- More than two out of three companies now use artificial intelligence
- 89% have not seen increased productivity, and 60% expect no further effect
- Yet 90% have not experienced any major job losses and 63% expect this to remain the same
A major study surveying around 6,000 CEOs, CFOs and other senior managers in the US, UK, Germany and Australia has quantified how many companies are actually using artificial intelligence – and claims many companies are still not seeing the benefits previously promised.
According to data from the National Bureau of Economic Research (NBER), more than two-thirds (69%) of businesses are currently using AI tools, with some additional growth expected within the next three years.
However, 89% reported no impact on productivity over the past three years. Still, with just as many (90%) noting any impact on employment over the same three-year period, it’s clear that businesses are willing to keep trying.
Are we actually using artificial intelligence to its full potential?
The most common use cases highlighted in the report include text generation (41%), data processing (30%), visual content creation (30%) and image processing (20%). However, while not quite as commonly used in robotics (9%) and autonomous vehicles (3%), where implementation is likely to be more complex, overall usage increased by around 50% over 2025.
Still, the outlook is not very positive. While 25% expect small productivity gains and 12% expect large gains, 60% expect to see no effect at all. The story is largely the same for employment, with 63% expecting no effect and only a combined 26% expecting to see job cuts, which at least brings some good news.
“Over the next three years, firms predict that the introduction of artificial intelligence will increase productivity by about 1.4% on average, while reducing employment by about 0.7%,” the researchers wrote.
Although the authors acknowledge that the study in isolation does not provide sufficient meaningful insight, they urge that further studies be conducted using standardized methodology to ensure more reliable comparisons: “We further emphasize the importance of consistency in study design and timing.”
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