There is a serious argument being made in Singapore right now: AI will not affect workers evenly, so the policy response cannot be a blanket one. It has to be targeted, and it has to be fair.
Kok Ping Soon, chief executive of the Singapore Business Federation, has made the argument carefully, and he brings numbers. Graduates in full-time permanent employment within six months fell from 87.5% in 2022 to 74.4% in 2025. Graduates receiving no job offers at all more than doubled, from 4.1% in 2023 to 8.5% in 2025.
He names who is exposed: junior and mid-level professionals in finance, law, professional services and software development — the entry-level research, basic coding and analysis work. His phrase for the risk is the one worth remembering: "the career ladder will be weakened at the bottom."
And a counterweight most coverage skips. A Ministry of Trade and Industry study found that early AI adoption correlated with higher firm revenue and higher total employment — not immediate job losses. The firms that moved early grew. That is worth holding onto before anyone concludes AI means shrinking.
All of that is true at the national level. Almost none of it helps you on Monday morning, because you are not running a country. You are running a company where one person does the invoicing, the customer chasing and the stock count, and you cannot restructure the labour market — you can only decide what happens to her role.
In a small business, jobs are not the right unit
This is where the national framing breaks down.
In a large organisation there is a data entry team. AI arrives, the team shrinks. That is the story everyone tells.
In a 20-person company nobody is a data entry clerk. Your operations person spends maybe 40% of her week on things a system could do without her — retyping orders from email into the system, checking one screen against another, chasing the same five customers, rebuilding the same report. The other 60% is judgment: deciding what to do when a shipment is late, knowing which customer will accept a partial delivery, spotting that an order looks wrong before it ships.
The exposed thing is not her. It is those tasks. And the difference matters enormously, because it changes what you are deciding. You are not deciding whether to keep her. You are deciding what she does with 40% of her week back.
That is a much better decision, and most owners never frame it that way because the public conversation trained them to think in headcount.
"Just and targeted" applies inside your company too
The argument for a fair national transition is that the burden falls unevenly, so support should be aimed at the people carrying it.
Same is true in a business of thirty people, and it is entirely within your control.
Some of your team will be fine. They already work in ways where the tools help them go faster. Others — often the longest-serving, often the ones whose value is precisely that they remember everything — are the most exposed, because their advantage is the thing a system replicates best.
Those are the people who will quietly resist the new system, and they will be right to, because from where they stand it looks like it is aimed at them. If you do not deal with that directly, the project fails. Not through sabotage. Through a hundred small reasons why the old way was easier this week.
Deal with it directly and something else happens: the person who held all the knowledge becomes the person who configures the rules, checks the exceptions and trains everyone else. Their status goes up, not down. I have watched that conversion work many times, and I have watched projects die because nobody had the conversation.
The distinction worth stealing: cognitive vs embodied
Kok makes a split that almost nobody else does, and it is the most useful idea in the piece for anyone running a physical business.
Cognitive AI is the software kind — it reads, drafts, summarises, analyses. It substitutes for desk work, which is why it hits junior professional roles hardest.
Embodied AI is robotics — it moves things. And his argument is that Singapore should accelerate it, deliberately, in sectors that cannot find workers. He even proposes differentiated foreign worker levies to push it along.
For a warehouse, a workshop or a kitchen, that is the opposite of a threat. The labour shortage is the binding constraint on your growth, and this is the category of automation that eases it. Same word, "AI", pointing in two completely different directions depending on whether your bottleneck is desks or hands.
So when you read that AI is coming for jobs, ask which kind. If your constraint is that you cannot hire enough people to move product, embodied automation is on your side.
Our take: automate the transactions first, and be honest about why
There is a sequencing point here that gets lost in the AI excitement.
The repetitive work in a small business — retyping, matching, chasing, reporting — mostly does not need AI. It needs a system that captures data once and reuses it. That is ordinary ERP and workflow automation, it is well understood, it is predictable, and it is where nearly all the hours are.
AI is genuinely useful on top of that: drafting, summarising, forecasting from clean history, spotting anomalies. But it is the second step, not the first, and pointing it at a broken process just gets you wrong answers faster.
So the honest plan is: automate the transaction work, give people the hours back, and put those hours into the work that needs a human — customers, suppliers, quality, the exceptions. Then tell your team exactly that, in those words, before you start. Not as reassurance. As the actual plan, with what each person will be doing afterwards.
The businesses that handle this badly announce efficiency and let everyone draw their own conclusions. The ones that handle it well decide first what people will do with the freed time, and say so on day one.
Pick your most experienced operations person. What could she do with one extra day a week — and have you ever asked her?
Read Kok Ping Soon’s original opinion piece.
Put a number on the hours
The Cost of Manual Work Calculator takes three inputs and tells you what the re-typing, checking and chasing costs you every year — and how many full-time salaries those hours add up to.
Originally published at The Gantry on 7 September 2026.
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