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Global Research With Over A Thousand Executives Reveals That Companies Are Laying Off And Reducing Hiring Due To Expectations Around Artificial Intelligence, Even Without Wide Proof Of Financial Gains Or Effective Substitution Of Workers By Technology Tools.
Companies in different countries have laid off employees and slowed hiring in anticipation that artificial intelligence will take over part of the work, even without consolidated evidence of effective large-scale substitution.
This is the main conclusion of a survey that interviewed over a thousand executives around the world.
The study was conducted by Thomas Davenport, a research associate at MIT, and Laks Srinivasan from the Ashoka University Social Impact Center, and formed the basis of an article published in the Harvard Business Review.
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According to the authors, part of the layoffs occurs in anticipation of what technology may do in the future, not what it is currently doing.
Anticipatory Layoffs And The Impact Of AI On The Job Market
In the United States, despite unemployment remaining at a low level, the adoption of generative tools has fueled speculation about the impact on the job market, especially in the technology sector.
The focus often falls on early-career professionals, perceived as more exposed to changes in entry-level routines.
Davenport and Srinivasan assert that this movement exists, but in most cases, it is not explained by systems that consistently replace people.
“We found that AI is behind some layoffs, but these are almost entirely anticipatory to the impact of AI,” they wrote.
Companies Reduce Headcounts Before Proving Gains With Artificial Intelligence
According to the researchers, the decision to downsize teams has been made before organizations can prove productivity gains or cost reductions attributable to AI.
“Companies are making the decision to reduce the number of employees before realizing the benefits of AI impact,” they argue.
The reading presented in the article is that technology has become an important element in workforce planning, even though actual use is not mature in some companies.
In this scenario, the change occurs first in the headcount spreadsheet and only later, when it happens, in work processes.
Cuts In SMEs And Large Companies Due To Future Expectations
The research indicates that 39% of small and medium-sized enterprises interviewed have already cut employees in anticipation of future capabilities of artificial intelligence.
Among large companies, 21% reported having made reductions for the same reason, still not associating the cuts with a proven successful implementation.
Another data reinforces the preventive logic, showing that 29% of organizations say they are hiring less than normal due to expectations of automation or increasing support from AI.
In practice, the slowdown in hiring appears as a form of gradual adjustment, parallel to layoffs.
Only 2% Register Large Cuts Due To Effective AI Implementation
Despite the volume of companies mentioning cuts related to the topic, the study indicates that only 2% have made large reductions in their workforce linked to effective implementation of the technology.
In other words, large substitutions directly attributed to the functioning of AI are still rare in the analyzed sample.
This contrast between expectation and realization helps explain why part of the public debate seems to run faster than operational results.
At the same time, it suggests that the use of AI may be influencing management decisions even when it has not yet profoundly altered the day-to-day work of teams.
Difficulty In Measuring Financial Return Coexists With Positive Perception
In addition to the effect on employment and hiring, the research highlights a recurring obstacle for those investing in AI: 44% of companies reported difficulties in establishing financial gains associated with the use of these tools.
The problem appears as a bottleneck for evaluating costs, benefits, and project prioritization.
Nevertheless, most respondents say they believe the investment is paying off, even without robust metrics in some organizations.
The survey indicates that 90% see profit or some type of return from investments in generative AI, in a broader and less objective assessment.
Expectations About AI Guide Management And Employment Decisions
The coexistence of difficulty in measurement and positive perception signals an uncertain ground for decisions affecting employment.
When an organization does not measure the impact well, the tendency is for management to rely on indirect signals, market comparisons, and expectations of future gains.
On the other hand, the study does not state that AI is irrelevant, but that it is still not delivering, in a generalized way, the level of transformation that would justify widespread cuts for direct substitution.
Thus, layoffs associated with the topic may reflect strategy, pressure for efficiency, or anticipation of a change still underway.
Even with the low rate of large reductions attributed to concrete implementations, the research suggests that the immediate effect may occur at the entry point of the job market.
If hiring slows down due to expectations of automation, entry-level positions tend to shrink before new roles emerge at the same pace.
Meanwhile, companies face the challenge of redesigning tasks and clearly measuring what has actually been automated, accelerated, or improved with AI.
Without this map, personnel cuts may rely more on promise than on performance, risking loss of knowledge and operational capacity.
The central reading of the article is that artificial intelligence is already influencing workforce decisions, but many of them happen before the technology “proves” the promised value.
As a result, the debate about jobs begins to include not only what AI does, but what leaders believe it will do.
If adoption continues to advance and return measurement remains fragile in some companies, the market may continue to contend with decisions made in the dark.
To what extent should organizations condition layoffs to provable results, rather than expectations about the future of AI?
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