Posted on 08/29/2026 9:48:14 PM PDT by SeekAndFind
A recent report from Stanford reviewed the latest employment data and found that, so far, AI has not resulted in large scale job destruction. Meanwhile, new hiring data from the Economic Times reveals that AI is actively fueling unprecedented job creation, with AI skills now powering nearly two-thirds of new Global Capability Center hiring. Together, these recent dispatches from the front lines of the labor market point to a calming reality: the much-dreaded AI job apocalypse hasn't materialized as a sudden extinction event.
The (sometimes buried) lede: AI is delivering real impact, and it is broadly changing the nature of work. But disruption is not a new phenomenon. The economy has always dismantled old work to build new work. What determines whether this evolution feels like progress or collapse isn't just the number of jobs lost, it's the speed at which that loss hits the labor market.
In 1995, Bill Gates circulated a memo titled "The Internet Tidal Wave," calling the web the most important computing development since the IBM PC. If the internet was a tidal wave, artificial intelligence is a tsunami. It is arguably the biggest advancement in computing since the Turing machine. Yet, from a distance, it's difficult to appreciate the speed of this wave, leading many to wonder when the broader economy will truly feel its impact.
To put this in context, we must understand the historical pattern already visible in the labor market. Combining decades of data from the U.S. Bureau of Labor Statistics and the Federal Reserve yields a remarkably consistent story of overlapping curves: job loss and job creation. Over the last two decades, nearly 20 million U.S. jobs vanished in disrupted sectors. Over the same period, total payrolls grew by 25.7 million. That equates to roughly 1.3 new jobs for every one destroyed. Classic examples include jobs in video rentals (-98.9%) and word processing (-83%) which largely vanished, but new work sprung up at the same time in areas like data processing (+54%) and warehousing (+260%) to support the digital economy.
The data also reveals an early signal that separates an absorbable decline from a brutal collapse: the disruption half-life, or how long an occupation takes to lose half its peak employment. Across the largest technological disruptions of the last few decades, the median half-life is about 10 years. Fast disruptions, like photo processing, take one to five years. Typical disruptions take eight to 13 years. And time is the ultimate shock absorber. When the economy transitions over ten years it feels like progress rather than a fast collapse, because it gives older workers time to retire and younger workers time to prepare.
If we track the most AI-exposed occupations-customer-service reps, IT support, telemarketers-since modern LLMs arrived in 2022, the early data is measured. After three years the current disruption looks closer to "typical" than a fast collapse, even before discounting the effects of offshoring, automation, and post-COVID corrections. This is Amara's Law playing out in real time: we tend to overestimate the effect of technology in the short run and underestimate it in the long run. The dire early warnings have given way to more cautious rhetoric. In 2025, Anthropic's Dario Amodei warned AI could erase half of entry-level white-collar jobs within five years. By 2026, he and OpenAI's Sam Altman are emphasizing productivity, economic growth, and the continued demand for human labor.
However, looking solely at total employment numbers masks a dangerous structural threat. Current evidence does not foretell the end of human labor, but AI is quietly breaking the mechanism by which we create experienced workers.
Software engineering is the canary in the coal mine. By most aggregate measures, employment looks stable; unemployment held at 4.2% in June 2026, and groups like the Yale Budget Lab find no clear AI effect yet on exposed occupations' absolute job totals. But the composition is shifting underneath our feet. Per AP and Oxford Economics, junior developer postings are down roughly 40% in four years. Employment for 22-to-27-year-old computer and math grads has fallen 8% since 2022, even as older grads in the same fields have edged up. This same erosion is surfacing wherever entry-level work once meant routine tasks: paralegals, junior analysts, and first-line support.
The paradox is that these industries keep growing even as their entry-level doors narrow. The BLS still projects software developers and QA analysts to grow 15% through 2034. But that projection relies on a pipeline that turns juniors into senior talent-precisely the pipeline now being choked off.
The reason lies in the nature of the work. Software development is a process of judgement and accountability: deciding what to build, executing it, and owning the result. AI is fluent at the middle layer-the well-specified, routine coding that once served as a junior's apprenticeship. But it remains far weaker at the judgment required on either side. The tasks AI automates are precisely the ones juniors were hired to learn on.
This is not merely an academic concern; it is a capital allocation problem. Misjudge the speed of disruption and you risk premature layoffs followed by a scramble to rehire, or funding the transition years too late, leaving you with a critical talent shortage when the leadership pipeline runs dry.
The challenge of the next decade isn't surviving the end of work. It is training the next generation of experts when the traditional paths to apprenticeship no longer exist. And businesses are beginning to realize this new reality as demand for AI continues to grow. IBM is tripling its entry-level hiring, redesigning those roles around the oversight of AI and systems thinking rather than cutting them. Rebuilding the entry-level on-ramp is now a competitive imperative.
Junior roles are not charity; they are talent capex. If AI creates more work than it destroys, companies will still need people who know how to run it, judge it, and fix it. AI may be the broadest technology yet, but that breadth is its best reason for optimism. A general-purpose technology seeds new work across every sector. The firms that recognize this, protect their entry-level pipelines, and keep training now are the ones who will own the senior labor market later.
Joe Bertolami is the Co-Founder and CTO at Clifton AI, an agentic context engine for investment research. Previously at Snap, Google, and Microsoft, with a couple of startups in between. He holds an M.B.A. from the University of Washington and likes using AI to write code, stories, and music, which he posts at https://www.bertolami.com.
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"We're reducing staff made unnecessary due to implementing AI."
This is a straw man argument.
Nobody said it would happen in the next two weeks. Come back in five years.
Indians brought over to the USA are literally writing the code for the top AI companies. The Claude team is 70% imported Indians.
I wouldnt feel safe yet. It will probably be an evolutionary process, as they figure out how to make AI more capable.
'Amazon Abandons Checkout-Less Tech That Secretly Used 1,000 Indian Employees Watching Cameras'
https://thedeepdive.ca/amazon-abandons-checkout-less-tech-that-secretly-used-1000-indian-employees-watching-cameras/
"Amazon is doing away with the “Just Walk Out” checkout-less technology at its Fresh grocery stores... Instead of relying solely on artificial intelligence and advanced sensors, as Amazon had claimed, the Just Walk Out system depended heavily on manual labor from over 1,000 workers based in India... These remote “cashiers” monitored video footage from stores to track what items customers removed from shelves before generating receipts hours later."
AI is going to produce a huge jobs boom, not mass unemployment
Related: I highly recommend the book “Building AI Agents”. It’s first chapters do a great job of explaining the internal workings of AI. That content alone is well worth the price to me.
Who authors that book?
What i can’t figure out is why we need so many data centers.
We are already using AI..
I’m a recent convert to this idea, instead of relying on news articles and propaganda about AI, I decided to do some research myself into the subject.
In the matter of a couple of weeks, it dawned on me that AI will not be the job apocalypse that a lot people think, it will be an explosion of new and different jobs.
I’m not a technical novice, I spent nearly 40 years in IT tech support, starting out supporting mainframes and then the last nearly 20 years programming Cisco Systems routers, switches and Voice systems for major fortune 100 companies.
For no logical reason I created an account with Claude AI from Anthropic, using just the free tools, I had Claude AI writing python code, creating spreadsheets, and working a number of different projects.
I’ve since signed up for a paid subscription of $17/month for one year. I have 4 projects under construction, all using fairly sophisticated python code and embedding it into excel spreadsheets, creating YouTube videos, cloning my voice, etc.
I’ve barely scratched the surface of what Claude AI can do and I’ve never been a python developer before using this product, I would consider myself a moderate to advanced user of Microsoft Excel.
What Claude AI allows someone to do is advance way beyond their current technical skills and create their own niche jobs and careers, things that would not have been possible before.
My experience as well
AI won’t kill jobs moving forward, because the demographics of a retiring population with a limited labor supply makes it almost an impossibility.
However, many American corporations are being run by stupid people that think there is an unlimited amount of labor in the future & the “churn & burn” model will remain viable.
“It Won’t.”
AI will create many job opportunities for people in the future.
Here’s a comforting thought. Tens of thousands of call takers in India and the Philippines lost their jobs due to AI replacing them. Soon, hundreds of thousands of them will have lost their jobs. The AI systems now respond to calls, even down to imitating their bad English accents.
The only people who will lose their jobs and remain unemployed are those who refuse to help themselves, with the AI tools that exist today for little to no money, anyone who with moderate intelligence can create incredible things with the tools.
Yes, people likely will lose their jobs, but AI will create wonderful opportunities for those who choose to take them.
Before I retired, I was primarily an IT contractor, basically a gun for hire, I always had a plan B in case the contract got cancelled or I lost my job prematurely.
I constantly keep my IT certifications up to date, I kept my resume up to date, and I continued to seek out training wherever possible.
In today’s world, I would be learning as much as possible about the AI tools that are out there and how to effectively use them. I would become a subject matter expert in my current job, adapting the AI tools to more efficiently do my current job and enhance my resume for future jobs.
That’s exactly what has happened in banking. Its like the Great Recession Part II. All last year and this year has been awful. Yes, there haven’t been mass layoffs but they’re hardly hiring anybody new and they’ve almost completely stopped hiring consultants.
The article reads like it was written by a Crypto-Bro, who wants to branch out.
Notice this article talks about “global” job availability. With the US home to most of the leaders in the AI space, you’d think they’d focus here first.
The reality is that capex on datacenter construction is outstripping demand. They’re trying to build so much in advance that the opex books are taking a big hit, but no one’s really buying the capacity they’re trying to produce.
Big Tech entities are laying off thousands of American workers and a week later are applying for the same number of H1Bs. Fire 10,000 American workers making $150K, you clear $1.5B in opex. Then turn around and hire 15,000 H1Bs making $30K, you just cleared up $750M in opex to build datacenters. Magic!
The devil is in the details. Don’t look at the employment numbers. Look at the number of employees at the big tech companies. They’re saying, “Oh, Amazon’s staffing numbers are relatively unchanged.” Well, yeah, if you fire 10,000 domestic workers and hire 15,000 foreigners in their place, guess what? It looks like Amazon is growing.
If anything, AI makes indian programmers viable. That’s the bad news.
The good news is AI makes good programmers better. I haven’t written a line of code now in almost 4 months and basically guide the AI agent to generate the code. I’m also making large block changes and features (under my watchful eye) in weeks compared to months.
Downside - I’m losing understanding of the system. I know how it works but because I’m skimming over the specifics I couldn’t tell you with certainty what’s happening at certain points and have to rely on the same AI to analyze what my code is doing.
It’s a different world out there.
Same thing that happened to the 5G end of life event.
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