Agenda

Despite growing investment in AI, many organisations remain constrained by unresolved data challenges. This session explores the critical disconnect between AI ambition and the underlying issues of data quality, ownership, and governance. It examines why scalable AI depends on strong data foundations and what’s required to shift focus from experimentation to enterprise-wide value creation.

• How are CDAOs tackling fragmented data ownership across siloed functions?

• What practical steps are being taken to improve data quality at speed and scale?

• Where do data governance models need to evolve to enable responsible AI use?

• How are leaders prioritising foundational data investments against short-term AI pressure?

10:10am - 10:40am

As AI scales across enterprise, success depends on strong data foundations. This session explores how CDAOs are tackling long-standing challenges around governance, quality, and architecture to build AI-ready infrastructure.

From metadata and lineage to stewardship and control, discover what it really takes to deliver trusted, scalable data systems that unlock AI’s full potential.

• What an AI-ready data estate looks like in practice — and how to get there

• Building trust at scale with metadata, lineage, and robust governance

• Overcoming legacy complexity to enable faster, safer AI deployment

10:40am - 11:10am

As AI capabilities expand, so do the risks associated with data misuse, bias, and non-compliance. This session examines how effective data governance can support responsible AI development, ensure regulatory alignment, and maintain innovation in complex, high-stakes environments.

• How are organisations embedding governance into fast-moving AI product lifecycles without slowing delivery?

• What new controls are needed to manage bias, explainability, and model drift in AI systems?

• How are CDAOs preparing for emerging UK and EU AI regulations while maintaining global consistency?

• What does “minimum viable governance” look like for scaling AI safely across the enterprise?

11:10am - 11:20am

As AI adoption accelerates, keeping pace with evolving regulatory demands is one of the biggest barriers to scale. This session explores how CDAOs are approaching the challenge of embedding trust into systems and processes, ensuring governance, managing risk, and maintaining compliance in fast-moving environments without stifling innovation.

• Navigating shifting UK, EU, and global AI regulatory landscapes

• Automating oversight: scalable approaches to risk and compliance

• Building governance frameworks that keep up with model velocity

Data transformation relies as much on people as it does on technology. This session explores how to embed a data-driven mindset across organisations, improve data literacy, and create the cultural conditions necessary to translate insight into sustained business impact.

• How are CDAOs turning data strategy into behavioural change across business functions?

• What practical steps are helping to close the data literacy gap at scale?

• How do leaders build trust in data insights when legacy scepticism persists?

• What are the most effective approaches to attracting, retaining, and empowering data talent?

11 am - 12 pm

How do you build trust in data systems and AI outputs—internally and externally—while aligning with emerging AI regulation, auditability demands, and responsible deployment frameworks?

11 am - 12 pm

How are CDAOs modernising fragmented data estates to unlock AI value—from ownership and stewardship to platforms, pipelines, and architecture?

12:00 - 13:00pm

What does it take to build enterprise-grade Retrieval-Augmented Generation (RAG) systems? What are the key challenges in orchestrating data pipelines, vector databases, model selection, latency, and real-time feedback loops?

How are CDAOs equipping teams with the tools, training, and behavioural frameworks to activate AI across the business—and what are the most effective partner solutions in driving adoption at scale?

What separates AI proof-of-concepts from scaled deployment—and how are CDAOs working with partners to accelerate value delivery from architecture to ROI?

David McCandless, Founder, Information is Beautiful In a world drowning in dashboards, how can data leaders cut through the noise and make insight land with impact? Too often, complex analysis gets lost in translation—overwhelming stakeholders or failing to drive action. This energising session explores how visual storytelling can transform the way data is communicated, helping CDAOs elevate their strategic voice across the organisation. Led by David McCandless, best-selling author and one of the world’s most renowned data designers, this session will show how clarity, design, and narrative can turn insight into influence at the highest levels.

• How can visual principles help simplify complex data for senior audiences?

• What storytelling techniques help insight resonate beyond the analytics team?

• How can data leaders create executive-ready narratives that inspire decisions and shape strategy?

14:00pm - 14:30pm

For all the promise of AI, many organisations remain stuck in pilot mode. Today CDAOs face growing pressure to prove real business impact, yet scaling from proof-of-concept to production is one of the biggest hurdles. This session explores what it takes to embed AI into core operations and deliver value at scale.

• Which AI use cases have delivered measurable and sustained ROI?

• Where have initiatives failed, and what early warning signs can others learn from?

• How are teams managing the transition from experimentation to operational deployment?

• What technical and organisational enablers are proving essential to scaling success?

14:30pm - 14:40pm

As enterprise interest in Generative AI accelerates, Retrieval-Augmented Generation (RAG) has emerged as a key architecture for grounding models in trusted data. But deploying RAG at scale is complex, and many early efforts stall at the prototype stage. This session explores what it really takes to make RAG work in production—from data orchestration to infrastructure and feedback loops.

• What are the common failure points in RAG deployment, and how can they be avoided?

• Which tools and system architectures enable scalable, reliable GenAI?

• What lessons are emerging from real-world implementations across sectors?

14:40pm - 15:10pm

Demonstrating the impact of data investments remains a critical challenge for data leaders. This discussion goes beyond theory to unpack the exact steps senior data leaders are using to prove value. Exploring how they quantify impact, win budget, engage the right stakeholders, and demonstrate ROI that secures future investment.

• Who needs to be brought in early? And how do you align their priorities to strengthen the case?

• What does a convincing, investment-worthy business case actually look like?

• Which commercial metrics and proof points get traction with CFOs, COOs and Boards?

• How are successful CDAOs communicating both the tangible and intangible benefits of data platforms, analytics tooling, or AI infrastructure?

• How do you demonstrate post-investment ROI in ways that open the door to future funding?

15:10pm - 15:20pm

Many data leaders have built robust platforms and pipelines, yet struggle to bridge the final gap: turning insights into everyday action. Empowering decision-makers outside the data team remains a critical challenge for unlocking full business value. This session explores how embedded analytics, AI copilots, and intuitive interfaces are helping close that gap.

• How can organisations integrate insight directly into day-to-day workflows?

• What are the most effective use cases for user-centric, embedded analytics?

• How can smart design improve data literacy and enablement across functions?

15:20pm - 15:50pm

There is no one-size-fits-all data operating model. While centralised control offers consistency and oversight, decentralised approaches can drive agility and domain-specific innovation. Many organisations are now exploring federated models to balance these competing demands—but finding the right fit remains a complex and context-dependent challenge.

• This session explores how CDAOs are navigating that tension, evolving their operating models to enable scalable, trusted, and business-aligned data delivery.

• Designing the “just right” level of centralisation vs autonomy for your organisation

• Building data product ownership and accountability in business units

• Developing governance frameworks that support, not restrict, federated innovation

15:50pm - 16:30pm

As AI reshapes business priorities, the future of the CDAO role is uncertain. This session explores how data leadership is evolving, whether the role will become central to enterprise growth, and what structural or strategic shifts may redefine its place in organisations by 2030.

• Will the CDAO become a board-level growth enabler or be absorbed into broader digital or AI functions?

• How are forward-looking organisations redefining the boundaries between data, AI, and technology leadership?

• What new skills, capabilities, or remits will tomorrow’s data leaders need to stay relevant?

• How can CDAOs ensure they’re not just custodians of data, but drivers of strategic value?