AI Should Have a Job Description

Over the past year, I've watched organizations rush to adopt artificial intelligence at an astonishing pace.

Some have achieved remarkable productivity gains.

Others have quietly discovered that simply purchasing AI doesn't automatically solve business problems.

One pattern keeps appearing.

Organizations begin with the technology instead of the problem.

The conversation often sounds like this:

"We have AI now. Where can we use it?"

I believe the better question is:

"What business problem are we trying to solve, and is AI the right tool for that job?"

That distinction matters.

Every Employee Has a Role

Imagine hiring a new employee.

On their first day you tell them:

"We don't have a job description. Just do whatever you think is useful."

It sounds absurd.

Every employee has:

A defined purpose. Responsibilities. Authority limits. Access controls. A supervisor. Performance expectations.

Without those things, the employee is almost guaranteed to create confusion.

Yet this is surprisingly close to how many organizations deploy AI.

AI is connected to internal documentation, emails, chat systems, customer records, and knowledge bases with only a vague expectation that it will somehow improve productivity.

That's not strategy.

That's experimentation.

AI Is Not an Employee Replacement

One trend concerns me more than any other.

Companies reducing staff because they believe AI can replace experienced professionals.

Unfortunately, what many organizations discover is that they didn't eliminate labor.

They eliminated experience.

The employees who left took with them years of accumulated knowledge, context, intuition, and professional judgment.

Those qualities don't exist inside an LLM simply because it has access to company documents.

Documentation contains information.

Professionals contribute reasoning.

Those are not the same thing.

Where AI Excels

I believe AI is exceptionally valuable when given a clearly defined role.

For example:

Summarizing large volumes of information. Identifying patterns. Drafting reports. Organizing knowledge. Suggesting alternative hypotheses. Accelerating repetitive administrative work.

These are tasks that augment human capability rather than replace it.

Where Humans Remain Essential

There are also responsibilities I believe should remain firmly under human control.

Accepting organizational risk.

Making legal or ethical decisions.

Declaring systems secure.

Approving recommendations.

Exercising professional judgment.

Those decisions require accountability, context, and experience that extend beyond pattern prediction.

A Better Way to Think About AI

Rather than asking,

"Where can we use AI?"

organizations might begin by asking:

What problem are we solving? Why is AI the right tool? What decisions is AI allowed to make? What information does AI actually need? Who is responsible for reviewing its work? How will success be measured?

These questions define a role.

And roles create accountability.

Final Thoughts

Artificial intelligence has extraordinary potential.

I believe it will become one of the most transformative technologies of our generation.

But its success won't be determined by how much work it replaces.

It will be determined by how effectively it augments human expertise.

Technology should increase human capability—not diminish human reasoning.

For me, the guiding principle is simple:

AI without a clearly defined role isn't strategy—it's experimentation.

How is your organization defining AI's role? Are you assigning it responsibilities, or simply giving it access?