The People Building AI Are the Worst at Predicting It
I graded 18 dated AI predictions from the last two years against what actually happened. The scoreboard is brutal, and the one guy who scored well got nothing for it. In March 2025, Dario Amodei told the Council on Foreign Relations that AI would be writing 90% of code within three to six months, and essentially all of it within twelve. That twelve-month deadline passed in March. Almost nobody…
A recent analysis graded 18 outdated AI predictions from the past two years against actual outcomes, revealing that while some predictions were partial successes, most were wildly inaccurate. Sam Altman predicted that AI agents would join the workforce in 2025, but this has not materialized. MIT's NANDA project found that 95% of enterprise generative AI pilots produced no measurable profit impact.
Carnegie Mellon's AI agents completed only 30.3% of tasks in a fake company simulation. Marc Benioff's vision of 1 billion AI agents by the end of 2025 saw Salesforce reporting just 29,000 cumulative Agentforce deals by early 2026. Klarna's AI assistant was predicted to perform the work of 700 full-time agents, but the company later rehired humans for better quality.
Eric Schmidt predicted that AI would replace nearly all programmers in a year, but programmers remain employed. Meta's prediction of an AI that can effectively act as a midlevel engineer did not come to fruition. Elon Musk predicted AI smarter than any human by the end of next year, but the xAI Grok 4 model scored poorly on a benchmark.
Mira Murati claimed PhD-level AI for specific tasks would arrive in 18 months, and Deep Think did achieve this in math. Overall, while some predictions had elements of truth, the majority were significantly off the mark.
Written by urgent.news from Dev.to's reporting — not their text. Machine-written — may contain errors; check the original before relying on it.
