Key Themes for 2025

Data in an AI World: From Buzzword to Business Value

AI Maturity & Enterprise Adoption

From pilot use cases to fully automated enterprise value.

Data Quality, Governance & Regulation

Ensuring accuracy, clarity, compliance, and trust in data ecosystems.

Modern Data Engineering & Architecture

Building flexible, scalable foundations for AI and analytics.

Responsible, Secure & Ethical AI

Transparency, fairness, safety, and risk mitigation at scale.

Our Speakers

Speaker Name

Aaron Kalvani

Global AI Leader - AI Strategist & Advisor

United Nations

Speaker Name

Andreas Galatoulas

Data, Analytics & AI Director

AECOM

Speaker Name

Andrew Dudfield

Head of Artificial Intelligence

Full Fact

Speaker Name

Denholm Hesse

Chief Data Officer

BDO

Speaker Name

Fernando Zabotinsky

Global Technology Director

Ball Corporation

Speaker Name

Leanne Pienaar

Director of Data

Indurent

Speaker Name

Mark Beckwith

Director of Data Governance and Architecture

Financial Times

Speaker Name

Petr Vaclav

VP and Head of Data, Analytics & AI

RGA

Speaker Name

Reza Salari

Chief Information Security Officer

Pacific Life Re

Speaker Name

Sanja Hukovic

Group Director Head of Model and AI risk management

LSEG

Speaker Name

Paul Henry

VP of Data & AI

Citi

Speaker Name

Peter Dorrington

Founder

XMplify Consulting Ltd

Elevate Your Security Dialogue

Summit Agenda Overview

Welcome to the TLC Connect Data & AI Summit 2025. Explore sessions focused on AI governance, modern data architecture, analytics acceleration, and building responsible, resilient enterprise intelligence.

08:30am - Registration

Arrival, registration and networking breakfast

09:30 - Chair's Welcome

Welcome and Agenda Overview

Peter Dorrington – Founder – XMplify Consulting Ltd

09:35 - Partner Keynote - From Silos to Spearheads—Operationalizing the Data Mesh at Enterprise Scale

This session dives into the practical steps for CDOs to shift from monolithic lakes to domain-oriented data products.

Peter Dorrington – Founder – XMplify Consulting Ltd

10:05 - Opening Panel: Guardians of Trust: How CDOs, CISOs and CIOs Shape the Future of AI

10:45 - Fireside Chat: Data Unleashed: How a Truly Data-driven Culture Can Transform Organisations

11:25 - Networking Break & Refreshments

11:45 - Panel Discussion: AI ROI: Measuring Real AI Outcomes, Not the Hype

12:25 - Customer Case Study Workshop

12:45 - Customer Case Study Workshop

13:05 - Lunch, Networking & Vendor Exploration

14:00 - Panel Discussion: Ownership, Stewarship & Quality: Shifting Data Governance From Cost to Value Creation

14:40 - Customer Case Study Workshop

15:00 - Roundtable Discussions

Roundtable Discussion 1: Data Quality in the Age of Generative AI

With AI models only as strong as the data they consume, leaders must rethink data stewardship. This discussion examines strategies for ensuring accuracy, lineage and trustworthiness in increasingly complex data ecosystems.

Moderation Questions:

  1. How do you balance speed of innovation with the rigour of data quality controls?
  2. What frameworks or tools have you found most effective for ensuring data lineage and trustworthiness?
  3. How should organisations handle “good enough” data in contexts where perfection is unrealistic?

Roundtable Discussion 2: From Data Strategy to AI Value Creation

Many organisations have robust data strategies, but translating them into measurable AI-driven business outcomes remains a challenge. This session explores how Data & AI leaders can align strong data foundations with AI initiatives that deliver tangible enterprise value.

Moderation Questions:

  1. How do you ensure your data strategy is directly linked to business outcomes rather than technology adoption for its own sake?
  2. What governance models best support scaling AI initiatives across multiple business units?
  3. How do you measure and communicate the value of AI to the board and executive stakeholders?

Roundtable Discussion 3: Responsible AI – Embedding Ethics into Enterprise DNA

Beyond compliance, responsible AI is about embedding fairness, accountability and transparency into every stage of the data lifecycle. This roundtable examines how Data & AI leaders can lead the charge in operationalising ethics.

Moderation Questions:

  1. How do you translate abstract principles of responsible AI into concrete policies and practices?
  2. What governance mechanisms ensure accountability when AI decisions impact customers or citizens?
  3. How do you balance ethical considerations with competitive pressures to innovate quickly?

15:30 - Networking Break & Refreshments

15:50 - Fireside Chat: Bridging the Data & AI Talent Gap: Strategies for CDOs to Overcome the Skills Shortage

16:30 - Closing Keynote: From Insight to Impact: Orchestrating Data, AI & Ethics for Sustainable Growth

16:55 - Closing Remarks and Key Takeaways

Our Sponsors

Who Should Attend?

Designed for Leaders Turning Data, Analytics & AI Into Enterprise Value

CDOs & Data Leaders

Chief Data Officers, Directors and Heads of Data focused on establishing enterprise-wide data strategy, improving data maturity, and delivering measurable business outcomes..

Analytics & Insight Leaders

Leaders in Analytics, BI and Insights looking to scale data-driven decision making, improve data literacy, and unlock deeper, more actionable intelligence across the organisation.

AI, ML & Innovation Leaderss

Senior professionals driving AI, machine learning and automation programmes who want to accelerate value delivery while managing risk, governance and ethical responsibility.n.

Data Platform & Engineering Leaders

Directors and Heads of Data Engineering, Architecture and Platforms responsible for building modern, scalable, cloud-native data ecosystems that enable advanced analytics and AI.

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