AI Innovation Summit

As enterprises expand their use of ChatGPT, cloud-based AI and a growing range of models, costs can escalate when every task is routed to the same premier capability. This session explores how leaders can build a balanced AI portfolio by determining where frontier-level intelligence is justified, where lower-cost alternatives are sufficient, and how process design, modernisation and ROI should shape those choices. Leave with a clearer approach to scaling AI across mission-critical environments without allowing deployment costs to erode business value.

The four mission streams reconvene to turn Day 1's challenges into a delivery blueprint. Building directly on The Catalyst, partner-led working sessions move each stream from diagnosis to design — shaping the practical, prioritised blueprint each theme will carry into execution.

Track 1: From Experimentation to Enterprise Impact: How AI Leaders Are Scaling Beyond the Pilot Stage​
Track 2: From Cost Centre to Growth Engine: Proving Business Value from AI Investments
Track 3: Governance That Accelerates Innovation: Building the Foundations for Scalable AI​
Track 4: Fix the Foundation First: Why Data Readiness Determines AI Success​

As AI moves from supporting employees to planning and executing work, enterprises must rethink more than the technology. This session examines how leaders can redesign workflows, roles and decision rights around increasingly autonomous systems, determine where human judgment must remain decisive and establish clear accountability when outcomes are produced by people and agents together. Leave with a practical framework for introducing digital labor without creating confusion over ownership, oversight or control.

Many AI initiatives remain trapped in pilot because organizations wait for perfect data, underestimate adoption or treat automation as a substitute for human expertise. This session explores how Edward Don redesigned a complex RFP process from five weeks to five days by combining AI with institutional knowledge and human judgment. Leave with a clearer approach to selecting commercially meaningful problems, moving forward despite imperfect foundations and building AI capabilities that increase capacity, improve through feedback and earn employee trust.

AI initiatives often stall because leaders use the same language to describe very different ambitions. In this live whiteboard clinic, executives will bring a real use case and determine whether AI is being asked to help people understand, think, do or deliver, at what organizational scale and with what level of human control. Leave with a clearer definition of the initiative, the missing foundations exposed and a practical next move for progressing it.

Enterprise AI portfolios are filling with plausible ideas, but not every use case deserves to reach production. In this live investment committee, leaders will assess competing AI opportunities, respond to new information around business value, exposure, autonomy, opacity, data readiness and adoption, and decide what should be approved, redesigned or rejected. Leave with a practical decision map for matching each initiative to the right level of investment, oversight and post-deployment review.

The AI vendor landscape is expanding faster than most enterprises can evaluate it, and the wrong investment decision can be costly to unwind. This session examines when to build proprietary capability, when to buy from the market and where strategic partnerships offer the strongest route forward. Leave with a clearer decision framework for balancing speed, control, cost, differentiation and long-term flexibility as technologies, vendors and business requirements continue to change.

AI initiatives often begin inside technology or a central Center of Excellence, but they struggle to create lasting value when the business remains only a recipient of the capability. This session explores how leaders can transfer ownership closer to the workflow while preserving the platforms, standards and governance needed to scale, clarifying who is accountable for adoption, outcomes and continuous improvement. Leave with a clearer model for moving AI from centrally led delivery into an embedded business capability without creating fragmentation, duplication or weak oversight.

AI investment continues to rise, yet enterprise value is still being lost between strategic ambition and operational execution. In this Oxford-style debate, two executive leaders will argue whether AI value is won through board-level direction, investment discipline and responsible governance, or through redesigning the workflows, decision rights and human-AI relationships where the business actually operates.

Complex enterprises rarely fail at a single point; disruption often emerges through hidden dependencies across applications, infrastructure and customer journeys. This session explores how AI can strengthen Failure Mode and Effects Analysis by connecting historical incidents, telemetry, system changes and service dependencies to identify where risk is most likely to propagate. Leave with a clearer approach to prioritising resilience around the customer and business journeys that matter most, moving from reactive incident response towards earlier, more consistent intervention.

In a market moving this quickly, today’s strategic AI investment can become tomorrow’s constraint. This session examines how leaders can build for continuous change across models, agents, platforms and infrastructure without repeatedly replacing the foundations beneath them. Leave with a clearer framework for making architectural, standards and investment decisions that preserve flexibility, control costs and prevent short-term technology choices from becoming long-term dependency.

The mission streams converge for a candid, joint verdict. The culmination of the mission-track journey: streams come together to separate what's real from what's hype, and to lock in the concrete commitments each theme carries back to the business. The output every delegate leaves with.

Track 1: From Experimentation to Enterprise Impact: How AI Leaders Are Scaling Beyond the Pilot Stage​
Track 2: From Cost Centre to Growth Engine: Proving Business Value from AI Investments
Track 3: Governance That Accelerates Innovation: Building the Foundations for Scalable AI​
Track 4: Fix the Foundation First: Why Data Readiness Determines AI Success​

Scaling AI requires more than successful use cases; it requires an operating model that can repeat success across the enterprise. This session examines how hub-and-spoke structures can connect shared platforms, governance and model management with business-led delivery, while reducing duplicated infrastructure and one-off development. Leave with a clearer view of what should be centralised, what should remain close to the business and how reusable capabilities can shorten the path from opportunity to deployment.

Traditional ERP is dead and leaders know they cannot wait for slow and costly cloud re-implementations that delay progress. Agentic AI ERP shifts the core from a passive system of record to an intelligent system of action that automates work, learns continuously and delivers real outcomes fast. Skip upgrades and migrations that add no value. Join this session to learn how you can leapfrog your competitors stuck in subscription lock-in migrations and realize true self-funded AI outcomes in weeks, not years.

AI tools are making individuals faster, but those gains often disappear across disconnected teams, slow handoffs and fragmented workflows. This session examines how leaders can turn personal productivity into enterprise performance by redesigning how people, agents and information move through the organization. Leave with a clearer view of how to build shared context, accelerate cross-functional execution and make AI adoption visible in business outcomes rather than isolated efficiency gains.