For months I've been hearing from colleagues, clients, professionals, and friends who are frightened, or nearly paralyzed, by the arrival of AI in their professions.
The speed of the process is so dizzying that it awakens professional insecurities we didn't have until recently.
Artificial intelligence isn't just changing what we do. It's also transforming the way we think about our own value. The new fear isn't losing our job tomorrow, but ceasing to be needed the day after.
For a long time, the question in the face of a new technology was: "Will it replace me?" With artificial intelligence, that question has become more uncomfortable and more profound: "Which part of what I know how to do will still be valuable?"
That is where FOBO comes from: Fear of Becoming Obsolete.
It isn't only the fear of losing a job. It's something more intimate. It's the feeling that our skills, our knowledge, and even our experience could stop mattering. That what took us years to learn can be done, in a few seconds, by a tool anyone can use.
A student can ask an AI to explain a difficult concept using soccer examples. A professional can summarize a hundred-page report in a minute. Someone who has never written a line of code can build a simple app. Someone with no knowledge of music can compose a symphony. Someone with no design experience can generate a visually striking presentation or a disruptive video.
The question is no longer whether artificial intelligence can do some of our tasks. The question is what we do when those tasks stop being exclusively ours.
The fear isn't new, but the speed is
Every technological revolution produced similar fears. The steam engine threatened entire trades. The computer automated administrative tasks. The internet changed commerce, media, and the way we communicate. It took a decade or two for the executive secretary to practically disappear from the market. The same thing happened to toll booth workers: they had a decade of warning.
But artificial intelligence introduces a decisive difference: it doesn't automate only manual or repetitive work. It also steps into activities we associated with thinking: writing, analyzing, summarizing, translating, designing, programming, researching.
That's why the impact is so personal. For decades we built our identity around what we know how to do. "I'm an accountant," "I'm a journalist," "I'm a lawyer," "I'm a designer," "I'm a teacher." Now many of those professions are incorporating tools capable of doing an important part of that work in less time and, in some cases, at lower cost.
The problem appears when we confuse a task with our identity.
An accountant isn't just someone who enters data into a spreadsheet. A journalist isn't just someone who writes texts. A teacher isn't just someone who transmits information. A doctor isn't just someone who recognizes symptoms.
Technology can do some of those tasks. But we still need people capable of understanding contexts, asking relevant questions, taking on responsibility, interpreting nuance, and making decisions when there is no obvious answer.
From "knowing how to do" to "knowing how to decide"
For a long time, professional advantage lay in accumulating knowledge. Whoever knew more had more value. In a world where access to information is instant and machines can process it at high speed, that advantage begins to shift. Knowing how to answer isn't enough. You have to know what to ask. Producing a presentation isn't enough. You have to understand what problem it must solve. Generating ten ideas isn't enough. You have to recognize which one can work and why.
Artificial intelligence can write an email, but it doesn't always know whether it should be sent. It can propose a strategy, but it doesn't necessarily know an organization's history, its internal tensions, or the political cost of a decision. It can deliver a convincing answer, even when it's wrong.
Human value starts to concentrate somewhere else: judgment.
That judgment isn't an abstract skill or one reserved for a few enlightened people. It's built with experience, curiosity, critical thinking, and the capacity to learn. Also with something machines still can't fully replace: responsibility for the consequences.
An everyday example
Consider someone who works in customer service. Artificial intelligence can suggest responses, sort complaints, and detect patterns across thousands of conversations. That doesn't necessarily mean that person stops being needed. But their work can change.
Maybe they no longer have to answer every simple inquiry manually. Instead, they'll have to resolve the more complex cases, detect when a customer is truly frustrated, decide when to depart from the script, and find a solution that preserves the relationship.
The tool can make the work more efficient. It can also make it more demanding.
The same goes for a newsroom. An AI can summarize documents, suggest headlines, or write a first draft. But an opinion column isn't defined by its grammar alone. It's defined by a perspective, a hypothesis, a sensibility, and a stance toward the world. The machine can help us write. The question is whether we still have something to say.
The answer to FOBO isn't chasing every new thing
Faced with the fear of becoming obsolete, the most common reaction is to try to learn every tool. Courses, tutorials, and endless lists of apps appear. As if the solution were knowing every novelty before everyone else.
But that race has no finish line. Technology will keep changing. What seems indispensable today may be replaced tomorrow by a feature built into another tool. That's why, rather than learning specific apps, we need to develop capabilities that survive platform changes: asking better questions, working with others, communicating clearly, understanding complex problems, and learning continuously.
AI literacy will be important. But it won't consist only of knowing how to write a prompt to get an answer. It will also mean knowing how to verify it, challenge it, and recognize its limits.
Because a fast answer isn't necessarily a good answer. And a confident answer isn't necessarily a true one.
The most dangerous obsolescence
There is also a form of obsolescence that doesn't come from technology but from our attitude toward it. It's possible to become obsolete not because a machine does a task better, but because we stop asking ourselves questions. Because we accept the first answer. Because we stop talking with colleagues, observing customers, reading, experimenting. Because we delegate so much of our thinking that we end up losing the ability to decide. The real risk isn't that artificial intelligence thinks like a person. It's that people start thinking like a tool: automatically, predictably, and without their own judgment.
FOBO can be a warning sign, but also an opportunity. It forces us to review what value we bring and what kind of professionals we want to be. Not to compete with machines on speed, memory, or volume of output. That competition is lost before it starts.
Our task is different: to use technology to expand our capabilities without handing over what makes us accountable for our decisions.
In the age of artificial intelligence, the obsolete won't be those who don't know how to use every tool. The obsolete will be those who believe they have nothing new left to learn, ask, or contribute.
And perhaps that's the paradox: to avoid becoming obsolete, we'll have to go back to doing something deeply human. Learn.
By Ezequiel Kieczkier, founding partner and CEO of Olivia.