On AI and the Future of Work

Much of the conversation about AI focuses on a single question:

Will it replace jobs?

It's an understandable question. Every major technological shift has changed the nature of work, and AI appears capable of automating activities that were once considered uniquely human.

But I suspect we're paying too much attention to replacement and not enough attention to redesign.

Throughout history, technology has rarely eliminated work in a single step. More often, it changes how work is performed, what skills are valued, and where people spend their time.

Spreadsheets didn't eliminate finance professionals.

They changed what finance professionals did.

Email didn't eliminate communication.

It changed the speed, volume, and expectations surrounding communication.

The internet didn't eliminate research.

It changed how information was gathered and evaluated.

AI may follow a similar pattern.

Many of the tasks now being automated are routine forms of cognitive work. Summarizing information. Drafting content. Organizing knowledge. Generating options. Identifying patterns.

These activities matter.

But they're rarely the entire job.

A financial advisor doesn't create value by producing information alone.

A teacher doesn't create value by delivering information alone.

A physician doesn't create value by providing information alone.

Their work also involves judgment, interpretation, communication, trust, and context.

As AI becomes increasingly capable, organizations will face a different challenge.

Not which jobs disappear.

But how jobs change.

If research takes minutes instead of hours, what should people do with the time that is created?

If reporting becomes automated, what becomes more important?

If information becomes abundant, which skills become scarce?

These are questions of work design, not technology.

And they're likely to shape the future more than any individual AI tool.

I've noticed that many organizations approach AI as a productivity initiative.

How can we do the same work faster?

It's a reasonable place to start.

But over time, the more interesting question may become:

How should the work itself change?

Because increasing efficiency and creating value are not necessarily the same thing.

An organization can automate a task without reconsidering whether that task should exist in its current form.

It can reduce effort without improving outcomes.

It can increase output without increasing impact.

The organizations that benefit most from AI may not be the ones that automate the most work.

They may be the ones that rethink work altogether.

Not every task requires a human.

But not every task that can be automated should define how humans spend their time.

The future of work may not be defined by how many jobs disappear.

It may be defined by what remains after routine work is removed.

And that raises a question worth paying attention to:

As AI changes what humans can do, how should it change what humans are asked to do?