Working with AI
AI should give you your evenings back, not take your team’s jobs
The question I get asked most is some version of “does this mean I let someone go?” The honest answer is that AI replaces tasks, not people, and which tasks it takes is a decision you make. The technology does not decide it for you.
In a small business the realistic outcome is not fewer people. It is the same people spending less of the week on work that never needed a human, and more of it on the work that only a human can do. That is the whole argument, and there is now decent evidence behind it.
34%
for the newest staff
In a study of more than 5,000 support agents, AI assistance lifted output by 14% on average, but by around 34% for the least experienced workers. For the most experienced, the effect was minimal.
Brynjolfsson, Li & Raymond, Quarterly Journal of Economics, 2025. Generative AI at Work →
Read that distribution carefully, because it is the opposite of the replacement story. The tool did not make the best people redundant. It brought everyone else closer to them. The researchers found it worked by spreading the practices of the strongest performers across the team, helping newer staff move down the experience curve faster than they would have alone.
If you have ever spent months getting a new starter to the point where you trust them with the phone, that finding should mean something to you.
What AI is genuinely good at, and what it is not
The useful dividing line is not clever versus simple. It is repeatable and low-judgement versus variable and high-stakes.
Answering a call at 8pm and taking the details. Acknowledging an enquiry within seconds so the person does not ring your competitor. Sending the reminder that stops a no-show. Chasing the quote that went quiet. None of that requires judgement. All of it requires somebody to be available at a moment nobody is available.
Quoting a complex job. Reading a customer who is upset about something that is partly your fault. Deciding whether to take work on when the schedule is already tight. Training an apprentice. That is the work that needs a person, and no amount of automation changes it.
19%
On tasks outside what the AI handles well, consultants using it were 19% less likely to reach the correct answer than those working without it. The tool did not just fail to help. It actively misled.
Dell’Acqua and others, Harvard Business School with BCG, 2023, field experiment with 758 consultants. On tasks inside its range the same group completed 12.2% more work, 25.1% faster, at higher quality.
That study is the one to keep in mind, because it puts a number on the thing vendors never mention. AI is not uniformly helpful. Pointed at the wrong work it makes people measurably worse, and confidently so. Picking the right tasks matters more than picking the tool.
The replacement question, answered properly
It would be dishonest to say automation never costs anyone a job. At large scale, in businesses where a role is entirely repetitive processing, it clearly can.
But that is not the situation most Australian trades and service businesses are in. The typical operation I speak to is not overstaffed. It is a handful of people doing more than they can reasonably fit in a week, with the owner absorbing whatever is left over at night. There is no surplus to cut. The constraint is time, not headcount.
In that setting, automating the admin does not produce a redundancy. It produces capacity. The person who was spending an hour a day on reminders and callbacks is now doing the work you actually hired them for, and the growth that was always going to require another pair of hands can happen before you can afford them.
The direction it goes is a leadership decision, not a technical one. The same system that frees up five hours a week can be used to give someone their afternoons back or to justify cutting their hours. That choice sits with the owner, and it always did.
Where the hours actually come from
It is worth being concrete, because “saves you time” is the emptiest phrase in this industry. Here is a modelled week for a small operation.
Modelled example: admin hours in a typical week
| Returning 20 enquiry calls, 4 min each | 80 min |
| 15 follow-up messages, 3 min each | 45 min |
| 12 reminders and confirmations, 2 min each | 24 min |
| Inbox triage, 30 min a day | 150 min |
| Total per week | ~5 hours |
| Across 48 working weeks | ~239 hours |
Modelled figures, not a benchmark, and no system removes all of it. Substitute your own. Roughly 239 hours is a bit over six working weeks a year, spent on work that produced no revenue and required no expertise.
Six weeks. That is not a productivity statistic, it is a fortnight of annual leave you did not take and a month of evenings you did not get.
The part nobody puts in the brochure
Most writing about business automation stops at the money. The part that matters more, in my experience, is what an always-on business does to the person running it.
It is the phone checked at 9pm because an enquiry might have come in. The Sunday afternoon spent on invoices and callbacks. The low background hum of holding a list of people you have not got back to yet. None of that appears in a P&L, and all of it accumulates.
I spent enough years in the Air Force to have watched what sustained operational tempo does to good people. Capability is not just what your team can do on a good day. It is what they can keep doing, week after week, without something giving way. A business that only functions because the owner never switches off is not a strong business. It is a fragile one with a single point of failure, and that point of failure is a person.
Automating the after-hours response is not a productivity play in that light. It is the difference between a business that can run for a decade and one that burns out its best person in three years.
Where to start, and what to keep human
If you take one thing from this, make it the sequence. Automate the work that is high volume, low judgement and time critical, in that order:
- First contact. The enquiry that arrives when nobody can take it. Phone answering, missed-call text-back, and the inbox, because these are pure timing problems with no judgement in them.
- The chase. Reminders, confirmations, and the follow-up on a quote that went quiet. Consistent, tedious, and the first thing a busy person drops.
- The forgotten list. Past customers nobody has contacted in two years, because that is work that will otherwise simply never get done.
And keep with people: the quoting, the difficult conversations, the judgement calls, the relationships. Not because a machine could not attempt them, but because the jagged frontier research suggests that is precisely where it would make you worse.
“I have never met an operator who wanted more hours in the business. They wanted fewer hours doing the parts of it that never needed them in the first place.” Jared Theisinger, Founder & Director, Clearline AI
Common questions
- Will this replace my staff?
- It replaces tasks, not people, and which tasks is your call rather than the technology’s. Most businesses we work with are not overstaffed, they are out of time. Automating admin in that situation creates capacity rather than redundancy. If you wanted to use it to cut hours instead, you could, but that would be a decision you made, not an outcome the system forced.
- Does AI actually make people more productive, or is that marketing?
- There is real evidence. A study of more than 5,000 support agents published in the Quarterly Journal of Economics found a 14% average lift in issues resolved per hour, rising to around 34% for the least experienced staff. The mechanism was interesting: it spread the working practices of the best performers to everyone else.
- Where does AI make things worse?
- Outside the work it handles well. A Harvard and BCG experiment with 758 consultants found people using AI on tasks beyond its capability were 19% less likely to get the right answer than people not using it at all. That is why choosing the right tasks matters more than choosing the tool.
- What should a small business automate first?
- First contact, because it is a pure timing problem and it is where the money leaks. Then reminders and follow-up. Then the dormant database. Leave quoting, difficult conversations and relationship work with your people.
- Will my customers know they are dealing with AI?
- Our systems do not claim to be human when someone asks directly, and anything sensitive is escalated to a person rather than answered automatically. The aim is a fast, useful, accurate response, not a trick.
Part of a series on where trades and service businesses lose work: what a missed call costs, why calling back does not recover it, the cheapest leads you already paid for, and the inbox is the leak you cannot see. More about why Clearline exists.
References
- Brynjolfsson, E., Li, D. and Raymond, L.R. (2025) “Generative AI at Work.” The Quarterly Journal of Economics, 140(2), pp. 889–942. Study of more than 5,000 customer support agents. academic.oup.com/qje/article/140/2/889. Working paper version: NBER w31161.
- Dell’Acqua, F., McFowland III, E., Mollick, E.R., Lifshitz-Assaf, H., Kellogg, K., Rajendran, S., Krayer, L., Candelon, F. and Lakhani, K.R. (2023) Navigating the Jagged Technological Frontier: Field Experimental Evidence of the Effects of Artificial Intelligence on Knowledge Worker Productivity and Quality. Harvard Business School Working Paper 24-013, with Boston Consulting Group. papers.ssrn.com/abstract=4573321
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