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What the employment numbers show
Forecasts, observed employment trends and employer expectations measure different things. They also cover different populations: an occupation across every industry is not the same as the workforce of technology companies.
| Measure | Finding | What it covers |
|---|---|---|
| U.S. occupational projection, BLS (2026) | Software-developer employment is projected to grow 15.8%, or 267,700 jobs, from 2024 to 2034. | Software developers across industries, not just technology companies. |
| U.S. occupational projection, BLS (2026) | Data scientists are projected to grow 33.5%, or 82,500 jobs, from 2024 to 2034; information security analysts, 28.5%, or 52,100 jobs. | Those occupations across industries. |
| U.S. occupational projection, BLS (2026) | Customer service representatives are projected to decline 5.5%, or 153,700 jobs, and procurement clerks 8.7%, or 5,400 jobs, from 2024 to 2034. | These are all-industry occupations, not counts of tech-sector jobs lost to AI. |
| Global employer expectations, World Economic Forum (2025) | By 2030, employers estimate 170 million jobs created and 92 million displaced, for net growth of 78 million. | Global estimates across occupations and multiple macrotrends; not an AI-only estimate or a count of technology jobs. |
| Observed coder employment pattern, Federal Reserve (2026) | Coder employment continued to grow, but more slowly than before 2022. | A historical employment trend; it does not isolate AI as the cause. |
The BLS projections are consistent with a labor market in which technology shifts demand in different directions. The agency says that greater use of information technology, including AI, may boost demand in some occupations while other occupations decline. Its projections are forecasts based on historical patterns and assessments of possible future developments, not controlled estimates of how many jobs AI will create or remove.
Why automating tasks does not automatically eliminate an occupation
AI can assist with parts of software work, including coding, testing and documentation. Automating or speeding up a task can change what workers do without removing the entire job: people may still be needed for work that remains, for coordinating tasks, or for developing and maintaining AI systems. BLS identifies demand for AI solutions and for maintaining AI systems as factors that may support computing occupations.
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That does not mean every worker or role will benefit. Employers may reorganize work when tools change how much time particular tasks require. Whether that produces fewer hires, different responsibilities, or new work depends on how organizations use the tools and what customers and employers need. BLS explicitly notes uncertainty in assessing how emerging technologies will affect employment.
What the evidence can—and cannot—say about layoffs
The Federal Reserve’s finding that coder employment grew more slowly after 2022 is relevant, but it is not a count of jobs lost to AI. It describes a change in the pace of employment growth, and does not establish what would have happened without AI.
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Company announcements and executive explanations need similar care. An employer may cite AI when describing a restructuring, but that statement does not by itself show how many positions were eliminated because of AI rather than other business decisions. Associated Press reporting in July 2025 described competing explanations for weakness in technology job postings and layoffs, including broader cooling in the labor market and the end of pandemic-era hiring. The available evidence does not establish a comprehensive share of tech job cuts caused by AI.
Keep these claims distinct when evaluating a headline:
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A free scan shows the junk files, broken settings and background clutter dragging Windows down - then fixes them in one click.Free scan · Windows 10 & 11- Exposure: a task or occupation could be affected by AI.
- Employer rationale: a company says AI influenced a staffing decision.
- Measured outcome: employment or hiring changed over a defined period.
- Causation: evidence shows how much of that change happened because of AI rather than other factors.
How to read forecasts and headlines as a worker
Use the figures as context, not as a prediction of what will happen to one person, employer or local job market. Before drawing a conclusion, check the geography, period and population measured. A U.S. projection for an occupation across all industries, a global employer survey and a company’s layoff announcement cannot be compared as if they count the same thing.
For career and household decisions, focus on changes you can observe in your own field: whether employers are hiring for the work you do, whether role requirements are shifting, and whether AI tools are changing your responsibilities. It is sensible to build adaptable skills and avoid relying on one headline as a reason for an abrupt career or financial decision. No projection guarantees a particular job outcome.
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