When AI Does the Work, What Should Humans Adapt?

AI is changing the way we work.

It can write, analyze, summarize, generate code, create content, answer questions, and increasingly perform tasks that were previously done entirely by humans.

And this is only the beginning.

So a simple question emerges: How should we adapt when AI starts doing the work?

Observe

The first reaction is often to add AI to the way we already work.

Same processes. Same roles. Same workflows.
Just faster.

A developer uses AI to generate code. An analyst uses it to analyze information. A manager uses it to prepare a report. A leader uses it to synthesize data and support decisions.

These can all create value.

But if AI changes what can be done, how quickly it can be done, and who — or what — can do it, simply adding AI to our existing way of working may not be enough.

We may become more efficient without really adapting.

Over the years, I’ve seen technologies, practices and ways of working evolve significantly. One thing remains consistent: introducing a new technology is often easier than adapting the system around it.

AI makes that challenge even more visible.

Adapt

Perhaps the more interesting questions are not only:

What can AI do for us? or What can we automate?

But also:

What should change because AI can now do it?

If AI can perform part of our work, we need to reconsider the work around it.

What should humans continue to do?
What should AI assist with?
What should AI do independently?
Where is human judgment still essential?

And what new capabilities should humans develop as some existing tasks become easier, faster or automated?

This is already more than adopting a new tool.

It is adaptation.

Look at the whole system

Imagine AI can now perform 30% of the work of a software team.

The obvious question might be:

Which tasks can we automate?

But that may be the smallest question.

If the work changes, the workflow may need to change.
If the workflow changes, roles and interactions may change.
If work and decisions happen faster, the information and feedback we need may change.
If productivity increases, the way we measure value and outcomes may need to change.

And if all of these things change, leadership may need to adapt too.

The developer sees a different way to create software.
The team sees a different way to collaborate.
The manager sees different capabilities and constraints.
The executive sees a different operating system for the organization.

They are looking at the same transformation from different parts of the system.

AI doesn't only change the work. It can change the ecosystem around the work.

Evolve

This also means there probably isn't one universal answer.

A developer, a designer, a manager, a team or an entire organization will not adapt in exactly the same way.

Their context is different.
Their constraints are different.
Their goals are different.

And as AI itself continues to evolve, today's answer may not be tomorrow's answer.

So instead of trying to design the perfect future now, perhaps we need a simpler capability:

Observe. Experiment. Learn. Adapt.
Then do it again.

This is what I want to explore through Adaptive Circle: how humans, teams, organizations, AI and technology can continuously adapt as their environment changes.

Not adaptation as a one-time transformation.
Adaptation as a continuous capability.

And I'd like to start with you:

If AI started doing 30% of your work tomorrow, what would you change first?

Your tasks? Your workflow? Your skills? Your team? The way you measure value? Something else?

I'd be interested to hear your perspective.

And if these are questions you want to keep exploring, follow Adaptive Circle.

We are only at the beginning.