AI Should Create Capacity. Not Consume It.
The Atamai Perspective
Anne McGuire · Founder, Atamai Advisory · July 2026
Over the past few months, I've noticed a pattern in conversations with leaders and former colleagues. The conversation usually starts the same way:
"I know I should be using AI more, Anne. I just don't have time."
It's an interesting response because nobody is questioning whether AI matters. Most people genuinely want to learn. They're curious about the technology and they can see its potential. What they're struggling with is finding the capacity to do it while keeping up with everything else their role demands.
The more I hear this, the less I think it's an AI problem. I think it's a leadership problem.
During my time at Workday, one of our performance goals was to incorporate AI into our everyday work. It was the right objective. AI was quickly becoming an important capability, and encouraging people to experiment made sense. But it also left me with a question: how would we know if we'd actually succeeded?
Would success simply be that people were using AI? Or would it be that they were making better decisions, working more effectively and creating measurable capacity? Those are very different outcomes.
This is where I think many organisations are getting stuck.
If a business decides to implement a new CRM, nobody expects the sales team to figure it out for themselves. We don't send an email saying, "Here's the software, go and build your own workflows." We redesign processes. We train people, provide support and establish new ways of working because we understand that technology alone doesn't create business value.
Yet that's often how AI is being introduced.
People are given access to powerful tools and encouraged to experiment, but with very little clarity about where to start, what problems they're trying to solve or what success actually looks like. The expectation seems to be that value will emerge naturally.
Sometimes it does. Often it doesn't. I think that's because we're measuring the wrong thing.
Using AI isn't the goal. Creating capacity is.
If AI simply becomes another tool people are expected to learn on top of an already overloaded workload, we've misunderstood its purpose. Technology should remove work before it creates new work. Otherwise, we're not improving the way the organisation operates, we're simply asking people to do one more thing.
The leadership conversation shouldn't begin with, "How do we get everyone using AI?" It should begin with a much more practical question:
"What work are we going to stop doing because AI can now do it for us?"
That's where the real value lies.
It might be producing the first draft of a proposal, summarising meeting notes or automating repetitive administrative tasks. The specific use case matters less than the principle. Every meaningful use of AI should give people back time to focus on the work that requires judgement, creativity and human connection.
Perhaps that's why I keep coming back to those conversations with friends and former colleagues.
When someone tells me they don't have time to learn AI, I no longer hear resistance to technology. I hear an organisation that hasn't yet created the space for people to change the way they work.
AI isn't exposing a lack of technical capability. It's exposing whether an organisation already knows how to change.
And I suspect that's the conversation more leadership teams should be having.
About Anne McGuire
Anne McGuire is Founder of Atamai Advisory, an executive advisory practice helping organisations navigate growth, transformation and AI through better operating models, organisational capability and practical execution.
Anne writes The Atamai Perspective, sharing observations from more than 20 years leading operations, transformation and technology inside global enterprises and high-growth businesses.
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