All In On AI?
Contrary to conventional wisdom, the 2023 ABS (which produced 2022 data) found that adoption of technology, including AI, did not change overall worker numbers.
About 78% of organizations reported using AI in 2024, up from 55% the year prior, according to Stanford’s 2025 AI Index. Recent analyses found that AI has had — at least so far — little impact on employment numbers.
Some jobs, like financial examiner, are more “exposed” to AI than, say, a construction worker whose job can’t be easily simulated by an AI model. But research from the Economic Innovation Group shows that from 2022 to the beginning of 2025, the unemployment rate rose less for the most AI exposed workers (up 0.30 percentage points) than for the least AI-exposed workers (up 0.94 points).
Impact of Technology on Workers
Businesses most often reported their “number of workers did not change overall” between 2020 and 2022 after adopting any of the five technologies the ABS tracked: AI, specialized software, robotics, cloud-based tech or specialized equipment (Figure 1).
When these technologies did have an impact, all (except robotics) were reportedly more likely to increase than decrease worker numbers.
There was no statistically significant difference between the number of workers increased (9.5%) or decreased (8.1%) by robotics.
When compared, none of the technologies significantly increased worker numbers more than any other.
Impact of Technology on Worker Skills
Most businesses also reported these technologies had little or no impact on worker skill level (Figure 2).
AI was the technology businesses most often cited as positively affecting the skill level of workers (Figure 2).
Only 3.9% of businesses using robotics and 3.3% of businesses using AI reported workers’ skill level decreased — the largest shares in this category (with no statistically significant difference between them).
AI (40.7%), specialized equipment (50.2%) and robotics (56.6%) largely had no overall impact on worker’s scientific, technological, engineering, and mathematics (STEM) skills (Figure 3).
When a technology did alter skills of STEM workers, it was more likely to boost than diminish them — with robotics (20.7%) and AI (22.1%) the most likely.
Cloud-based technology and specialized software were most often found “not applicable” to STEM worker skills (40.9% and 41.6%, respectively) or to have caused no change overall (44.4% and 44.9%, respectively). There were no statistically significant differences between these two impact categories and technologies.
Why Companies Embrace New Technologies
Improving the quality or reliability of processes or methods was the most common motivating factor for businesses to adopt cloud-based technology (51.8%), specialized software (49.8%) and AI (45.8%) between 2020 and 2022 (Figure 4).
Specialized equipment and robotics were the only categories in which improving processes or methods was not the top motivating factor.
The top reason cited for adopting specialized equipment was to improve the quality or reliability of goods or services (49.8%).
Businesses used robotics to automate tasks performed by human labor (50.8%), improve the quality or reliability of goods and services (41.8%), and improve the quality or reliability of processes or methods (43.6%). The differences between these motivations were not statistically significant.
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