Is AI the Priority if it's Getting 2.5% of the Week?

I’m seeing a huge uptick in organizations giving their teams protected time for AI exploration, and this is a really great start in giving opportunities to learn the tools, and play around with what AI can and can’t be used for. Some organizations require 2-4 hours a week, but I’m seeing most offer 1 hour of protected time, and in a lot of cases on a Friday afternoon.

But here’s where the math just doesn’t math for me. Many companies are committing to AI adoption and enablement being their number one priority, to give their teams capacity to do other things. Let’s automate the mundane or time-consuming parts of the job, and give more time for innovation. That makes sense, and in a lot of cases was one of the reasons for heavy AI investment.

But I have 2 issues with this…

The first – if AI is the priority, and you are protecting 1 hour a week, then in a standard 40 hour work week, you are giving people 2.5% of their week to step away and explore it. AI will show up throughout the rest of their week too, so the other 97.5% is expanding, but when I ask organizations what projects have been deprioritized, or what has been removed from leaders calendars in order for this to happen, the answer I get most is: nothing.

So in that 97.5%, leaders are now also expected to learn the technology, decide where it fits in their teams, redesign workflows (and in some instances their teams), think cross-functionally and have a stance on where humans need to be involved in the work. Not only that but there is also now added pressure of managing how their teams feel about all of this. People are anxious and worried about what this means for their jobs, and are asking leaders questions, most don’t have the answers to yet.

The second – organizations expect AI investment to increase efficiency and capacity, but in order to understand how and where AI can create capacity, you first need capacity to do that. You need time to sit with the actual work before you can decide what could or should change. You can’t give someone a tool and an hour on a Friday afternoon, to go and explore the orgs number one priority, and expect them to produce real clarity. This would need testing, collaboration, disagreement, communication etc.

So what I am seeing happen is that leaders are absorbing this themselves. They’re taking on more work, staying later and delaying their own development. However, in six months time, this could be one of the reasons transformation is slow. They’re doing instead of teaching, so capability isn’t being built below them, and their own thinking stays narrow when it needs to broaden across the organization.

This is what I call the Hero Leader Loop showing up – if the org keeps depending on the leaders ability to absorb more without removing anything, it may initially look like progress because they’re delivering, experimenting and still supporting the team, but it isn’t a long term strategy. If they aren’t building capability below them, the org will eventually feel it in how quickly this can scale.

I don’t think the fix here is to give 5 hours instead of 1, but I do think organizations need to ask themselves if AI is truly the priority, what are you willing to stop doing to make room for it? What can be deprioritized and taken off the calendar?

AI might eventually free-up huge amounts of capacity inside your organization, but first people need enough capacity to work out how. Protected experimentation time is a good intervention, but the mistake would be to believe that this time alone can create the organizational capacity required for transformation. If we look at what’s being removed from leader’s workloads to make room for it, the capacity being created doesn’t appear to match the scale of the expectation.