AI must become more cost-effective
Just because AI can perform a task doesn’t mean it makes financial sense for a business to automate it. Beyond the technology itself, companies must invest in implementation, employee training, compliance, cybersecurity and ongoing oversight. Those costs can add up quickly. In fact, one MIT study that investigated the relative cost of deploying AI on tasks using computer vision systems found that while 36% of occupations included at least one task that could technically be automated, only 8% included a task that was economical to automate at scale. In other words, being able to automate a task doesn’t necessarily mean it makes financial sense to do so.
AI can deliver savings on routine work such as summarizing documents, drafting emails, and extracting information. But costs rise significantly when tasks require complex reasoning, planning or decision-making. At the same time, businesses face uncertainty around the future cost of AI infrastructure, computing power and specialized hardware.
The result: while AI adoption continues to grow, the current business case for replacing large numbers of workers is much weaker than the case for using AI to help humans work more efficiently.
AI adoption would have to greatly accelerate
While consumers have embraced AI quickly, regular adoption across businesses has been much slower. Many companies are still experimenting with the technology, and day-to-day use largely depends on the industry.
That slower pace matters. AI is increasingly being used to support existing workflows rather than replace them, giving workers and businesses more time to adapt. Economic constraints, implementation challenges and industry-specific needs are all likely to slow widespread adoption.
Labor markets are constantly evolving, with jobs created and eliminated every year as businesses grow, shrink and adopt new technologies. Some job impacts have occurred, especially in positions that are easier to automate.
Currently, many employers are adjusting by scaling down hiring instead of implementing widespread layoffs. According to the report, this adjustment is primarily affecting younger workers entering the job market, who are finding fewer entry-level opportunities.
For AI to drive large-scale job losses, adoption would need to happen much faster than these normal adjustment processes. So far, employment trends suggest that transition remains gradual rather than disruptive.
At the same time, AI is creating demand for new skills and careers. Growth in AI infrastructure, data centers and related industries is already generating jobs, showing how technological change can create new work even as it transforms existing ones.
“The ultimate employment impact depends not just on the jobs displaced, but also on the economy’s ability to create and absorb workers into new ones,” noted Rannella and Thomas in their report.
What this means for the American workforce
AI’s capabilities and impacts change nearly every day, so concerns about how it will affect the job market aren’t likely to end until more is known about i’s true feasibility as a work tool.
For now, the evidence suggests AI is more likely to reshape how people work than eliminate large numbers of jobs. As businesses continue experimenting with the technology, its effect on the workforce will depend in part on how people learn to use it and how effectively the economy creates new opportunities.
The bottom line for future of work: “There will be a gradual change, rather than a rapid and significant disruption,” said Rannella and Thomas.