Companies rethink AI rollouts as errors and costs mount

Businesses that moved quickly to adopt AI are scaling back some initiatives as errors, low-quality output and rising costs undermine expected benefits. Meta has reduced plans to replace staff with agents after employees spent increasing amounts of time fixing technical and security problems, Reuters reported. Microsoft and McKinsey are limiting employee usage amid cost pressures, while Palantir, Booz Allen Hamilton and Nvidia have imposed restrictions over data security concerns.

Evidence of broad productivity gains remains limited. An Atlanta Federal Reserve working paper found that 90% of executives said AI efforts had yet to improve productivity at their companies. An Ernst & Young survey found that 36% of senior AI executives at companies with at least $1bn in annual revenue reported incidents involving consequences such as data loss, financial damage or operational disruption.

Training and oversight gaps are complicating deployment. Just 45% of managers surveyed by Indeed felt equipped to lead employees proficient in AI. Microsoft found that adding agents to flawed processes did not fix underlying problems, while pairing early-career engineers with experienced colleagues improved productivity. Employers are increasingly turning toward sustained, role-specific training.

Workers also face unreliable automated management. Walmart employees described inefficient fulfilment routes, false safety alerts and unrealistic schedules, according to Business Insider. Research from the University of Pittsburgh found that productivity did not rise after companies invested in AI and cut staff, challenging expectations that automation-driven layoffs would improve performance.