Companies investing heavily in artificial intelligence are increasing their workforce faster than other firms, including in entry-level positions that many expect AI to replace, according to a new report.
The analysis combined corporate spending data from Ramp with workforce records from Revelio Labs. It examined 21,599 companies in the United States.
The report classified businesses as “high-intensity adopters” when they spent an average of $30 per employee per month on AI during the first three months of adoption. These companies recorded a 10.2% increase in overall headcount.
Hiring also increased across engineering, sales, administration, customer service, finance, marketing, and scientific roles.
The strongest employment growth appeared in the information sector, which includes software, internet, media, and technology-related companies.
The findings do not prove that AI investment directly creates jobs.
The data mainly covers technology-focused and knowledge-based companies. Many of these firms may have venture capital backing and could already be expanding quickly.
This makes it difficult to determine whether AI caused the hiring growth or whether rapidly growing companies were simply more likely to invest in AI.
The report’s authors acknowledged that the study does not show that AI creates jobs in every industry. However, they said the results challenge predictions that AI will cause widespread job losses.
The findings also challenge claims that AI is eliminating all entry-level positions.
Previous Goldman Sachs research estimated that AI had removed around 16,000 net jobs per month during the past year. Gen Z workers and people seeking junior roles reportedly experienced the largest impact.
However, the new report found that entry-level headcount at technology-focused companies increased by 12%.
The researchers said AI can help software and technology businesses produce core work more quickly and at a lower cost.
This includes writing and debugging code, building internal tools, preparing technical documents, and supporting product development.
Lower production costs can make it more profitable for a company to expand its entire workforce rather than only increasing the size of its engineering team.
Companies that only purchased AI subscriptions or tested pilot projects did not record similar employment growth.
The report found that businesses needed to make sustained investments in AI before they saw noticeable workforce gains.
This could create a larger divide between companies that can turn AI into real business improvements and those that remain stuck in the testing stage.
Businesses with access to capital, technical employees, management resources, and strong founder networks may receive the greatest benefits from AI adoption.
As a result, companies that already have significant resources may also be best positioned to achieve the largest gains.
Another common assumption facing pressure is that companies offering open AI models cannot build profitable businesses.
Open-model companies are beginning to generate meaningful revenue as more organisations move away from renting access to AI systems and instead operate models on their own infrastructure.
This development suggests that offering models openly does not necessarily prevent companies from building sustainable businesses around them.
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