AI can make a task disappear surprisingly quickly. That doesnāt mean youāre finished with it.
It often comes back as something somebody still has to review or correct. Models have improved, but in my experience, they still need checking.
Thatās why Cory Blumenfeld, the entrepreneur behind Taking My Time Back, uses a simple three-question test before handing work to AI.
In this guest piece, he explains where human judgement still matters when AI is doing more of the work. šš»
āThe AI told me to do this.ā
I hear that from clients and my own team more often than Iād like. My first response is usually: did you think about it? Did you actually read it?
The problem isnāt always the answer AI gave them. Sometimes the mistake is asking AI to make the judgement for them.
If you donāt know what good looks like, almost anything AI gives you can seem good enough. You need to understand the work well enough to tell it what you want and spot when it gets something wrong.
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The three-question test
I use AI every day. For repetitive work, it makes sense because it gives me more time to think. But thereās a phrase I keep coming back to: cheap delegation gets expensive.
The cost usually shows up later, when somebody has to fix the output or a customer notices the difference.
So before I delegate a task, whether itās to AI, a virtual assistant or somebody else, I think about three things.
1ļøā£ Does it involve emotion?
If the work depends on empathy or how somebody feels on the other end, it usually needs a person.
2ļøā£ Does it involve judgement?
If somebody needs to make a real decision, AI shouldnāt be making it for you.
3ļøā£ Is it repetitive and repeatable?
If the task is basically the same every time and doesnāt require judgement or emotion, give it to AI.
What I hand over
AI isnāt going to do my podcasts, but it can handle plenty of the work around them.
Across the team, Iād estimate we get back an hour and a half to two hours a day from repetitive work that didnāt need much thought in the first place.
After one of my calls, I want the transcript saved in Notion, turned into notes, summarised and used to draft a follow-up email.
A person used to have to know the call had ended and work through those jobs one by one. Now the workflow runs automatically, without me having to kick off each step.
The problem is that a bad automation can keep producing poor work every time it runs, and somebody still has to catch it.
Iāve seen this in outsourcing too. When somebody spends every day doing the same mindless task, theyāre not learning much from it. Thatās the sort of work Iām happy to hand over. Iām more careful with work built on years of experience.
Ford had been relying more heavily on automated quality systems, but executives werenāt getting the results they wanted. It brought in 350 veteran engineers to help find problems and improve the AI itself.
The review bill
At what point does reviewing work that AI created cheaply and quickly take longer than doing it properly in the first place?
Itās easy to skip that question until the review work starts piling up.
AI can save a lot of time, but some of that saving gets swallowed by keeping things working. A model update can break an automation or suddenly make old instructions less reliable.
That rework adds up. In one survey, 85% of employees said AI saved them 1ā7 hours a week, but 37% of the time saved went back into correcting, rewriting or adding missing context. Often, the clean-up falls to whoever notices the problem and has to sort it out.
Saving time doesnāt necessarily mean less work either.
I can take more calls because Iām not writing every summary myself, but those calls create more follow-up and give my team more clients to support.
AI lets the business take on more, but the workload doesnāt shrink on its own.
The time you save is easy to fill again, so you have to be deliberate if you want any of it to stay free.
Your nameās still on it
If something goes out under your name, itās still your responsibility, whether AI touched it or not. You still have to verify the information and decide whether the work meets your standard.
Air Canada learned that the hard way when its chatbot gave a customer incorrect fare information. A tribunal held the airline responsible for what the bot had told him.
With writing, I often start from a transcript because it keeps me close to how I actually speak. Then I might use AI to pull the information together or show me where 1,200 words can become 900.
If it helps me say the same thing more clearly and saves somebody time, great. I still decide whether the suggestion sounds right, and plenty of the time the original language is better.
Whatever AI does along the way, the person whose name is on the work still has to make the call. Thatās why I think judgement matters more as AI takes on a bigger share of the work.
When people become the premium option
I can already see it in content. Once it becomes cheap to produce something passable, a lot of it starts sounding the same. Work with a clear human voice stands out more.
I think customer service is going the same way. 87% of customers now say companies using generative AI for support still need to give them access to a human.
Klarnaās experience shows why that matters. Its AI assistant was doing the work of around 700 agents in 2024. A year later, its CEO admitted the cost focus had hurt quality. The company started hiring people again, with him describing human service as a VIP option.
When bots become standard, getting an actual person who understands the situation starts to feel more valuable.
Iām happy to automate aggressively, but Iām careful when the work depends on human judgement because thatās where cheap delegation tends to get expensive.
š¤ Cory Blumenfeld is a five-time founder with two exits and the writer behind Taking My Time Back, where he writes about building businesses that donāt depend on the founder for everything. Heās built teams of 70+ and now focuses on helping founders win back their time through better systems, people and AI. Connect with Cory on LinkedIn.
