Microsoft AI chief executive Mustafa Suleyman said that artificial intelligence can replace most white-collar work in the 12 to 18 months. The Microsoft head said this during a YouTube interview with the Financial Times, where they talked about the company’s aims to achieve “humanist superintelligence.” During this conversation, the topic steered into artificial capable intelligence, which was the term that Suleyman coined for the phase in AI development between basic large language models (LLMs) and Artificial General Intelligence (AGI).
When the host asked him about the latter, he said, “I think we’re going to have a human-level performance on most, if not all, professional tasks. So, white-collar work, where you’re sitting down at a computer — either being, you know, a lawyer, or an accountant, or a project manager, or a marketing person — most of those tasks will be fully automated by an AI within the next 12 to 18 months.”
This line echoes that voiced other business leaders, with Anthropic CEO Dario Amodei proclaiming that AI will wipe out half of all entry-level white-collar jobs in five years. Ford CEO Jim Farley agrees with this prediction, saying that “AI will leave a lot of white-collar people behind.” Even scientists are worried about this, with an MIT simulation showing that AI could replace 11.7% of U.S. workers across multiple industries and not just in tech.
However, others are a bit more skeptical about this prediction. While there has been a claimed increase in AI-driven layoffs last year, some researchers suggested that this was instead driven by poor business performance blamed on exaggerated AI capabilities. Another MIT study showed that 95% of enterprise use of generative AI had no measurable impact on profit and loss, while a report from Pricewaterhouse Coopers that 55% of chief executives saw no benefits with the deployment of AI tools.
Still, Suleyman is confident about how AI can be used in nearly any application. “There are going to be billions of digital minds. There are going to be many, many different lineages of model [sic]. Creating a new model is like creating a podcast or writing a blog — it is going to be possible to design an AI that suits your requirements for every institution, organization, and person on the planet.”
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