AI leads to layoffs, but OpenAI is hiring salespeople

Stephen Curry, Deep Tide TechFlow

Recently, a wave of AI-related unemployment anxiety has swept across the internet in both the East and West.

Block laid off 4,000 employees, with the CEO saying AI can do your job; Pinterest cut 15% of its staff to invest in AI; Dow Chemical laid off 4,500 people, citing increased automation…

In China, the situation is no different. NetEase was rumored to replace outsourcing with AI, iFlytek denied large-scale layoffs, and ByteDance was reported to optimize 20% of non-AI departments every six months…

According to statistics, in the first three months of 2026, global tech layoffs exceeded 45,000, nearly 10,000 of which were explicitly attributed to AI.

Against this backdrop, last Friday, the Financial Times reported that OpenAI plans to expand its staff from 4,500 to 8,000 by the end of the year.

3,500 new positions. A company making AI says it doesn’t have enough people?

Check out OpenAI’s careers page—while they are hiring engineers and researchers, another large portion of the listings are for roles like partner managers, enterprise sales, GTM (go-to-market) teams, and a new position mentioned in the report called technical ambassadorship, which translates to:

Technical ambassadors, specifically helping enterprise clients learn how to use AI.

So, OpenAI isn’t hiring people to make AI smarter; they’re hiring people to make others willing to pay for AI.

Winning clients beats winning models

ChatGPT has 900 million weekly active users, but most don’t pay.

Paid consumers, however, are still being served at a loss: the computing power cost per heavy user exceeds the $20 monthly fee. This year, revenue is projected at $25 billion, with an estimated loss of $14 billion.

Consumers drive traffic, but enterprise clients drive profit. And those enterprise clients are moving toward Anthropic’s Claude.

Ramp’s data shows that among companies that first purchased AI tools, Anthropic captured 73% of the market share. Ten weeks ago, that figure was split evenly between two companies.

Last December, Altman sent a “code red” memo to all staff, pausing all non-core projects like advertising and shopping assistants, focusing all resources on improving ChatGPT.

The trigger was Google Gemini 3 surpassing ChatGPT in multiple tests, but deeper anxiety exists on the enterprise side: Anthropic is embedding Claude into clients’ codebases and workflows, and once integrated, migration costs start to snowball.

Models can be iterated, but once clients leave, they don’t come back on their own. Winning clients requires more than AI suggestions; someone has to go knock on their door.

You can’t sell the shovel itself

AI can write code, handle customer service, and analyze data, but there’s one thing it can’t do:

Convince a company’s tech leader to sign an annual contract and buy from me.

For individual users, AI is just an app download—if they’re unhappy, they can uninstall anytime. For enterprises, it’s a different story. Data security reviews, internal process restructuring, system compatibility, employee training—all these hurdles can halt a project.

This isn’t something that can be solved by model scores; it requires someone sitting in the client’s conference room to push forward.

OpenAI seems to have realized this. They’re not just hiring salespeople; FT reports they’re negotiating joint ventures with private equity firms like TPG and Brookfield to help enterprises implement AI. The core of this business is still about sending people in.

Block’s story is telling the same thing.

Less than three weeks after laying off 4,000 people, the company started bringing some back. A design engineer was told they were “laid off incorrectly,” and a technical lead found that after the entire team was cut, no one could handle key operations, threatening resignation. Only then did the company rehire some staff.

Dorsey even hinted in the layoff letter: “We might have laid off some people incorrectly…”

AI has indeed caused layoffs anxiety, but if the main arteries of value creation are cut because of AI layoffs, that’s clearly overkill. Even in a company where the CEO publicly claims AI can replace most employees, there are still tasks AI can’t handle.

AI is best at replacing clearly defined tasks, but “convincing an organization it needs AI and helping it use it” is precisely something that can’t be clearly defined.

Every technological revolution has had people saying “selling shovels is the most profitable.” This round of AI is no different; the consensus is that infrastructure companies will be immune to wins and losses.

But OpenAI’s current situation shows that even if you produce the shovels, someone still needs to teach others how to use them. And that “teaching” process can’t be done with shovels alone.

Door-to-door sales, job security in AI anxiety

Looking at those laid off and those hired back together reveals a dividing line.

Among the 4,000 laid off at Block, a large portion were engineering and operations roles expanded during the pandemic—jobs that can be described in standard terms. OpenAI’s 3,500 new hires are mainly in sales, customer success, partner management—roles that can’t be easily documented in processes.

What OpenAI is doing is a classic: door-to-door sales.

Sending people to clients’ offices, listening to needs, integrating systems, monitoring launches. Whether called technical ambassadors or partner managers, in essence, it’s like the old O2O battles from ten years ago—Meituan sending people door-to-door convincing restaurant owners to install POS machines.

This approach isn’t unique to these two companies.

Shopify’s CEO told employees this year that if they want to hire more staff, they first need to prove AI can’t do the job. Klarna laid off 700 customer service reps two years ago, claiming AI was enough; last year, they quietly rehired some, with the CEO admitting they “moved too fast” on AI.

What’s the difference between those laid off and those rehired?

Jobs that can be cut share a common feature: their tasks can be broken down into clear inputs and outputs. Writing code, replying to tickets, generating reports—boundaries are clear, and AI excels at these.

Door-to-door sales are the opposite. Helping a financial client integrate AI into compliance systems or assisting a gaming company with content generation—no two projects are the same. The person on the other side is different, so the solution varies. This can’t be scripted into prompts.

AI isn’t eliminating all jobs; it’s redefining their value. Tasks that can be clearly described are becoming cheaper; those that can’t are becoming more expensive.

Companies that three years ago could change the world with a paper now need thousands of people knocking on doors one by one.

If you’re anxious about AI replacing you, the answer may not depend on your industry but on whether your work can be summed up in a single sentence.

The part that can be clearly explained is already less secure.