Are Humans Becoming Wiser?

By Mukadam Olaitan Ajetunmobi, Human Intelligence Transformation Architect™

The strategy deck was impressive.

Fifty polished slides. Market analysis. Competitor profiles. Financial scenarios. Recommended actions. It had been created with artificial intelligence in less than an hour.

Then someone in the meeting asked three simple questions.

Which assumptions have we verified?

Who could be harmed if this recommendation is wrong?

Who will take responsibility for the final decision?

The room became quiet.

There were more answers on the screen than ever before—but less certainty that anyone in the room had truly thought.

This scene is becoming familiar. AI drafts our proposals, summarizes our meetings, interprets our data, recommends our next move and sometimes gives us the words with which we explain ourselves to other people. Work becomes faster. Output becomes cleaner. The pressure to keep up becomes stronger.

Yet beneath the efficiency is a question few organizations are asking:

Are we using artificial intelligence to extend human capability—or to escape the human responsibility to think, feel, judge and choose?

That is not a question about technology alone.

It is a question about who we are becoming while using it.

What the evidence shows

Artificial intelligence is not advancing slowly. Stanford’s 2026 AI Index reports that several frontier models now meet or exceed human baselines on selected PhD-level science, multimodal-reasoning and competition-mathematics benchmarks. Organizational AI adoption reached 88 percent.

Yet the same report describes a “jagged frontier”: models can perform brilliantly on some demanding tasks while failing surprisingly basic ones, and responsible-AI measurement is not keeping pace with capability.

The lesson is not that AI is either miraculous or useless.

The lesson is that capability is not the same as reliability.

A 2025 Microsoft Research and Carnegie Mellon study examined 319 knowledge workers and 936 examples of AI-assisted tasks. Higher confidence in generative AI was associated with less reported critical thinking, while greater confidence in one’s own ability was associated with more.

The researchers also found that critical thinking does not disappear; it shifts toward verifying information, integrating responses and stewarding the task.

This study does not prove that AI makes people less intelligent. It offers something more useful: a warning that the way we use AI can change where—and how much—we think.

Employers already recognize the human side of this challenge. In the World Economic Forum’s Future of Jobs Report 2025, analytical thinking remained the leading core skill, while resilience, leadership, creative thinking, curiosity and lifelong learning continued to rise in importance.

The OECD likewise identifies both the benefits of workplace AI and risks that include loss of agency, bias, discrimination and lack of transparency.

The documented evidence is clear: AI capability and adoption are advancing rapidly, productivity benefits are real, and human-centred capabilities remain essential.

The deeper conclusion that follows is my interpretation:

We are not facing only a technology gap. We are facing a Human Intelligence Gap™.

The Human Intelligence Gap™

The Human Intelligence Gap™ is the widening distance between what technology enables us to do and what we are prepared to do wisely.

We can generate more options without becoming better at choosing.

We can access more information without becoming more perceptive.

We can communicate more frequently without becoming more relationally present.

We can predict behaviour without understanding the human being behind the data.

We can automate a decision without resolving who is morally accountable for its consequences.

This gives us an essential distinction:

AI produces capability. Wisdom provides direction.

Capability asks, What can be done?

Wisdom asks, What should be done, for whom, at what cost and toward what future?

An answer may be factually plausible and still be wrong for this person, this context or this moment. A recommendation may optimize a metric while damaging trust. A message may be grammatically perfect while emotionally empty. A decision may be efficient while quietly violating the values an organization claims to protect.

AI can process patterns from the past.

Human beings must decide which patterns deserve a future.

That decision requires more than technical literacy. It requires self-awareness, emotional regulation, perception, ethical reflection, relational understanding, imagination and responsibility.

These are not decorative “soft skills.”

They are governing capacities.

Without them, AI does not remove human weakness. It amplifies it.

A fearful leader can use AI to rationalize control.

A biased system can make exclusion look objective.

An impatient manager can automate communication that needed courage and presence.

An insecure professional can accept a polished answer because questioning it would expose what they do not know.

The danger is not simply that AI may produce errors.

It is that human beings may stop noticing when an answer deserves resistance.

The WISER Decision Filter™

To close the Human Intelligence Gap™, we need a deliberate pause between machine output and human action.

I call this original tool the WISER Decision Filter™. It is not presented as a clinical or scientific instrument. It is a practical Human Intelligence Transformation™ framework for preserving judgment when AI influences a consequential decision.

W — What is the real decision?

Do not begin with the prompt. Begin with the purpose.

What are you actually trying to decide, create or improve? What is at stake? A vague human question does not become wise simply because AI gives it a polished answer.

I — Inspect the evidence and assumptions

What in the output is verified fact, reasonable inference, prediction or invention? Which sources matter? What assumptions did the system make because you failed to state them?

Fluency creates confidence.

It does not create truth.

S — See the whole human system

Who benefits? Who carries the risk? Whose voice is absent? How might this decision affect dignity, trust, opportunity, workload or belonging?

Data can describe people without fully seeing them.

E — Examine emotion and incentive

What is shaping your willingness to accept this answer—fear, urgency, ambition, ego, fatigue or convenience? What does the organization gain by believing it? What might you prefer not to confront?

The person evaluating an answer is never psychologically neutral.

R — Retain responsibility

Who owns the final decision? Can you explain it in your own words? Are you willing to stand before the people affected and account for its consequences?

If no human being owns the decision, the process is incomplete.

A five-minute practice

Use the filter on your next meaningful AI-assisted task.

Before opening the tool, write three sentences:

1. The decision I am making is…

2. The people or outcomes affected are…

3. The assumption I may be getting wrong is…

Then use AI to expand options, challenge your reasoning and reveal blind spots.

Do not ask only for the best answer. Ask for the strongest counterargument, the missing stakeholder, the conditions under which the recommendation would fail and the evidence that would change the conclusion.

Finally, pass the result through WISER and write the decision in your own words.

This small discipline changes your relationship with the tool. You are no longer a passive recipient of generated certainty. You become the conscious author of a responsible choice.

The real human advantage

The future of work will not be secured by rejecting AI. Nor will it be secured by adopting every tool as quickly as possible.

The real advantage is partnership without surrender.

Let AI handle speed, scale, comparison and iteration. Let the human being provide purpose, context, empathy, moral imagination and accountability.

And where AI becomes capable of assisting with those functions, do not abandon them. Strengthen your capacity to evaluate how they are being performed.

For every capability you outsource, choose a human capacity you will continue to practise.

If AI drafts, you verify and restore your voice.

If AI recommends, you test consequences.

If AI predicts, you examine dignity and fairness.

If AI accelerates, you pause before commitment.

If AI gives an answer, you remain responsible for the question.

The defining divide of the coming decade may not be between people who use AI and people who do not.

It may be between those who become increasingly dependent on machine capability and those who use that capability to become more discerning, adaptive, creative and deeply human.

AI is getting smarter.

Our task is not to compete with its speed. Our task is to become wiser in our use of power.

Do not merely upgrade the technology. Upgrade the human behind it.