How to redesign the operating model to move AI from the edges to the core

Despite widespread intent and investment, AI remains stuck at the edges of most organisations because the real constraint is no longer technology, but operating model change, governance, and organisational will.

Most businesses are still layering AI onto existing structures instead of redesigning the core around it.

At the 5th Data & AI Edge, Katarina Dulanovic sat down with ADAPT’s Senior Research Director Matt Boon to examine why so many businesses still fail to move AI into the core.

Key takeaways:

• AI scales when organisations redesign the operating model, not when they keep adding tools to the existing one.
• The biggest gains come when AI reshapes the value chain end to end, rather than sitting in isolated use cases at the edges.
• Scale depends on governance and workforce confidence being built in from the start, so trust, resilience, and adoption can grow together.

Stop optimising technology, start redesigning the business

Katarina is clear that the technology debate is largely settled: cloud platforms, data tools and AI capabilities are more than sufficient.

What’s missing is the courage to fundamentally change how organisations operate.

Too many leaders are still focused on platform choices rather than reshaping roles, workflows and decision-making with AI embedded at the core.

AI doesn’t replace people; it changes what they do and delaying that redesign until a perfect business case exists only ensures organisations fall behind.

Culture, value chains and the end of bolt‑on AI

Embedding AI requires moving beyond isolated use cases and efficiency wins to rethinking the entire value chain, end to end.

Organisations fail when AI is bolted onto existing silos rather than reshaping how functions work together.

Data culture is not training alone; it’s shared understanding of data, ownership, and purpose across the business.

Leaders must decide what kind of organisation they want to be in two years’ time and then embed AI (with humans in the loop), across that future state.

Governance, resilience and people confidence

Governance is not a compliance artefact or an IT problem; it’s a team sport and a core business capability.

Data and AI governance must be embedded “by design” into operating models, not treated as projects or checklists.

At the same time, leaders must address fear directly: jobs will change, not disappear, and honesty builds trust.

AI systems will fail at times; what differentiates strong organisations is preparedness, governance, and the ability to recover quickly without damaging customer trust.