There is no question that AI is becoming part of everyday working life. People are using it to draft documents, analyse information, prepare presentations, create marketing material, summarise meetings, solve problems and get to a first answer much faster than they could before. In many cases, that is a good thing. Used well, it can remove a lot of the routine work that takes up time and give people more space to focus on the things that actually require experience, judgement and context. What interests me is what that means for leadership.
The more capable the technology becomes, the easier it is to assume that some of the thinking has been done for us. A response arrives quickly, it is well structured, it sounds confident and, on the surface at least, it often looks perfectly reasonable. That creates a very different challenge from simply learning how to use the technology. Leaders still need to know whether the answer is right, whether it makes sense in the circumstances and whether it is something they are prepared to stand behind.
There is some interesting research emerging around this. PwC’s 2026 Global AI Jobs Barometer found productivity growth was significantly higher in industries most exposed to AI. It also found that junior roles with high exposure to AI were seven times more likely to require skills traditionally associated with more senior positions, including judgement and leadership.
I think that is telling. As technology becomes better at producing information, summaries, analysis and recommendations, some of the things we once associated with doing the work start to shift. What becomes more valuable is the ability to assess what you are looking at, understand what is missing and make a call when there is no perfect answer.
That is not really a new leadership skill. Good leaders have always had to work with incomplete information. They have always had to weigh competing views, understand the consequences of a decision and occasionally trust their experience when the numbers do not tell the whole story. AI simply puts that responsibility into sharper focus because the output can look so convincing. But have we put too much faith in it? We have all heard stories where AI got it wrong. So if it is not infallible, we need to ensure we have the ability to question the answer. It’s vital to remember the danger of becoming too reliant on AI means we are handing over the responsibility of our own work outcomes to something that can never be accountable or responsible. So before you submit that research presentation, you need to consider double checking what AI is telling you.
Microsoft’s 2026 Work Trend Index found that 66 per cent of AI users said the technology allowed them to spend more time on higher-value work. At the same time, only 26 per cent believed their leadership was clearly and consistently aligned on how AI should be used. One of the observations from the research was that the most advanced users did not simply accept what AI gave them. They used it to extend their thinking rather than replace it.
That is probably the distinction leaders need to keep in mind.
The useful question is not whether someone used AI to help them with a piece of work. Increasingly, that will be normal. The better questions are: Did they check it? Did they challenge it? Did they understand the assumptions behind it? Could they explain why they agreed with the recommendation? And, most importantly, would they still be comfortable putting their own name to the decision?
There is also a broader organisational issue here. Gartner research in Australia found that while many employees now have access to enterprise AI tools, a large proportion are also using personal AI tools to help them work more efficiently or solve more complex problems. That tells us adoption is happening whether organisations are completely ready for it or not.
The leadership response cannot simply be to put a policy in place and assume the issue is dealt with. People need to understand where AI is useful, where the risks sit, when they need to disclose its use and where human judgement remains essential. They also need to know who is ultimately responsible for the outcome.
Deloitte’s 2026 Human Capital Trends research found that 80 per cent of leaders, managers and workers were concerned that people might use AI to appear more productive than they really were, while only a small proportion of organisations said they were making meaningful progress in redesigning work around the relationship between humans and AI. That gap is worth paying attention to.
The technology is moving quickly, but the harder work is still organisational and human. It is about deciding what good judgement looks like, what standards still matter and how responsibility works when technology has played a role in getting to the answer.
There is a lot to be optimistic about. AI can make people faster, give them access to better information and remove some of the work that adds very little value. But it does not know your organisation in the way you do. It does not understand the people affected by a decision, the history behind it or the consequences if you get it wrong.
And that is where leadership still sits. AI can help you reach an answer, but the responsibility for deciding whether it is the right one still belongs to you.
Rod Matthews