What happens if, or arguably, when our reliance on AI becomes a crutch.
As we increasingly encourage employees o use AI to write, research, analyse, brainstorm and solve problems, we effectively help people work faster and more efficiently. Win-win, right? But with AI becoming deeply embedded into everyday work, another question deserves our attention.
Are we developing employees who are highly capable of working with AI, but increasingly incapable of working without it?
It is an uncomfortable question because the benefits of AI can no longer be ignored. Few people would argue that employees should return to doing everything manually simply to prove they can. We no longer insist accountants perform every calculation without a spreadsheet or writers abandon spellcheck in the interests of character building.
However, there is a difference between using technology to extend capability and becoming so dependent on it that the underlying capability begins to disappear.
What happens when AI always goes first?
Increasingly, AI is becoming the starting point rather than the editor, fact checker or proof reader.
Need an idea? Ask AI.
Need to solve a problem? Ask AI.
Need to write something? Ask AI.
Need to understand something? Ask AI to explain it.
While it can be enormously useful, it begs the question: if AI always produces the first idea, first draft or first interpretation, then employees may spend less time doing the difficult thinking that develops expertise in the first place.
The thought process forces us to organise ideas, identify gaps in our thinking and decide what we actually mean. Similarly, struggling with a problem can be frustrating, but it is often through that struggle that we learn how to solve the next one.
If AI removes too much of the struggle, what else might it remove with it?
You need skills to check the machine
The irony is that effective AI use requires many of the same capabilities that over-reliance on AI could weaken.
To identify an inaccurate answer, you need knowledge.
To recognise a weak argument, you need critical thinking.
To improve a poor draft, you need writing skills.
To question an AI recommendation, you need enough expertise to know if something is a bit off.
Our love affair with AI creates a potential capability problem. If employees increasingly rely on AI to perform the work through which those skills were once developed, who will have the expertise to check AI’s work in the future?
The answer is not to use less AI
The solution is not to ban AI or insist employees complete tasks manually for the sake of it. Rather it is to use AI deliberately. Sometimes AI should go first. Other times
the human should. Sometimes employees should use AI to challenge their thinking rather than replace it. Instead of asking, “Give me the answer” they might ask, “What have I overlooked?” or “Challenge my reasoning.”
Organisations need to think not only about where AI can save time, but where human effort remains important because the process itself develops capability.
Build capability, not dependency
The most AI-capable workforce will not necessarily be the one that uses AI for everything. It will be the one that knows when to use it, when to question it and when to think independently. The end goal should not be to create employees who cannot work without AI.
It should be to create employees whose capabilities are strengthened by it.
At GAPS Professional Writing, our workplace AI training focuses on developing employees who can work with AI without surrendering the judgement, critical thinking and professional expertise required to work effectively without it.