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Revisiting the AGI Timeline: The Disruption That’s Already Here and What Comes Next

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28.04.2026

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Revisiting the AGI Timeline: The Disruption That’s Already Here and What Comes Next

The timeline to AGI may be slipping, but the economic and organizational disruption is only accelerating.

In early 2025, a team of five researchers from the AI Futures Project published AI 2027: a scenario document tracing how technological progress, governance choices and geopolitical dynamics would interact and compound over the next several years. The final report concluded that by 2027, it would be plausible for A.I. systems to surpass human cognitive performance across a meaningful range of tasks. This is called artificial general intelligence (AGI), and it’s a threshold event the entire A.I. industry has been tracking for years.

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One year later, and with one year to go until that prophesied AGI moment, it’s worth revisiting the researchers’ original forecasts to highlight what is missing from the conversation, examine how A.I. capabilities are compounding faster than our institutions are prepared to handle and explore what that means for businesses (and the rest of society) in 2027 and beyond. 

How did the AI 2027 authors’ predictions play out? 

The authors outlined their five-year path to AGI, with explicit metrics to track progress along the way. They characterized 2025 and 2026 as foundational years, marked by the emergence of A.I. agents that would propel advancements in computational power and model capabilities, setting the stage for AGI in 2027. They extended the scenarios through 2030 by presenting two possible endpoints for a post-AGI world. 

In a formal self-assessment published in February 2026, the authors estimated progress toward AGI had reached roughly two-thirds of their expected pace. Reaching AGI will thus take longer than expected, and the authors updated their forecast, pushing the likely arrival of AGI to between 2029 and 2032.

Although the authors may disagree among themselves on timing, that uncertainty does not detract from the pace of observable change. For enterprise leaders, A.I.-driven disruption is not a threshold event scheduled sometime in the........

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