Microsoft AI Chief Mustafa Suleyman has a grim warning for every office worker- Within 18 months… – Crypto News

Microsoft AI chief executive Mustafa Suleyman has predicted that artificial intelligence will reach human-level performance across most professional tasks within 18 months, putting lawyers, accountants, marketers and project managers among those most at risk of displacement.

Speaking in a conversation with the Financial Times, Suleyman delivered one of the most precise and sweeping timelines yet from a major technology leader on the pace at which AI will reshape office work. The prediction has reignited a debate that has been building since early 2025, when a chorus of chief executives first began sounding the alarm on white-collar automation.

Why Suleyman Says Accountants, Lawyers and Marketers Are Most Vulnerable

Suleyman predicted “human-level performance on most, if not all professional tasks” being done by AI. Most tasks that involve “sitting down at a computer” will be fully automated by AI within the next year or 18 months, he said, naming accounting, legal, marketing, and even project management as vulnerable

The Microsoft AI chief cited the exponential growth in computational power as a primary driver. As processing capacity advances, he argued, AI models will be able to write and review code better than most human programmers, with knock-on effects for a wide range of knowledge-based professions.

Suleyman also struck an unexpectedly democratising note on the future of AI deployment. “Creating a new model is going to be like creating a podcast or writing a blog,” he said. “It is going to be possible to design an AI that suits your requirements for every institution, organisation, and person on the planet.”

AI Researchers Compare This Moment to the Days Before Covid Hit

Suleyman’s warning found a parallel in a widely circulated essay by AI researcher Matt Shumer, a version of which was published at Fortune. Shumer compared the current moment to February 2020, in the days before the Covid-19 pandemic reached the United States, arguing the coming disruption would ultimately prove more dramatic than the pandemic’s own economic shock.

OpenAI chief executive Sam Altman and Shumer have both written about what they described as alarm, and even personal sadness, at watching the technology they built rapidly render earlier work obsolete.

SpaceX chief executive Elon Musk, speaking at Davos in January, said he believed artificial general intelligence, meaning AI that matches or surpasses human-level intelligence, could arrive as early as this year.

Writing in The Atlantic, journalist Josh Tyrangiel argued the US was unprepared for the coming disruption, comparing the recent reticence of chief executives on the subject to seeing “a shark fin break the water.”

What the Data Actually Shows: AI’s Impact on Professional Jobs Has Been Modest So Far

Despite the scale of the predictions, the evidence on the ground tells a more complicated story. A 2025 Thomson Reuters report found that lawyers, accountants, and auditors are experimenting with AI for targeted tasks such as document review and routine analysis, but that productivity improvements have so far been marginal and fall well short of signalling mass job displacement.

In some documented cases, AI has made workers less productive rather than more. A study by the nonprofit Model Evaluation and Threat Research found that AI’s impact on software developers actually caused tasks to take 20 per cent longer than they would have done without it.

Economic returns from AI investment also remain concentrated. Research by Apollo Global Management chief economist Torsten Slok found that while profit margins in large technology companies increased by more than 20 per cent in the fourth quarter of 2025, the broader Bloomberg 500 Index recorded almost no change.

Slok separately noted that “investors do not believe AI will result in higher earnings outside the tech sector,” citing consensus Wall Street expectations for the S&P 500.

AI-Related Job Cuts Are Already Happening, Even If Mass Displacement Has Not

There are, however, early and measurable signs that AI is beginning to contribute to workforce reductions. Employment consultancy Challenger, Gray and Christmas recorded approximately 49,135 job cuts so far this year that were attributed to AI. Microsoft itself cut 15,000 workers last year, and whilst the company did not cite AI as the primary reason, chief executive Satya Nadella said in a memo following the eliminations that the company must “reimagine our mission for a new era.”

Financial markets have already begun pricing in the technology’s disruptive potential. In February, software stocks suffered a significant sell-off driven by automation fears, which analysts termed the “SaaSpocalypse,” referring to the software-as-a-service sector.

The sell-off followed announcements by Anthropic and OpenAI of agentic AI systems for enterprises, designed to perform many of the core functions previously carried out by SaaS organisations.

Suleyman’s Bigger Mission: Building Superintelligence and Cutting Ties With OpenAI

Beyond the 18-month forecast, Suleyman outlined a longer-term ambition. He said his central mission as the steward of Microsoft AI is to achieve what he called “superintelligence,” and that the company intends to reduce its dependence on OpenAI by developing its own independent foundation models.

“This after all is the most important technology of our time,” Suleyman said. “We have to develop our own foundation models which are at the absolute frontier.”

Earlier warnings from other chief executives set the context for Suleyman’s remarks. Anthropic chief executive Dario Amodei warned last May that AI could wipe out half of all entry-level white-collar jobs, though he has since moderated that position.

Ford chief executive Jim Farley said AI would cut in half the number of white-collar jobs across the US. MIT Technology Review featured Suleyman in April, in which he insisted that AI development would not hit a ceiling in the near term, even as accumulating evidence continues to complicate the most expansive predictions made about the technology’s pace of disruption.