Artificial intelligence is now embedded in much of the software organisations use every day. Yet despite rapid adoption, the impact many leaders expected has not fully materialised.

Last year, 32 per cent of leaders expected AI to be transformative for their organisation (HRIB 2025). Twelve months later, only 15 per cent of Australian organisations report seeing significant impact so far (HRIB 2026).

The gap is striking. But it’s not a technology problem. It’s a workforce design problem. In many organisations, technology is changing faster than the work itself. Tools are being introduced, pilots are running and employees are experimenting, but the structure of roles, workflows and capabilities often remains largely unchanged. Adoption, in other words, is not the same as transformation.

ELMO President Joseph Lyons

The real issue: we haven’t redesigned work

Much of the conversation around AI has centred on productivity gains from the tools themselves. In reality, those gains only materialise when organisations rethink how work is structured — redesigning roles, redefining capability requirements and understanding how automation will reshape jobs over time.

It does not necessarily have to be about pure headcount reduction. Rather than cost out and then rehire, the opportunity is to reskill and redeploy. This shift requires organisations to connect elements that have traditionally been managed separately: job architecture, capability frameworks, performance management, learning and succession planning. 

At ELMO, through our industry first, AI-powered Career Development solution, we are increasingly helping organisations map skills and capability frameworks across job families, making explicit the AI literacy and digital competencies required within each role.

Those insights do not sit in a static document that takes months of consulting time to produce, only to become outdated almost immediately. Instead, they connect directly to progression pathways, learning plans and performance conversations.

Just as importantly, they enable organisations to forecast capability needs before disruption occurs. Forward-looking HR leaders are increasingly asking new questions: which roles in my organisation are most exposed to AI-driven change? Where should we be investing in reskilling now? What capabilities will our workforce need two or three years from today?

By combining skills frameworks with workforce data, organisations can build a capability forecast that answers these questions before disruption becomes visible. That visibility changes the strategic question leaders ask. 

Instead of focusing purely on where headcount can be reduced, organisations begin asking where existing talent can be redeployed and where capability gaps need to be addressed.

We have already seen examples internally where individuals in implementation roles had adjacent skills that could be redeployed into customer success roles. 

The result was stronger retention and improved revenue outcomes without external hiring. That shift from cost reduction to capability redeployment is where AI’s real organisational value begins to emerge.

Accountability across the C-suite

Another misconception is that AI transformation sits solely with technology teams. In fact, two in five HR leaders (39 per cent) believe responsibility should lie entirely with IT (HRIB 2026). 

In reality, AI accountability must sit across the executive team. Leaders cannot ask teams to change the way they work without examining how their own teams operate first. Any leader who is not reviewing how work is done, and what tools their teams are using, risks falling behind.

Functional leaders must take ownership of how AI reshapes their operating models. The CEO, CFO and Chief People Officer play a central role in determining how the workforce evolves. Technology leaders, including emerging roles such as Heads of MLOps, are responsible for governance, infrastructure and integrity.

I believe this is HR’s most profound and exciting opportunity in decades: to act as the architect of the workforce. That means shaping capability frameworks, guiding organisational change and ensuring businesses maintain a human-centred approach as automation accelerates.

The need for clearer leadership is already visible in workforce sentiment. Only 19 per cent of employees say expectations around AI use in their organisation is very clear, while just 14 per cent feel very well supported to use AI responsibly and effectively (HIRB 2026). As adoption expands, leadership clarity is undoubtedly becoming increasingly important.

Why fragmented AI is breaking down

A further barrier to impact is the fragmented way some organisations have approached AI. Pilots often sit within individual teams, new tools are introduced to solve isolated problems and data remains spread across multiple systems. In fact, ELMO’s 2026 HR Industry Benchmark research found only six per cent of organisations have more than three-quarters of their workforce using approved AI tools. 

But HR leaders are starting to push back against this approach. What they are increasingly asking for instead is an integrated and complete platform that connects data, workflows and intelligence across the employee lifecycle. 

This is the structural shift required if organisations want to move beyond experimentation and deliver measurable gains.

What executives must do differently

For leaders, the implications are clear. Organisations that treat AI as a workforce design challenge will unlock far greater value than those treating it as a technology upgrade. The technology is already here. The real transformation begins when leaders redesign work around it, connecting capability, roles and workforce planning to the reality of AI-enabled work.

ELMO is the Complete AI Workforce Platform. Find out more here.