The Cost of Waiting: Why AI Readiness Is a Leadership Problem
- Executive Central
The Cost of Waiting: Why AI Readiness Is a Leadership Problem
Most organisations are asking the wrong question about AI. The question isn’t which tools to buy. It’s whether your leaders are ready to lead people through what those tools change.
The answer, for most, is no. Gartner’s latest CHRO Report found that 63% of leaders feel unprepared to drive their organisation’s AI objectives. And 86% of HR leaders say the leadership competencies they rely on need updating.
That gap is expensive. And it gets more expensive every quarter it stays open.
The change is already happening, with or without a plan
It’s tempting to treat AI as something coming down the road. It isn’t. Gartner reports that 56% of employees already use AI for a core part of their job, and 40% of CHROs say their organisation has already redefined roles or skills because of it.
In many organisations, this is happening quietly. Teams are changing how they work without anyone deciding what good looks like. HR often isn’t in the room. Leaders are left to manage the fallout without the skills or the language to do it well.
And the pace is picking up. PwC’s 2026 Global Workforce Hopes and Fears Survey, which heard from nearly 50,000 workers in 48 countries, found 64% used AI at work in the past year. That’s up 10 points on the year before. Daily use of generative AI rose from 14% to 22%.
In Australia, the picture so far is quieter, and that’s worth being honest about. The Department of Employment and Workplace Relations (DEWR) found no evidence to date of broad AI-driven upheaval in our labour market. But it did find an early signal. Between November 2022 and February 2026, employment in the most AI-exposed fifth of occupations grew by 5.6%, compared with 9.5% in the least exposed. DEWR is careful to say this isn’t proof AI is costing jobs, and that the signal has become clearer in recent quarters.
DEWR’s data also can’t see how tasks and skills are changing inside jobs. That’s where the shift is happening first, and it’s where leaders are needed.
Why AI adoption stalls
AI projects rarely fail because the technology doesn’t work. They stall because people don’t change how they work.
Gartner found that 47% of employees who are expected to use AI resist it in their daily jobs. That resistance isn’t stubbornness. It’s usually a sensible response to uncertainty: What does this mean for my role? Am I being measured differently? Is anyone going to show me how?
Traditional change management was built for projects with a clear start and finish. AI doesn’t work like that. It’s continuous. The tools keep changing, and so do the jobs. Leaders who treat AI as a one-off rollout end up stuck in a cycle of launch, low uptake, and relaunch.
A new divide: your best people and everyone else
PwC’s research points to a workforce that is starting to move at two speeds.
On one side are the “front-runners”: people with scarce skills and strong AI capability. They’re more confident, more ambitious and more mobile. Almost a third (29%) say they’re very or extremely likely to change employer in the next year.
On the other side is what PwC calls the “engine room”. That’s 56% of the workforce, the people doing most of the day-to-day work, whose skills are less scarce and who aren’t far along the AI learning curve. Only two in five of them say they have access to the learning and development they need. Across the whole workforce, that figure has dropped from 59% to 51% in a year.
So organisations face two risks at once: losing the people who are furthest ahead, and leaving the majority behind. Both are leadership problems. PwC found daily AI users are 15 points more likely to trust top management and 21 points more confident they can learn new skills. Support and trust go together.
What waiting actually costs
The cost of not acting shows up in places that don’t appear on an AI business case:
- Investment that never pays back. Licences get bought, pilots get run, and usage flatlines because nobody changed the way work gets done.
- Losing your most capable people. The employees furthest ahead on AI are the ones most likely to leave. If they don’t see growth with you, they’ll find it somewhere else.
- A majority left behind. When learning doesn’t keep up with change, most of your workforce falls further behind every quarter.
- Jobs that get worse, not better. Gartner warns that layering AI onto old processes can create roles that are monotonous, isolating or mentally exhausting. PwC found 27% of workers already say fatigue or burnout limits their productivity.
- Leaders losing credibility. Managers who can’t answer their team’s questions about AI lose trust quickly, and that trust is hard to rebuild.
Meanwhile, the organisations moving now are pulling ahead. According to Gartner, organisations that build leader behaviours that support AI adoption are 2.3 times more likely to see meaningful business value from their AI investments.
The manager’s job has changed
One of the clearest findings in the report is about managers. As AI takes over administrative work like scheduling, status updates and meeting summaries, Gartner says the manager role shifts toward empathetic leadership, coaching and oversight of how people and AI work together.
That’s a different job. It asks for different skills: holding honest conversations about uncertainty, helping people find meaning in changing roles, coaching rather than directing. Seventy-five per cent of CHROs believe leadership and people management skills will become more important as AI is integrated, not less.
Leaders are feeling the change first. PwC found 51% of senior executives and 46% of managers had applied new skills in their roles over the past year, compared with 29% of non-managers. They’re being asked to learn and lead at the same time.
Most managers were never developed for this. They were promoted for being good at the work, then left to figure out leadership on the job.
Where to start
You don’t need a perfect AI strategy to begin. You need leaders who can guide people through change that doesn’t stop. Three places to start:
- Get clear on what’s changing in your roles. Look at where AI is already reshaping work and ask whether those jobs are getting better or worse for the people in them.
- Update what you expect of leaders. If your leadership framework still describes the manager of five years ago, it won’t help anyone lead through this. Focus on outcomes and the capabilities that matter most to your business.
- Develop the whole workforce, not just the front-runners. Keep investing in your most capable people so they stay, but make sure the engine room gets real support too. Leaders are the ones who make that happen day to day.
- Invest in coaching capability. Coaching is how leaders help people adapt, and it’s the skill the manager role is moving toward. Building it into your leadership development gives change somewhere to land.
At Executive Central, we work with organisations to build leaders who can lead through continuous change. Through executive coaching, the Coaching Academy and leadership programs such as Emerging Leaders and Women Leading, we help leaders develop the capabilities AI transformation depends on: clarity, trust, and the ability to coach their people through what comes next.
If you’re thinking about how ready your leaders are for what AI is already changing, we’d welcome a conversation.
Contact Us now!
Sources: Gartner, The CHRO Report, 3Q26. PwC, Global Workforce Hopes and Fears Survey 2026. DEWR 2026, AI and employment in Australia: Monitoring framework and evidence to date, Department of Employment and Workplace Relations, Canberra.
