The Very Way We Describe People Is About to Change

The very way we describe people is going to change.

Until now, we have described people mainly by affiliation and occupation.

Which company they work for, which department, what rank, what role.

“I work in marketing at a large company.”

“I'm a startup developer.”

“I make content at an ad agency.”

“I do electrical work at a construction company.”

Like that.

In industrial society, this was fairly natural.

For an individual to be highly productive, the organization called a company was necessary. The company owned the factory, the company owned the equipment, and the company held most of the capital, distribution, and information. The individual entered it, took on a role, and that role became the person's economic identity.

But in the AI era, I believe this standard will steadily weaken.

AI is rapidly expanding the range of means of production available to an individual.

Researching, organizing, analyzing, developing, designing, writing, processing data, communicating with customers, automating repetitive work — one individual can now handle a vast array of tasks at far lower cost.

Then the reason to define a person only by their role inside a company shrinks too.

Instead, the more important question may become this:

“What does this person turn into what?”

And we can name those functions anew.

For example, I think I could describe myself like this.

Problem design.

Someone who listens to a customer's complex, ambiguous problem, finds its essence and gives it structure, and turns it into a solution that actually works.

What comes to me is a “problem,” and what I produce is “structure and a solution.”

Problem → structure → solution.

Some people are great at content.

They find, within a customer's experience, problems, knowledge, and products, the stories people will care about. Then they turn them into writing, video, images, and messages, creating attention and trust.

Experience and knowledge → content → attention and trust.

Some people are great at analysis.

They read numbers and data scattered in complexity, find the meaning inside, and convert it into forms people can actually judge and act on.

Data → interpretation → decisions.

Some people are great at sales.

They discover needs people haven't yet clearly articulated, connect the right people with the right solutions, and turn those relationships into actual transactions.

Sales is not simply the act of selling goods.

Latent need → relationship → trust → transaction.

Some people are great at product.

They take vague ideas or requirements and turn them into services and products people can actually use.

Idea → design → product.

Some people are great at technology.

They understand the features people want or the problems they face, and implement them as technical systems that actually work.

Requirements → technology → a working system.

Some people are great at connecting.

They link people who didn't know each other, bundle different resources and abilities, and make new collaboration happen.

People and resources → connection → collaboration and opportunity.

And this is not a story for knowledge workers only.

Some people carry field skills.

Electricians, plumbers, mechanics, welders, carpenters, facilities specialists — using their hands and bodies, long experience and honed technique, they solve the problems of the physical world.

They make broken machines move again, reconnect severed power, fix ruptured pipes, raise buildings, repair cars, machine metal.

What comes to them is the physical world's breakdowns and problems, and what they produce is a physical environment that works again.

Physical problem → skilled technique → normal condition.

Some people are great at care.

They watch over those who need someone's sustained attention and help — children, the elderly, patients — and make that person's daily life, safety, and quality of life better.

Need and discomfort → care → stability and quality of life.

Some people are great at education.

They explain knowledge and skills others don't understand, at that person's level, until it becomes ability the learner can use alone.

Knowledge → understanding → ability.

Some people are great at operations.

They untangle the snarl of people, schedules, resources, and tasks, and turn it into a system where work keeps running.

Chaos → process → stable operations.

In the end, these are words we already use.

Sales.

Content.

Analysis.

Product.

Technology.

Operations.

Education.

Field skills.

Connection.

Care.

Problem design.

But what matters going forward, I think, is understanding these words not as mere job titles but as the names of the value-transforming functions a person performs in the world.

Nor does one person need only one function.

Someone can be great at sales and content at once.

Someone can do technology and product at once.

Someone can hold field skills and also teach well.

I can hold together the ability to see problems as structures and the ability to build them into real systems.

That is, a person becomes not a single title but a combination of multiple functions.

We used to say:

“That person is such-and-such at such-and-such company.”

Soon we may say:

“That person is strong at problem design.”

“That person is strong at sales.”

“That person is strong at content.”

“That person is strong in field skills.”

“That person runs operations brilliantly.”

These expressions are far more essential.

Which company the person currently belongs to can change.

Rank changes.

Projects change.

But what a person is good at discovering, and what they can transform into what value — that is the asset that accumulates in them.

In the AI era this difference will grow especially large.

Because if AI increasingly assists with peripheral work — research, document drafting, design, development, data processing — people can concentrate on the core function they do best.

Then the reason everyone must be employed long-term at a single company shrinks as well.

When a customer's problem arises, the person strong at problem design comes in.

When content is needed, the person strong at content comes in.

When customers must be found, the person strong at sales comes in.

When numbers must be judged, the person strong at analysis comes in.

When a product must be built, the people strong at product and technology come in.

When field equipment must be fixed, the field-skills specialist comes in.

An operations specialist may come in to connect them all and keep the loop turning.

And AI, in between, assists with research, records, analysis, production, development, communication.

They need not all be employees of the same company.

They connect around the problem, contribute their functions, and create value together.

Then organizational competitiveness changes too.

Not how many employees you have,

but how precisely you can connect the needed function at the needed moment.

Not who employs more people,

but how fast you can combine the right people, AI, technology, and capital for the problem.

That is what becomes important.

And the customer, too, may not be someone outside this network.

Customers provide problems.

They provide knowledge from the field.

They validate products.

They provide new ideas.

Sometimes they even connect new customers and experts.

Running my own business, I already see this.

My customers are buyers, but they are also collaborators who define problems with me and build new solutions together.

Then the boundaries blur — employee and customer, inside and outside the company, producer and consumer.

The organization of the future may be less a structure that owns people and more one that connects the different functions people carry.

Industrial society gave people seats.

Which company.

Which department.

Which rank.

Which role.

But in the AI era, people may come to define their own functions.

And so the most important question for a person may become:

not “What is your job?”

Not that,

but “What are you good at?”

More precisely:

“What that enters the world do you transform, and into what value?”

If sales — needs into transactions.

If content — experience into attention and trust.

If analysis — data into judgment.

If education — knowledge into ability.

If field skills — breakdowns into working order.

And if, like me, you see problems as structures —

complex problems into working solutions.

Perhaps the first thing the AI era demands we redefine is not AI,

but the definition of what a human being is here to do.