"What is enough?" A coaching question for the AI age.

AI promises to deliver abundance. Supernormal productivity gains, breakthrough innovations, a future of leisure with tech doing the heavy lifting. These claims have been advertised ad nauseum.

But abundance, unchecked by judgment, produces its own problems. Human exploits have already brought us irreversible climate change. Freedom from scarcity will invite even more casual wastefulness.

From digital gadgets, to fast fashion, to people and jobs, discard and replace is already becoming customary. AI could supercharge a spiral towards a disposable future.

Many will get dizzy, but leaders must stay sober.

Start by asking: What is enough?

1.         How much efficiency is enough?

AI’s productivity case is theoretically compelling. Faster processing, fewer errors, lower headcount costs. It all looks convincing when modelled in a spreadsheet.

But efficiency is a means, not an end. Leaders who treat it as the whole answer will miss what the numbers can’t tell you.

When a customer-facing process is automated, what emotional connection is lost with your followers? When tasks are transferred from people to AI, what cultural ballast leaves with the staff who go? 

Asking “what is efficient enough?” interrogates whether you have traded something precious for another soulless KPI.

2.         How much profit is enough?

AI can be a significant margin expander. The natural ambition is to capture as much of that upside as possible. But how much profit is enough?

Profit extracted at the expense of displaced workers, degraded customer experience, or under-invested safeguards is not a net gain. It is a transfer of cost onto others. You can call it “externalities,” even conceal it as “change management;” the harm does not vanish.

Rare is the leader who can articulate, as a matter of principle, how much profit is enough.  That requires a backbone and focus.

3.         Have you done enough for those whose roles are changing?

AI-driven job displacement rarely happens en masse or suddenly. It creeps up gradually: a role that is subtly narrowed, resignations that are not backfilled, a function relabelled as something unfamiliar. But the people affected can feel it before anyone can say “displacement.”

“Enough” here means more than a retraining budget or an outplacement service. It means genuine career conversations, time, and compassion that encourage hearts. This is where human judgment and empathy have the edge over AI.

4.         Do you know enough about the AI your team is deploying? 

You don’t need to be a data scientist. But you do need to be more than a nodding sponsor. When your team proposes an AI tool - whether for internal operations or customer-facing use - you should be able to confidently answer some basic questions: What data does it train on? What happens when it gets things wrong? Who is accountable for mistakes?

“Enough” here is not about technical mastery. It’s about wanting to know enough to ask the harder questions, to slow down a proposal so you can think, or to distinguish genuine tech capability from deference to star vendor branding. Leaders who outsource this type of judgment to their technical teams are not leading but abdicating.

5.         Have you done enough on AI risk?

Managing risk in AI means more than formulaic checklists and stress tests. Consequences that were not foreseen at launch become surprises when something goes awry. As AI evolves, new vulnerabilities are revealed.

Before trusting AI, leaders should ponder: Have you assessed how your AI systems might affect customers who are less digitally literate? Have you built in human override at points where the stakes are highest? Do you have someone - a real person - whom you trust to ask the awkward questions before they become embarrassing headlines?

With AI risk, “enough” is not a target. It is an attitude: healthily suspicious, genuinely humble, and willing to pause or reverse course when warranted.

A closing thought

“Enough” resists modern business’s bias for more - more speed, more scale, more optimisation. Asking “what is enough” is decidedly contrarian. It will invite strange looks, perhaps even derision.

And that is precisely why it is needed.

Because where’s the fun in going with the flow?

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I am a leadership coach. I help leaders and organisations succeed through good leadership practices. Because good leadership matters.