I’ve been holding some interviews lately for an intern role.

It became clear that more than one candidate was using AI to respond to my questions in real-time.

Rather than generating their own answers, they were relying on AI - at this point, there was more eye scanning than eye contact.

All the cover letters and tasks submitted ahead of the interviews had the same issue: They were completely devoid of personality and original thinking.

It would be easy to put this down to age or inexperience. But that’s not true. The same pattern shows up well beyond early career candidates. There is a growing comfort with output that is average, as long as it arrives quickly and requires minimal effort to produce.

I am not sure when average became acceptable. The consequences are more significant than they first appear.

Let’s not blame the tools themselves

Used well, AI is amazing. It accelerates research, sharpens a draft, and handles repetitive work that used to consume hours. That is a great advantage, and dismissing it entirely misses the point.

The issue is what happens when AI becomes a substitute for thinking rather than a support for it.

Generating an answer before forming an opinion, or an idea, means skipping the part of the process that actually builds the best output and ultimately, outcome.

I’m seeing the same thing show up in how businesses approach their marketing:

• Strategies built from templates rather than real audience understanding
• Content that reads like it could have come from any business in any sector
• Outreach that was pinged out on scale, hoping for a 1% response rate

Average output, produced efficiently, is still average output.

What AI should actually be doing

The thinking that goes into understanding a market, defining an audience, and deciding what a business wants to stand for over time is human work. It requires real commercial understanding and the kind of judgement that comes from experience and attention.

What can be accelerated is everything that follows once that thinking is done.

• Researching a market or sector quickly and thoroughly
• Testing different angles on a message before committing to one
• Building out an execution plan once the strategic direction is set

Used at that stage, with strong inputs and a human eye on the output, AI is a genuine asset.

Getting back to thinking

Strategic thinking needs nurturing, as does creative problem-solving and an instinct to challenge a brief, question assumptions, or make a connection that has not been made before.

These skills develop through practice, through working on problems without easy answers, through forming views and defending them, but occasionally being wrong, which is where you learn the most.

If the default response to any challenge is to generate an answer rather than think through one, those instincts do not develop.

Returning to those interviews…the candidates using AI throughout, I believe, were doing so because no one (me included) had clearly made the case that the thinking and a connection with me was the point, not the output.

What to do differently

If any of this resonates, a few things worth considering:

• Before using AI, form your own view first: Even a rough one. Use the tool to refine and pressure-test, not to replace the initial thinking
• Ask the question AI cannot answer for you: what do you actually want the audience to think, feel, and do as a result of this? That answer has to come from you
• Review AI output critically: The default quality is average. Your job is to push it past that before it goes anywhere near a client or a public channel
• Invest in the habits that build instinct. Read widely, have real conversations, form opinions on things and write them down. These are the inputs that make strategic thinking possible
• Protect relationships: pitches, proposals, follow-up conversations are human on both sides of the coin.

Average is just not good enough. If you care enough, you’d be sure of that too.