When an executives says layoffs were driven by AI, what exactly is the AI doing that removes the need for those humans?
Here’s some dog-walk speculation.
Decks, Meetings, etc.
All the prep work around The Meeting. Things like: the agenda, slides, the pre-read, notes during the meeting, and followup tracking. There’s the careful synthesis of who said what so it can be presented in a different room to a different set of people for the next round of synthesis. In any sufficiently large organization this is - what? - 10% to 20% of knowledge-worker time? Maybe more.
Maybe when companies lay off people, they are relying on AI to do a lot of this work. Not perfectly, but maybe good enough versus paying teams of people to do it. Or maybe AI does it even better than humans!
You can imagine an SVP with no VPs and just a handful of individual contributors. All of the corporate data is connected to a chat application and the SVP just talks with the AI. They might then have a brief meeting with the handful of people there to discuss what they think and, of course, what their AI chat sessions said. There’s probably some MCP Servers. You could imagine some markdown files (skills and plugins in the Claude Cowork sense) forming the foundation of it.
Contra to this is the notion that the deck is going to be skimmed for 90 seconds anyway. The “real” work is done by people informally talking with each other to “pre-wire” and “socialize” the deck. But, maybe you throw in some Agent-2-Agent to have your AI talk to their AI(s).
The measuring middle
“The vast majority of those we laid off last week were measurers,” he wrote. He defined “measurers” as those in middle management, finance, legal, internal auditing, and revenue recognition. Matthew Prince, Cloudflare CEO
It turns out, executives who lay off staff tell us, there’s a lot of people who just measure and track things. Part of this is getting the deck together and doing The Meeting, above.
What does the measuring middle do? Figuring out what to measure, then measuring it, then talking to the people being measured about those measurements. Daily status. Quarterly briefs. Career conversations. Maybe even the board deck! The annual strategy and budgeting planning. Analysis about new businesses to enter, etc. Each year, of course, you need to revisit how you measure. And when a new executive comes in, you need to introduce a new measuring system and then take the time how to apply the new measuring system to how you’re working.
Why pull six VPs into a strategy offsite when each board member can just talk to Claude about the state of the business and get a tailored brief? And, of course, each of those six VPs has teams of people who get their deck and talking points ready, and then respond to the other VPs.
AI can do most of that, the Cloudflare CEO says:
Tireless, independent, efficient and available, AI systems can now measure an organization with a level of objective detail and precision that was previously impossible even for the best employees.
This feels like where most of the AI-attributed tech layoffs actually land. Maybe? Project managers, program managers, chiefs-of-staff, the layer of “I run the cadence.”
Reporting
AIs can probably do all those dashboards and detailed reports that need to be executed into short emails. This adjacent to the meeting stuff but distinct. This is the long-promised thing of actually knowing what is happening in your business day to day, not just project-status.
Real “what changed this week and what does it mean” reporting that the BI team has been promising since 2008. AI is finally making that cheap enough to do once you hook up chat apps to all those data lakes.
Operations and paperwork
Anyone who has filed a tax return knows how much of organizational life is filling out a PDF and routing it somewhere. Corporate life is full of filling out PDFs (and, even more horrifically for some, ERP web forms): POs, invoices, the paperwork to open or close a bank branch, the corporate-law boilerplate for every non-trivial action a company takes. One could imaging SEC files. Have the AI do it. Have a person review it. Adjacent: the lower tiers (or upper!) of corporate law, which is a lot of “here’s the standard M&A doc, change these seven fields.” There must be a lot of “prepare the paper work to send to the person/organization” that goes on.
Corporate communications
When you need to tell the people in the organization something, instead of spending time with humans to come up with what to say and how, and then to actually say it in various mediums…just have an AI do it all.
Again, an executive sits at an AI chat app and talks with it, finally saying, “that looks good, send an email to all employees with this exciting update.”
You could even train on the executive’s voice and visual and send out an AI generated video.
This could likely be extended to all communications (see marketing and design below).
Programming
Programmers are well covered. But it also includes architects, QA, project managers and measurers, product managers who decide what features and fixes get in, security people, even ops people who are monitoring and fixing problems in production.
The executive just logs into the chat app and says “hey, how are the servers?” Or, “hey, can you add the ability to sell our tires in Cyprus?”
New AI features
The business adds new features to its existing software and, thus, business. We saw a lot of this driven by humans during COVID where banks had to do new types of loan applications, retailers had to support curb-side pickup and return, restaurants needed scheduling and COVID paperwork checking, etc., etc. Humans did this insanely fast - with the help of lot of “digital transformation” of how they did software and platforms they used to run apps.
Now, imagine if new features were instead driven by an executive’s imagination and they could just sit in front of their AI chat app and say “wouldn’t it be cool if we had a new type of corn dog?”
Customer service
Mostly automatable, with an asterisk. In my experience, the reason humans were ever required for customer service is that eventually a decision has to be made or an action has to be taken. The old “automated customer service” felt like just keyword search against a knowledge base, which is why everyone hated it and immediately typed “agent” eighteen times into the chat. When you call customer service, it’s usually because you want something to happen, not just learn about how the business functions and its thoughts on you. For example, you want to cancel a credit card, change a flight, etc.
The new version can actually do the thing - issue the refund, reschedule the order, close the account - and that changes the math. I mean, assuming you trust its judgement - but the cost of the errors might be much less than the cost of humans, and speeding up the process might include customer service that, you know, a few first class ticket given out here and there is no big deal.
Diagnostics
From the mechanic figuring out why a jet engine is acting weird to the platform engineer figuring out which of the seventeen services in the request path is causing the latency spike in equity trading. Maybe AI is good at “given all this state, where is the problem.” Hopefully.
Planning
An executive sits down in front of an AI chat app and says: how much ground beef should we order for next quarter? How much steel? How many people should staff the night shift? Should we open that new branch in Cleveland?
This used to be spreadsheets plus a twenty-year veteran’s pattern-matching. You want ground beef to Rotterdam next quarter, not a kilo more or less. But, it’s August, so you know even though they say they can handle a tripling in ground beef, you know the dock workers might mostly be on vacation.
Just unzip a few markdown files into .claude, OAuth to that ERP system, and ship that meat. No need for so many humans.
Marketing
There’s also marketing, design, graphic stuff - why go through the trouble of generating copy, infographics, brochures, and even signs? It’s not great at writing, but if you just want to get a point across quickly, or explain something, it’s definitely cheaper and faster than a human.
Instead of hiring professionals, I use AI a lot for video and other content production. Descript is amazing for this kind of thing and it’s loaded with AI.
I was in León recently and noticed that even the churches there were using art from ChatGPT (the old anime looking stuff), and a lot of signage at restaurants too.
In general: one person doing the work of three
One person can now do the work of 3+ people. Each employee can now get things done faster (doing one or more of the above), so they can use the 40 hours a week to do more work. This is “productivity”: you are paying less for the same output. You can also pay less and/or the same amount for even more output. That’s kind of like “productivity plus”!
If one person can do the work of 3 people, you either get rid of two people if you want to take on the risk of (a) there is no new work, (b) that person stays and has good enough availability between sickness, vacation, and leaving the job…or you get rid of one person, retaining a “backup human.”
Maybe the AI is the “backup human” too!
What this list has in common
The categories above are almost all white-collar coordination work. Meetings, measuring, reporting, paperwork, communicating, deciding what to decide. The layer of work that grew enormously over the last thirty years as companies got bigger, more matrixed, and more globally distributed. Work whose product is a document another human reads so they can produce a document another human reads.
The classic comparison is one of those black and white pictures of a bunch of clerks in an office that are replaced by a spreadsheet.
Some people like to imagine that AI cannot reduce “manual” work, from plumbing to nursing, radiology, and doctoring. But, you’ve got robots (one day, we’re told - I saw last week that someone has made advances in folding clothes), and if you can take a picture of a leaky pipe and have AI tell you how to replace it, maybe less plumbers too. Of course, getting a plumber to come instantly is often difficult, so maybe we don’t have enough plumber supply. Until robots advance, I think you still need humans to build houses, cook food, cut your hair (definitely straight razor your neck!), etc.
This meeting could have been a chat session
To day-dream more, think about any case where you’d say “this meeting could have been an email,” and that’s likely a good candidate. That’s a start, but there’s clearly there’s lot more.
What have you come across?