Study: companies with heavy AI investment grow headcount by around 10% within two years

Full text

Companies going all-in on AI are also seeing positive impacts on headcount

Entry-level roles saw higher-than-average growth, opposing existing research

Workforce gains aren't immediate – AI needs time to find its place within organizations

A new report has challenged the narrative that AI adoption has been leading to job losses, instead revealing that the companies making the biggest investments in AI are actually growing their workforces.

The study combines corporate AI spending data from Ramp's payment platform and workforce records from Revelio Labs to analyze more than 21,500 US companies, making it one of the biggest of its kind.

It concludes that high-intensity AI adopters increased their headcount by around 10% during the first two years after deploying AI, making AI good news for workers and labor after all.

AI adoption is causing companies to hire more workers

Clearly, only strong AI adoption has a positive impact on workers, because companies making modest investments didn't see any significant growth.

The study also stresses that the impacts are slow-growing – rather than seeing an immediate uptick in employment, it takes time for companies to integrate AI, discover productive use cases and hire more workers.

High adopters are defined as those who invested around $33 per employee per month during the first three months after adoption, compared with around $3 for low adopters.

It also challenges other recent research, asserting that entry-level employment actually rose by a higher-than-average 12% among high-intensity AI adopters. Other reports have implied that entry-level workers have been among the hardest hit.

Even though tech giants dominate the headlines, with Salesforce cutting nearly half of its support staff and Amazon notably cutting tens of thousands of workers, the Ramp/Revelio Labs report actually shows growth across more than just AI engineer roles, spanning sales, marketing, admin, finance, customer service and more.

While the research can't be used to predict long-term labor impacts, it does at least serve as a notice that workers aren't currently at risk of total redundancy, even amid job role shifts.