Client Portal
In September 2026 the ABC published a piece on young Australians pushing back against artificial intelligence. A 19-year-old university student told the ABC that AI "stops me from being able to use my brain independently". A Melbourne school student described a friendship group united in avoiding it. A 17-year-old pointed at the environmental cost. An arts graduate admitted she worries that opposing AI openly could hurt her job prospects, which tells you how loaded the topic has become.
The numbers in the piece say this is not a fringe position. Nearly 80 per cent of Australian students used generative AI in their study last year, according to research the ABC cites, and a Minderoo Foundation study found almost two thirds of Australians believe AI is moving too fast. Read those together: the generation using these tools most heavily is also the one most uneasy about them. They are not rejecting AI out of ignorance. They are rejecting it from experience.
Their objections are governance questions in casual clothes
Strip away the generational framing and look at the list. Does relying on AI weaken my own thinking? That is a capability question. Who had a say in the rules? That is consultation and accountability. Is the output biased? That is quality control. Can someone misuse it against me? That is acceptable use and consent. What does it cost the environment? That is a procurement question. We spend our working week helping businesses put exactly these questions into AI policies, and here is a generation asking them unprompted.
Not every concern is equally solvable inside a small business, and we are not going to pretend the environmental one has a tidy per-seat answer. But none of them deserves an eye-roll, because every one of them will eventually be asked inside your business by a staff member, a candidate or a customer.
The "cheat code" problem is real, and it is a business problem
The sharpest concern in the piece is dependency: AI as a cheat code that does the thinking for you. We made the same argument from a stage three weeks ago in The Good, The Bad and The Bot: AI makes good people better, it does not make average people expert. If you already know what good looks like, it amplifies you. If you do not, it helps you produce confident rubbish at speed.
For a business, that cuts deeper than study habits. Judgement is built by repetition. The accountant who can glance at a reconciliation and feel that something is off got that instinct by doing hundreds of them. If your juniors never draft the letter, never price the job and never trace the fault themselves, they never build the judgement that makes AI safe in their hands later, and in ten years you have nobody who can check the machine. So decide which work must still be done by hand while someone is learning, and where AI acts as a reviewer rather than the author. That is not being anti-AI. That is succession planning for expertise.
Two attitudes, one workplace
The most telling passage in the article is a father and son on opposite sides. The father, who runs a business, sees AI as an economic essential he cannot afford to ignore, and credits it with work he could never have funded otherwise. His teenage son and his friends want nothing to do with it. Give it a few years and that pair is a manager and a new hire in the same office.
Both directions land on the same problem: mixed attitudes to AI with no shared rules. An owner mandating tools a sceptical graduate quietly avoids is a governance failure. So is staff quietly using assistants an anxious owner has banned. What fixes it is not one side being right, it is deciding things together: which tools are approved, what information can go into them, where a human must review, and who owns the outcome. We wrote a practical starting point in It is time to govern your team's AI use, and the young people in the ABC's story hand you the one improvement that costs nothing: they resent rules written without them, so write yours with the team in the room.
What we would actually do
- Write the AI policy with your team, sceptics included. Adoption follows consent, and the objections above are the agenda for that meeting.
- Name what AI must not author. Work a person is still learning from, and anything that leaves the business without human review.
- Answer the four questions. What AI tools are actually in use, what information goes into them, what guardrails exist, and which person is accountable.
- Be ready to say why and where you use AI. Candidates and customers now ask, and "we have not thought about it" is the only bad answer.
Scepticism is not the enemy of good AI adoption. Unexamined enthusiasm is. The pushback the ABC describes is, underneath, a demand for the things we keep coming back to on this blog: judgement protected, rules agreed together, accountability named, and humans kept in charge of the bot.