I build automation tools for bookkeepers and accountants. The thing I keep seeing firsthand is that automation doesn't eliminate the job - it eliminates the boring part of the job, and then the job description shifts.

Before our tools: a bookkeeper spends 80% of their time on data entry and transaction categorisation, 20% on actually thinking about the numbers. After: those ratios flip. The bookkeeper is still there, still needed, but now they're doing the part that actually requires judgment.

The catch nobody talks about is the transition period. The people who were really good at the mechanical part (fast data entry, memorised category codes) suddenly find their competitive advantage has evaporated. And the people who were good at the thinking part but slow at data entry are suddenly the most valuable people in the room. That's a real disruption for real humans even if the total number of jobs stays roughly the same.

I think the "AI won't take your job" framing misses this nuance. It's not about headcount. It's about which specific skills get devalued and how quickly people can retool. In accounting at least, the answer is "slowly" because the profession moves at glacial speed.

You’re describing task reallocation, but the bigger second-order effect is where the firm can now source the remaining human judgment.

AI reduces the penalty for weak domain context. Once the work is packaged like that, the “thinking part” becomes far easier to offshore because:

- Training time drops as you’re not teaching the whole craft, you’re teaching exception-handling around an AI-driven pipeline.

- Quality becomes more auditable because outputs can be checked with automated review layers.

- Communication overhead shrinks with fewer back-and-forth cycles when AI pre-fills and structures the work.

- Labor arbitrage expands and the limiting factor stops being “can we find someone locally who knows our messy process” and becomes “who is cheapest who can supervise and resolve exceptions.”

So yeah, the jobs mostly remain and some people become more valuable. But the clearing price for that labor moves toward the global minimum faster than it used to.

The impact won’t show up as “no jobs,” it is already showing up as stagnant or declining Western salaries, thinner career ladders, and more of the value captured by the firms that own the workflows rather than the people doing the work.

> automation tools ... eliminates the boring part of the job, and then the job description shifts.

But the job had better take fewer people, or the automation is not justified.

There's also a tradeoff between automation flexibility and cost. If you need an LLM for each transaction, your costs will be much higher than if some simple CRUD server does it.

Here's a nice example from a more physical business - sandwich making.

Start with the Nala Sandwich Bot.[1] This is a single robot arm emulating a human making sandwiches. Humans have to do all the prep, and all the cleaning. It's slow, maybe one sandwich per minute. If they have any commercial installations, they're not showing them. This is cool, but ineffective.

Next is a Raptor/JLS robotic sandwich assembly line.[2] This is a dozen robots and many conveyors assembling sandwiches. It's reasonably fast, at 100 sandwiches per minute. This system could be reconfigured to make a variety of sandwich-format food products, but it would take a fair amount of downtime and adjustment. Not new robots, just different tooling. Everything is stainless steel or food grade plastic, so it can be routinely hosed down with hot soapy water. This is modern automation. Quite practical and in wide use.

Finally, there's the Weber automated sandwich line.[3] Now this is classic single-purpose automation, like 1950s Detroit engine lines. There are barely any robots at all; it's all special purpose hardware. You get 600 or more sandwiches per minute. Not only is everything stainless or food-grade plastic, it has a built-in self cleaning system so it can clean itself. Staff is minimal. But changing to a product with a slightly different form factor requires major modifications and skills not normally present in the plant. Only useful if you have a market for several hundred identical sandwiches per minute.

These three examples show why automation hasn't taken over. To get the most economical production, you need extreme product standardization. Sometimes you can get this. There are food plants which turn out Oreos or Twinkies in vast quantities at low cost with consistent quality. But if you want product variations, productivity goes way, way down.

[1] https://nalarobotics.com/sandwich.html

[2] https://www.youtube.com/watch?v=_YdWBEJMFyE

[3] https://www.youtube.com/watch?v=tRUfdBEpFJg

The desktop PC was the same - everyone said that it was going to wipe out jobs, when the main thing it wiped out was filing cabinets.

AI commentators seem to overlook that one of the primary functions of capitalism is to keep people in busywork: what David Graber called Bullshit Jobs. So AI is going to automate most of the bullshit away but the bullshit employees will keep working, because there wasn’t much need for them in the first place.

I recently did a contract at medium sized business with a large retail and online business that had a CFO and several accountants / bookkeepers. You're describing a situation where that CFO only needs two or three accountants and bookkeepers to run the business and would lay off two or three people.

It IS about headcount in a lot of cases.

Another component or view of this is that automating the rote work is "eliminating the boring parts" (I love this and have worked extensively on this) but it is also eliminating the less cognitively demanding work.

Once you have automated extensively, all of the remaining work is cognitively demanding and doing 8 hours of that work every day is exhausting.

I frame the shift more like this:

Systems engineering is an extremely hard computer science domain with few engineers either interested in it, or good at it.

Building dashboards is tedious and requires organizational structure to deliver on. This is the bread and butter of what agents are good at building right now. You still need organization and communication skills in your company and to direct the coding agents towards that dashboard you want and need. Until you hit a implementation wall and someone will need to spend time trying to understand some of the code. At least with dashboards, you can probably just start over from scratch.

It's arguably more work to prompt in english to an AI agent to assist you in hard systems problems, and the signals the agent would need to add value aren't readily available (yet?!). Plus, there's no way systems engineers would feel comfortable taking generated code at face-value. So they definitely will spend the extra mental energy to read what is output.

So I don't know. I think we're going to keep marching forward, because that's what we do, but I also don't think this "vibe-coded" automated code generator phase we're in right now will ultimately last. It'll likely fall apart and the pieces we put back together will likely return us to some new kind of normal, but we'll all still need to know how to be damn good software engineers.

You’re not taking into account that a successful bookkeeper may have hired someone like a new grad to take the drudgery off of their hands and now they can just do it themselves.

I'd imagine that when the 80% of less productive time is automated, the market doesn't respond by demanding 80% more output. There's just 20% as much work either making this a part time job or more likely a much smaller workforce as the number of man*hours demanded by the market greatly reduces.

> The bookkeeper is still there, still needed, but now they're doing the part that actually requires judgment.

The argument might be fundamentally sound, but now we're automating the part that requires judgement. So if the accountants aren't doing the mechanical part or the judgement part, where exactly is the role going? Formalised reading of an AI provided printout?

It seems quite reasonable to predict that humans just won't be able to make a living doing anything that involves screens or thinking, and we go back to manual labour as basically what humans do.

I'm not very familiar with the field on a practical basis.

What parts of the job require judgement that is resistant to automation? What percentage of customers need that?

If the hours an accountant spends on a customer go from 4 per month to 1, do you reckon they can sustainably charge the same?

(I work in house handling the tax function.)

If AI tools worked, they would eliminate the bookkeepers. Their job is data entry and validation.

But bookkeeping is extremely important. Bad bookkeeping has killed more companies than bad accounting. Without proper books, the accounting, finance, and tax teams are just cosplaying.

>> The thing I keep seeing firsthand is that automation doesn't eliminate the job - it eliminates the boring part of the job, and then the job description shifts.

No, not necessarily. There are different kinds of automation.

Earlier in my career I sold and implemented enterprise automation solutions for large clients. Think document scanning, intelligent data extraction and indexing and automatic routing. The C-level buyers overwhelmingly had one goal: to reduce headcount. And that was almost always the result. Retraining redundant staff for other roles was rare. It was only done in contexts where retaining accumulated institutional knowledge was important and worth the expense.

Here's the thing though: to overcome objections from those staff, whom we had to interview to understand the processes we were automating, we told them your story: you aren't being replaced, you're being repurposed for higher-level work. Wouldn't it be nice if the computer did the boring and tedious parts of your job so that you can focus on more important things? Most of them were convinced. Some, particularly those who had been around the block, weren't.

Ultimately, technologies like AI will have the the same impact. They weren't quite there yet, but I think it's just a matter of time.

Yeah bro, its been three years. We are just beginning. We will replace the vast majority of professional service workers in 10 years including lawyers as Ai shifts to local and moves away from the cloud.