Presentation

Keynote
 

Panel discussion moderated by Marc Hodes

As AI systems evolve from assistants to autonomous agents, enterprises need a clear operating model, decision rights, governance, delivery standards, and accountability. This panel explores what an effective AI Center of Excellence looks like in practice: who sits on the team, how it partners with business units, how it sets standards for security and compliance, and how it scales successful use cases across the organisation.

We’ll discuss what the CoE should centralise vs federate, how to avoid becoming a bottleneck, and how to maintain human oversight for risk management and quality. Attendees will leave with patterns for structuring an AI CoE that accelerates outcomes while reducing risk.

TBC

Panel discussion moderated by Mike Dronfield

UST surveyed enterprise technology decision-makers in industries ranging from financial services and healthcare to manufacturing, retail, and consumer packaged goods to better understand how they are changing, upgrading, and modernising their cloud and on-premises infrastructure and observability tooling to support AI workloads.

This session will share findings from UST’s survey of enterprise decision-makers and discuss what those shifts mean in real environments, cloud, on-prem, and hybrid. Panellists will unpack where organisations are investing, what’s driving those decisions, and what pitfalls to avoid as AI moves into production.

Presentation

Data modernization and AI are inseparable. AI demands data architectures capable of handling unstructured data, real-time analytics, and continuous compliance monitoring. Traditional batch ETL pipelines and siloed data systems cannot meet these requirements. Without modern, cloud-native, and event-driven data platforms, enterprises cannot achieve the agility, scalability, and trust required for advanced AI use cases.

Modernising enterprise data should centre on creating a sentient data stack- an architecture that combines semantic modeling, autonomous agents, and policy-as-code to create adaptive and goal-driven data operations.  To accelerate this transformation, we advise organisations to rethink their data architecture in six core areas: Semantic-first modeling, Agent-ready API design, Retrieval-Augmented Generation/RAG, AgentOps, Responsible AI governance, and human mediation. 

Panel discussion moderated by Barry Matthews

Success is measured less by novelty and more by repeatable business impact. This panel shares how enterprises quantify value using practical metrics such as Task Completion Rate (TCR), Work Reduction Rate (WRR), and Cost per Task (CPT) and how they translate those measures into funding decisions, operating changes, and scaled deployment. Leaders will discuss what worked, what didn’t, and why initiatives commonly fall short (data readiness, adoption, process redesign, controls, or unclear ownership). 

Panel discussion moderated by Heather Dawe

With the rise of AI used in the SDLC, IT leaders must rethink application security and governance across infrastructure, applications, and LLMs. Managing risk in the age of ‘white coding’ is essential to address challenges such as hallucinations, context overload, and model drift.

Many organisations have acquired disparate tools to improve observability. For AI in the SDLC, organisations need an architectural layer that integrates into the engineering platform and feeds development models. An integrated observability layer becomes the nervous system for AI.  

CPG is entering a major shift: categories are commoditizing, challenger brands are reshaping consumer relevance, sustainability expectations are rising, and AI is accelerating change across marketing, innovation, and supply chains, all while margins stay under pressure and portfolios are being reconfigured. This session explores what will differentiate the companies that lead over the next 10–20 years, whether traditional gross-margin improvement levers still work, how technology adoption will transform end-to-end operations, and where tech partners can help CPG organizations navigate and shape this transition.

Workshop

This working session turns the day's insights into a concrete execution plan. Using a guided workbook, participants will take 1–2 real use cases through three phases, Diagnose & Design, Prototype & Prove, and Operationalise & Scale, to produce a 90-day roadmap with named owners, governance checkpoints, success metrics, and dependency tracking (data, security, change management, delivery capacity).

You’ll also identify your biggest blockers and leave with a reusable framework you can run with your teams to replicate the process across additional use cases.