AI is improving work for some people, but current evidence does not show that it has made working life better overall. Many surveyed workers report benefits, yet reported performance and enjoyment are not the same as independently measured productivity, higher pay, or secure employment. Whether AI improves work in the future will depend partly on how employers manage workload, worker input, privacy, training, and the distribution of gains.
What do workers say AI has changed?
In a 2024 summary of its workplace surveys, the OECD reported that four in five surveyed workers said AI improved their performance at work, while three in five said it increased their enjoyment. Those figures describe workers’ perceptions in the surveyed groups. They do not establish that AI caused the same improvement for every worker or that perceived gains became higher output or pay.
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The underlying OECD survey, published in 2023, collected responses in early 2022 from 5,334 workers and 2,053 firms in finance and manufacturing across Austria, Canada, France, Germany, Ireland, the United Kingdom, and the United States. That is useful evidence about those sectors and countries, but it is not a measure of all occupations or current use of newer generative AI tools.
Use and quality of work are different questions
Microsoft and LinkedIn reported in their 2024 Work Trend Index that 75% of surveyed knowledge workers used AI at work. The survey covered 31,000 people across 31 countries and was supplemented by other company data. It offers a broad, company-sponsored view of AI use among knowledge workers—not a measure of whether work became safer, more satisfying, better paid, or more secure. Its population and method also differ from the OECD surveys, so the percentages should not be compared as though they measured the same thing.
Are reported time savings becoming measurable gains?
Not consistently in the evidence reviewed. The International Labour Organization’s June 2026 review of experiments, firm-level data, platform studies, and worker surveys describes reported time savings as a few per cent of working hours, but says these savings have not yet translated broadly into higher measured output, earnings, or employment. Gains appear uneven and are often not independently verified.
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This distinction matters: a worker may finish a task faster without producing more valuable output overall, receiving a larger share of the value, or having a lighter workload. An employer might use saved time to reduce pressure or improve service, or instead assign more tasks. A time-saving report alone cannot tell us which outcome occurred.
What can make AI worsen work?
Work quality is broader than speed. OECD and ILO materials flag risks involving work intensity, job stability and wages, privacy and data use, inequality, autonomy, coordination, and job quality. These risks are not proof that every AI deployment causes harm; they are reasons to look beyond adoption rates and productivity claims.
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1Repair Windows errors before they cause bigger problems2Scan for outdated or missing drivers - takes under a minute3Clear out junk files and repair common Windows errors- Workload and pace: Faster task completion can become a higher expected pace rather than more time or breathing room for workers.
- Autonomy and oversight: Algorithmic management can influence how work is assigned or evaluated. Workers need a meaningful way to understand, question, and contest consequential decisions.
- Privacy and data: Workplace systems may rely on information about workers or their activity. Clear limits on collection, access, and use matter to trust and accountability.
- Job quality and security: Changes in tasks can affect satisfaction, wages, stability, and access to opportunities. Exposure to AI is not, by itself, evidence that a job will disappear.
- Unequal effects: Outcomes can vary by occupation and demographic group, so averages may conceal workers who face greater disruption or receive fewer benefits.
Does AI usually replace workers or assist them?
The ILO’s 2025 synthesis says AI is more likely in many roles to augment human capabilities and enhance productivity than to produce widespread automation. It also emphasizes variation across occupations and demographic groups. This is a broad assessment, not a guarantee about any particular job: a technology can assist with some tasks while changing the number, content, or conditions of jobs in a specific workplace.
The same ILO paper highlights algorithmic management and the data labor behind AI systems—work that can be overlooked when attention focuses only on the people using AI tools. Judging effects therefore requires looking at the whole work process, not only the task that appears to have been automated or accelerated.
What would make AI more likely to improve working life?
Workplace choices are part of the outcome. OECD material reports an association between training and worker consultation and better worker outcomes in its surveys. That association does not prove that either factor alone causes better results, but both are practical indicators to examine when assessing an AI deployment.
Questions workers and employers can ask
- Are workers reporting better performance or enjoyment, and are those perceptions checked separately from measured output, earnings, and employment?
- Does saved time reduce pressure or improve the work, or does it simply raise the expected pace and volume?
- Can workers understand and challenge AI-supported decisions that affect their tasks or conditions?
- Are data collection and use transparent, limited, and subject to clear safeguards?
- Do workers receive relevant training and have a real opportunity to shape how the system is introduced?
- Are outcomes tracked across occupations and demographic groups, rather than relying on one workplace-wide average?
These questions are a way to evaluate a particular workplace, not a universal scoring system. The available OECD and ILO evidence identifies relevant outcomes and risks but does not establish one standard measure of whether every AI deployment makes work better.
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Repair common Windows errors and clear accumulated junk for a smoother, more stable PC - no reinstall needed.Free scan · no reinstallWhat should readers conclude about AI and the future of work?
The evidence supports neither a blanket promise of a better working life nor a blanket prediction of widespread job loss. Some workers report that AI helps them perform and enjoy their work; broader measured gains in output, earnings, and employment have not yet been established at scale in the ILO’s reviewed evidence. The gap between those findings is central: improving work depends not just on what AI can do, but on how workplaces organize its use and share its benefits.
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