# The AI Challenge Nobody Wants to Own

_Why AI isn’t delivering ROI and how to fix it. Learn how to move from pilots to scalable AI business value with the right operating model._

[AI](https://www.fusion5.com/au/artificial-intelligence)is delivering real productivity gains, yet translating those gains into meaningful business outcomes is proving harder than many expected. The missing piece may not be the technology itself, but the organisational redesign required to realise its value.

Two years ago, the question was whether AI would deliver meaningful productivity gains. Today, that question has largely been answered.

Across Australia and New Zealand, organisations are rolling out [Copilot](https://www.fusion5.com/au/microsoft/microsoft-copilot), experimenting with agents, automating tasks and embedding AI into day-to-day operations. Teams are creating content faster, accelerating research, reducing manual effort and finding new ways to improve productivity.

The productivity gains are real, and in many cases they are arriving faster than previous waves of technology change.

Yet alongside the excitement sits a growing question for leadership teams. If AI is improving productivity across the organisation, where is the business value beginning to show up?

For some, the answer is becoming clearer. For others, it remains harder to identify. Improvements in margins, reductions in cost to serve, increases in operating leverage and measurable shifts in business performance are proving more difficult to capture than the productivity gains that sit beneath them.

As a result, AI adoption is moving faster than AI value.

## Productivity is not the same as value

The first wave of AI has largely focused on helping people work faster, and the gains have been significant. Employees can complete tasks more efficiently, access information more quickly and automate routine activities that previously consumed valuable time.

Those gains matter, but productivity is an input, not an outcome.

An organisation does not become more profitable simply because employees complete tasks faster. Productivity creates potential. Real value is only created when that potential is translated into improved performance, whether through higher revenue, lower costs, better customer experiences or new ways of operating.

## We've seen this before

History suggests this should not surprise us.

When electricity first arrived in factories, many organisations replaced steam engines with electric motors but left the factory layout and operating model largely unchanged. The technology improved, but the way work was organised remained much the same.

The significant gains arrived later, when businesses redesigned their factories around what electricity made possible.

Economist Erik Brynjolfsson has made a similar observation about digital technologies. The greatest returns rarely come from technology investment alone. They emerge when organisations redesign processes, structures and ways of working around new capabilities.

AI may be following a similar path. The opportunity is not simply to help people work faster, but to rethink how work is organised in the first place. That shift, from improving existing work to redesigning it, is where the greatest value often emerges.

## Organisations were designed for a different workforce

Most organisations are still designed around an all-human workforce. Workflows, approvals, accountability models, performance measures and management structures continue to reflect the assumption that people perform the work, make the decisions and manage the exceptions.

AI is increasingly participating in customer interactions, analysis, [administration](https://www.fusion5.com/au/artificial-intelligence/blogs/ai-agent-transforms-legal-team)and operational processes. The next wave of agentic AI extends beyond helping people complete work more efficiently and towards executing elements of the work itself.

As that shift gathers pace, organisations will need to rethink assumptions that have long sat at the heart of how work is organised.

This helps explain why organisations are seeing productivity gains without corresponding business transformation. AI does not simply change tasks. It changes where decisions are made, how information flows and how people interact with processes and systems.

In many cases, organisations are introducing AI into operating models that were never designed to accommodate it.

Research suggests leaders recognise the challenge. Deloitte's 2026 Global Human Capital Trends research found that while 85% of organisations view adaptability as critical, only 6% report meaningful progress in designing effective human-AI interactions.

The gap is striking. Most organisations recognise that work will need to change, but far fewer have [developed a practical approach for redesigning work, integrating human and AI capabilities, and determining who should lead that effort](https://www.fusion5.com/au/artificial-intelligence/agentic-ai-transformation).

Creating the foundations for secure, governed and scalable AI operations.

## The AI challenge nobody wants to own

If organisational redesign is increasingly becoming the source of AI value, an obvious question follows: who owns it?

The answer is often less clear than organisations expect.

Technology has owners. Cybersecurity has owners. AI platforms have owners. Organisational redesign rarely sits neatly within a single function.

That is partly because the greatest opportunities often sit between functions rather than within them. They span Operations, Finance, HR, Customer Service, Technology and the broader business. The friction that slows work down is often found in handovers, approvals, duplicated effort and disconnected processes that cut across organisational boundaries.

Unlike a technology deployment, organisational redesign cannot simply be delegated to a single team. It requires changes across functions, processes and ways of working, making ownership, sponsorship and governance significantly more complex.

This is what makes redesign difficult. Not because leaders disagree with the need for change, or because teams are actively resisting it, but because few people have the authority, visibility and capacity to redesign how work flows across the organisation.

There is also a more practical challenge. One of the paradoxes of AI is that the productivity gains it creates do not automatically generate space for transformation. Teams become more productive, expectations increase and more work gets done, but the newly created capacity is often absorbed just as quickly.

Many leaders will recognise this pattern. Despite becoming more efficient, their teams often feel busier than ever. As a result, organisations become increasingly effective within the existing operating model while having less time to step back and question whether that operating model still makes sense.

Everyone agrees redesign is necessary. Far fewer organisations have decided who owns it.

## Creating ownership for redesign

The organisations making the strongest progress are creating deliberate ownership for redesign.

Rather than relying on governance committees, additional meetings or responsibilities squeezed into already overloaded roles, they are establishing small cross-functional groups that combine business knowledge, operational expertise and technology understanding.

Their focus is not simply identifying more AI use cases. It is understanding how work flows through the organisation, where value is created, where friction exists and where AI creates an opportunity to rethink how work gets done.

These teams are given the time, authority and executive sponsorship to act on those opportunities. They can examine processes that span organisational boundaries, challenge existing assumptions and redesign workflows around what AI now makes possible.

Importantly, this work is treated as a capability rather than an extracurricular activity. Redesign rarely happens by itself. Day-to-day work has a habit of consuming the very capacity that productivity gains create, leaving teams increasingly effective within existing processes but with little opportunity to step back and rethink them.

This aligns with a growing body of research suggesting that organisations achieving the strongest returns from AI invest heavily in people, process and organisational change alongside technology itself.

Ultimately, the goal is not more AI activity. It is redesigning how value is created.

## The next phase of AI is organisational

For the past two years, much of the focus has been on how organisations can fit AI into the business. The next challenge is more complex: understanding how the business itself should change because AI exists.

The organisations that create the greatest value from AI will not necessarily be those that deploy the most technology. They will be the ones willing to rethink how work, decisions and accountability operate in a world where AI is increasingly becoming part of the workforce.

As organisations move beyond experimentation and early productivity gains, a new challenge is emerging. Not whether AI can create value, but how organisations organise themselves to realise it.

That is the AI challenge nobody wants to own.

And increasingly, it is the one that matters most.

Tim spends time with tech leaders and customers to understand how transformation really plays out. He turns real-world examples into clear, practical content focused on what changed, what worked, and what others can learn.