Artificial Intelligence Has Not Replaced People’s Jobs, and Cannot – A Survey
We debunk the AI CEO's arrogant, self-serving and destructive hype ...
Audience: Unemployed persons, job seekers, HR staff, decision makers, equity stakeholders, and senior leadership
"In God we trust, all others must bring data."
- Attributed to W. Edwards Deming
Contents
Executive Summary
Introduction
Part 1: No Evidence of AI Replacing White-Collar Jobs
Part 2: Three High-Profile AI Replacement Failures
· Klarna: Customer Service Catastrophe
· Forward Health: Healthcare’s AI Misadventure
· Olive AI: Back-Office Breakdown
Part 3: Scholarly Evidence of Augmentation, Not Replacement
Conclusion: Shattering the Myth
Footnotes
· LinkedIn
· Substack
Update (23.08.2025):
The Commonwealth Bank of Australia (CBA) has reversed a controversial decision to replace 45 customer service jobs with AI technology. The financial institution admitted to the publication Information Age that the "initial assessment that the 45 positions in the Customer Service Direct business were not necessary did not adequately take into account all relevant business considerations".
The bank is not the first company to reverse the replacement of human workers with artificial intelligence.
Executive Summary
We have seen it ourselves: predictions by AI CEOs and others, who should know better, that AI is coming for practically everyone’s jobs; this during a time of great uncertainty and suffering by job seekers. Mass layoffs by big companies, falsely blamed on AI, have proliferated; as of July 2025, at least 806,000 souls.
Regrettably, many people, particularly the unemployed, fervently believe the former, and many more are victims of the latter. Little can be done about layoffs that have already happened, but we can and have researched what is slowing down hiring, and put to rest the false attribution, stated or implied, that AI adoption has caused the massive layoffs.
In this brief, we bring plentiful data, and show that:
1. Rumors of AI-generated layoffs are almost entirely imaginary; they just haven’t happened, mostly since AI totally lacks common sense
2. Companies that have tried have failed, some are now out of business as a direct result of misplaced reliance on AI
3. Professional scientists who study AI almost uniformly believe it has value as augmentation or amplification of human workers, but reject the notion of AI replacement of human workers; not only that is hasn’t happened, but additionally that current AIs cannot replace humans.
Introduction
The hype around artificial intelligence (AI) replacing human jobs has reached fever pitch, with some tech CEOs and pundits proclaiming a future where machines dominate white-collar work. The narrative is seductive: AI, particularly large language models (LLMs), will sweep away accountants, writers, analysts, and more, leaving humans obsolete.
Here, we cut through the nonsense. The reality, backed by rigorous evidence, tells an entirely different story. AI hasn’t replaced people’s jobs, at least not yet, and not in the way the doomsayers claim. This article surveys the data, shatters the myth of an AI job takeover, and highlights the severe limitations of LLMs in replacing human workers.
We’ll explore five credible sources that find no unambiguous cases of AI replacing white-collar jobs, three high-profile failures of companies that tried and failed to swap humans for AI, and scholarly research showing that AI augments, rather than replaces, human work. Most also believe that current AI technology cannot replace human beings.
Far from being a job-killing juggernaut, AI’s track record is a humbling lesson in its shortcomings. The technology is still in its infancy: we debunked the AI hype cycle more than a year ago, and drew our own, red-dished line showing our guess as to where the technology actually stood; if anything, we were optimistic.
Part 1: No Evidence of AI Replacing White-Collar Jobs
The fear of AI wiping out white-collar jobs is pervasive, but where’s the proof? A dive into credible, independent sources reveals a striking absence of verified cases where AI has fully replaced human workers in specific roles. Here are five high-quality reports and studies from 2025 that drive this point home, each grounded in data and analysis, not hype.
World Economic Forum - Future of Jobs Report 2025: This comprehensive report surveyed employers globally and found that while 40% anticipate workforce reductions due to task automation, AI creates as many jobs as it displaces. It emphasizes that white-collar roles: analysts, marketers, or managers, see task-level changes, not wholesale replacement. The data shows AI mildly and gradually reshaping workflows, not erasing jobs.
Exploding Topics - "60+ Stats On AI Replacing Jobs (2025)": This article compiles global statistics on AI’s labor market impact. It confirms that no single profession has seen its roles replaced by AI alone. Layoffs often tied to AI in headlines are confounded by cost-cutting, restructuring or offshoring, not direct machine takeovers. The numbers don’t lie: full job replacement remains a fantasy.
Harvard Gazette (August 2025) - "Will your job survive AI?": Harvard Business School experts weigh in, noting that AI automates specific tasks, like data entry or report drafting, but falls short of replacing entire white-collar roles. Complex judgment, creativity, and context keep humans in the driver’s seat. The article calls out the gap between speculative fears and real-world evidence.
Axios (May 2025) - "AI jobs danger: Sleepwalking into a white-collar bloodbath": This piece warns of potential future risks but admits no clear data shows AI replacing white-collar workers today. It distinguishes between task automation and job elimination, noting that layoffs often involve multiple factors, not just AI. The lack of unambiguous examples is telling.
New York Times Opinion (June 2025) - "A 'White-Collar Blood Bath' Doesn't Have to Be Our Fate": This opinion piece cuts through the hype, arguing that bold claims of AI-driven job losses lack empirical backing. It highlights how AI augments work, speeding up tasks like drafting emails, but doesn’t replace the nuanced roles of professionals, where judgement matters. The data points to evolution, not revolution.
These sources, spanning global organizations, academic institutions, and respected media, converge on a clear conclusion: there are no independently verified, unambiguous cases exist of AI outright replacing white-collar workers at any scale. The myth of an AI takeover is just that, a myth, fueled by speculation rather than substance.
Part 2: Three High-Profile AI Replacement Failures
If AI hasn’t replaced jobs, what happens when companies try? The answer so far: spectacular failure. Three well-documented cases: Klarna, Forward Health, and Olive AI, show companies attempting to swap humans for AI, only to crash and burn. These examples expose the severe limitations of AI when pushed to replace human workers outright.
Klarna: Customer Service Catastrophe
In 2022–2023, Swedish fintech giant Klarna replaced ~700 customer service agents (40% of its staff) with AI chatbots, aiming for cost savings and efficiency. The result? A disaster. Customers complained of poor service, with AI unable to handle nuanced queries requiring empathy or judgment.
As reported by The Economic Times, CEO Sebastian Siemiatkowski admitted the company “went too far,” sacrificing quality for automation. FinTech Weekly noted a drop in customer experience metrics, forcing Klarna to rehire human agents for a hybrid model. LaSoft Insights confirmed that AI’s lack of empathy and nuance led to a reputational hit, with Klarna now recruiting remote workers to fix the mess.
Outcome: FAILED due to quality failures and customer backlash.
Forward Health: Healthcare’s AI Misadventure
Forward Health, a U.S. healthcare startup, attempted to replace frontline clinic staff—clinicians, nurses, and desk workers—with AI-powered “CarePods” from 2021 to 2024. The goal was self-service diagnostic booths, but the execution was a fiasco.
Business Insider (November 2024) reported that over half of the automated blood draws failed, and patients were sometimes trapped inside pods, eroding trust. ICT Health (December 2024) highlighted high costs (~$1 million per pod) and patient alienation, with only three pods deployed before the company shut down. Maginative (November 2024) noted the loss of nearly 200 jobs and a failure to reach $100 million in revenue, despite $650 million in funding.
Outcome: FAILED due to technical glitches, poor user experience, and neglect of the human element in healthcare. This company is no longer in business.
Olive AI: Back-Office Breakdown
Olive AI aimed to automate hospital back-office tasks like billing and authorization from 2020 to 2023, targeting large-scale staff reductions. The result? A complete collapse.
SunsetHQ reported that Olive, once valued at $4 billion after raising $850 million, shut down in October 2023 due to operational inefficiencies and overambitious growth. HealthCare Dive (November 2023) noted 450 layoffs in 2022 and the sale of core units, as AI failed to deliver value. Fierce Healthcare (October 2023) cited CEO Sean Lane’s admission of strategic missteps and market shifts, with hospitals reverting to human processes.
Outcome: FAILED due to technical failures, poor integration, and financial collapse. This company is no longer in business.
These cases aren’t anomalies, they are warnings. Companies that bet on AI to replace humans underestimated the complexity, empathy, and judgment required in white-collar roles, leading to reversals, rehiring, or outright business failure.
Part 3: Scholarly Evidence of Augmentation, Not Replacement
If AI isn’t replacing white-collar workers, what is it doing? The answer lies in peer-reviewed research: AI augments human work, boosting productivity but not supplanting people. Scholarly studies consistently show LLMs excelling at specific tasks while failing to handle the full scope of white-collar roles.
Here’s the evidence.
A 2023 MIT study, referenced in the Harvard Gazette, tested LLMs in real-world white-collar settings. Writers, analysts, and marketers saw faster output: think drafting reports or emails, but human oversight was critical for quality and context. The study concluded that LLMs can enhance speed and efficiency, not replace entire roles.
Similarly, a 2025 IBM Research study, cited in the World Economic Forum report, found that LLMs in office support and financial operations reduced drudgery but required human judgment for complex decisions. No evidence supported full job replacement.
A 2024 PNAS Nexus article, noted in Exploding Topics, analysed task exposure across white-collar sectors. It found that 30–40% of tasks in roles like business operations or computer work are automatable, but the remaining 60–70%, involving creativity, strategy, or interpersonal skills, resist AI takeover.
A 2022 study, “Artificial Intelligence and Employment: New Cross-Country Evidence,” reported shifts in hiring and skill demands but no clear cases of AI-driven job elimination. Finally, a 2025 Carnegie Mellon qualitative study, also referenced in Exploding Topics, highlighted LLMs’ struggles with originality and nuanced problem-solving, reinforcing their role as tools, not replacements.
These studies paint a clear picture: LLMs are potentially powerful for automating some repetitive tasks, but they falter in areas requiring human insight, judgement, adaptability, or emotional intelligence. The scholarly consensus is augmentation, not annihilation.
Conclusion: Shattering the Myth
The narrative of AI replacing white-collar jobs is a myth, propped up by hype and fear, not facts. Independent sources like the World Economic Forum, Harvard, and the New York Times find no verified cases of AI fully replacing human roles.
High-profile failures at Klarna, Forward Health, and Olive AI expose AI’s limitations: technical glitches, lack of empathy, and inability to handle complexity, leading to customer backlash, rehiring, or company collapse. Scholarly research confirms these results, showing AI as a productivity booster, not a job killer.
CEOs may tout AI’s potential, but the data tells a humbler story: LLMs can’t match the nuanced, creative, and human elements of white-collar work. Far from a takeover, AI’s history is a lesson in overpromising and underdelivering. For now, humans remain irreplaceable.
Back to Contents · Back to Top
Footnotes
Thank you for reading this article!
More information about Overlogix can be found at Welcome to Overlogix!
We currently publish on both LinkedIn (general interest articles, summaries, TL;DR’s: easier and faster to read) and Substack (in-depth articles, how-to’s, technical studies and new approaches to business).
LinkedIn:
· Why hire me? The elevator pitch
· Introduction: Welcome to Overlogix!
· The Overlogix Sunday Times Our newsletter, with occasional specials, published roughly every two weeks.
· Master Index All our articles can be found from here in two clicks.
· The Overlogix Table of Context All Overlogix articles in reverse chronological order
· Applied Artificial Intelligence: Index of Articles One of our specialties is Applied AI. This index lists all relevant articles on the topic, in reverse chronological order.
· Applied AI: Stories in the News Our semi-permanent, curated listing of interesting and important news from the world of artificial intelligence, from many different sources.
· Index: Getting a Job Up until recently, getting a job, much less a good job, has been a nightmare for most job seekers. We publish articles on how and why this is so, and what job hunters can do to find the perfect job for them. We also supply credible external resources, so people can consider their alternatives.
· Starting a B2B Business For everyone who can, we heartily recommend starting your own business. The tools are there, and there has never been a better time to do it.
· Building Our Own Robot We’re automating Overlogix from the start, and this series of articles tells exactly how we are doing it.
· Rebuilding the Linux Server: Index of Articles Running AI on your own machine (recommended) requires a modern, up-to-date operating system, and often a lot of additional software infrastructure. This series, dedicated to exactly that sort of system administration, details what we have done to build a powerful server that runs both databases and artificial intelligence, locally.
· The Gospel According to ChatGPT Conversations with various AIs and additional articles on the various challenges associated with actually making profitable use of artificial intelligence.
· TL;DR: Index of Fast Reads Brief, fast reads on various topics in artificial intelligence. If you are a beginner at AI, or a busy human needing fast and factual explanations of complicated technical topics, this is the place to start.
· TL;DR: Overlogix Artificial Intelligence Mini-Wiki Same Fast Reads as previous but arranged in a mini-wiki format some folks may like better.
Substack:
· Welcome to the Overlogix Substack
· Overlogix: Table of Context Index to our Substack articles arranged by topics.
· Criteria for Paid Content Rules for what goes behind our paywall.
· Curated IT and AI Sources Annotated links to sites and YouTube channels we think are valuable.