For a long time, the internet rewarded production.
Post more. Publish faster. Ship content. Fill the feed. Write the update. Make the deck. Produce the report. Send the email. Create the image. Record the clip. Generate the campaign. Output became a kind of proof that work was happening.
AI is changing that bargain.
When machines can produce drafts, images, code, summaries, plans, and synthetic voices in seconds, the scarce skill is no longer merely making something. It is knowing what is worth making. It is knowing what good looks like. It is knowing when the output is plausible but wrong, polished but hollow, efficient but misdirected.
In other words, taste becomes a superpower.
Taste is often misunderstood as personal preference. “I like this” or “I don’t like that.” But in professional life, taste is more rigorous. It is informed judgment. It is pattern recognition sharpened by experience. It is the ability to sense that a paragraph sounds impressive but says nothing, that a chart hides the real question, that a product feature solves an internal desire rather than a customer problem.
AI can generate options. Taste decides.
This matters because AI lowers the cost of first drafts. That is useful. A blank page can be intimidating, and AI is very good at giving us something to react to. But when first drafts become cheap, editing becomes more valuable. Direction becomes more valuable. Standards become more valuable.
The World Economic Forum has highlighted the growing importance of judgment-oriented work as AI adoption spreads, noting that human judgment becomes more important when AI tools enter the workplace. Its Future of Jobs work has also emphasized the continuing importance of analytical thinking and evolving skill needs as technology reshapes labor markets.
That should reassure us, but not too much.
Judgment does not automatically survive automation. It must be practiced. One of the subtler risks of AI is cognitive offloading: the habit of outsourcing not only effort but thought. A 2026 study on critical thinking and AI use found a mixed pattern. AI can support learning and efficiency, but overreliance may reduce patience for sustained effort and weaken reasoning habits depending on how people use it.
That finding feels intuitively right. AI can be a tutor or a crutch. It can widen your thinking or narrow it. It can challenge your assumptions or launder them into polished prose.
The difference lies in the human posture.
A weak AI user asks, “Can you do this for me?”
A stronger AI user asks, “Show me three approaches, explain the tradeoffs, identify the risks, and challenge my assumptions.”
The strongest AI user asks, “What am I missing?”
The future belongs to people who can interrogate outputs rather than merely accept them.
This applies across fields. In journalism, AI can summarize documents, but a reporter still needs news judgment. In law, AI can draft clauses, but a lawyer must understand consequence and nuance. In medicine, AI can surface possibilities, but clinicians must weigh context, patient history, ethics, and uncertainty. In business, AI can produce strategies, but leaders must decide what is realistic, differentiated, and humane.
Even in creative work, taste becomes more important, not less. When everyone can generate a logo, a song snippet, a video concept, or a blog post, the question shifts from “Can this be made?” to “Should this exist, and why would anyone care?”
That is an uncomfortable question. It cannot be answered by scale.
The irony of AI abundance is that it may make human restraint more valuable. The person who says “no” to mediocre output may become more useful than the person who generates endless variations. The editor, curator, strategist, teacher, critic, designer, and thoughtful manager all gain importance in a world drowning in plausible material.
But taste is not magic. It can be developed.
Read deeply. Compare examples. Study failures. Ask why something works. Seek feedback from people with standards. Learn the history of your craft. Practice explaining your decisions. Build domain knowledge. Notice when AI gives you the average answer, then push beyond it.
Organizations should train for this too. AI training should not only teach employees which buttons to press. It should teach verification, critique, ethical reasoning, domain judgment, and escalation. A company that gives everyone AI tools without strengthening judgment is not becoming smarter. It is becoming faster at producing uncertainty.
There is a lovely possibility here. Perhaps AI will force us to rediscover the value of the human things we had started to neglect: attention, discernment, curiosity, context, responsibility, and care.
The machines may give us more output than we know what to do with.
Our job will be to decide what deserves to become real.
Sources
World Economic Forum on judgment work in the age of AI.
World Economic Forum Future of Jobs 2025 overview.
Research on AI use and critical thinking.
BCG on AI reshaping jobs and the need for judgment, oversight, and coordination.