Executive Summit

Unlocking enterprise value from data and AI has emerged as a key measure of success for CDAOs. Demonstrating tangible outcomes from pilot projects and data hygiene investments - once a primary focus of data teams - has now shifted towards an expectation of immediate results. However, could the emphasis on speed and benchmarking against other organisations actually constrain your potential and that of your business? How do you find your own path to value, and build the strength of influence to action it?

Join this keynote session from Sarah James, Sr Director Analyst, Gartner, to hear insights on:

• How to identify the unique value path for your organisation instead of benchmarking your ambitions against industry averages and competitor use cases
• Practical approaches to balancing short-term demands for AI results with the long-term investments required to create sustainable business advantage
• Actions the most influential CDAOs are taking today to establish themselves as indispensable transformation leaders in an increasingly AI-driven enterprise

Data has progressively gained more prominence as a department of change and transformation. As AI changes what's possible, data leaders have experienced a myriad of shifts- some gained a dual remit, some have a new partner to work with in the form of a Chief AI Officer, and some people have entered an enablement role in the data function. But which of these configurations best enable organisational progress with Data and AI?

Join a CDO, CAIO, and CDAIO as they debate and discuss their views on:

• How should responsibilities be divided between data, AI, technology, and business leaders?
• Can organisations make meaningful progress with AI without clear ownership and accountability?
• Who should ultimately own AI strategy: the business, technology, data, or a dedicated AI function?

The uncomfortable truth emerging from a wave of stalled AI pilots: the model is rarely what fails. Most AI pilots stall because agents lack understanding of specific nuances, and cannot interpret the unique context of each business. The enterprises breaking through to production-grade automation are not buying better models, they’re building unified data foundations and semantic frameworks that make business meaning machine-readable. This shift unlocks true AI progress, enabling greater autonomy of agents, while human oversight moves from reviewing every output to governing exceptions.

Join this session to discuss:

• What an agent-ready foundation contains: consumption-grade data products, ontology and semantic layer, knowledge graph, context graph, and who should own each.
• Model capability versus missing business semantics, and how to tell which is failing in your stack
• How far human-in-the-loop can realistically shrink as agent pathways mature, and which decisions should never be delegated

Chief Data & Analytics Officers face growing pressure to maximise the value of AI investments while ensuring trust, governance, and measurable business outcomes. As AI models become increasingly accessible, critical differentiators are emerging, most importantly, the ability to establish trusted enterprise information and transform that into enterprise intelligence. Only then is it possible to leverage that intelligence to drive AI-powered business outcomes, measurable business value, and sustainable competitive advantage over the next 24 months.

In this session, you will explore:

• What capabilities and strategic bets are most likely to differentiate AI and Data leaders over the next 24 months
• How leading organisations are building AI-ready information fabrics to connect legacy and modern data estates, unlock enterprise intelligence, and improve AI outcomes
• Common barriers preventing organisations from realising value from AI, and approaches to overcoming them

Connect with like-minded peers in a one-on-one setting through Peer-to-Peer Meetings. You will be matched with peers in your community based on your shared interests and priorities.

As analytics and AI adoption accelerates, CDAOs are shifting from reactive data quality to proactive, end-to-end visibility across the data lifecycle. By embedding governance and automation, organizations can scale reliable, decision-ready data products that deliver measurable business value.

Join this session to:

• Build trusted, enterprise-scale data workflows
• Enable proactive visibility for scalable data products
• Automate data reliability for analytics and AI success

More to Come!