As IT/BPO firms embraced AI and trimmed their workforce, initial savings were increasingly redirected into AI infrastructure requiring constant maintenance and upgrades. Charles Liu, CEO at Cubic Promote, argued, “I believe some organisations are now spending as much, or even more, on AI than they previously spent on the employees they replaced.” Bryan Catanzaro, VP of Applied Deep Learning at Nvidia, told Axios: “For my team, the cost of compute is far beyond the costs of the employees.” Miki Furman, CTO of Call Force Global, which operates in Jamaica, Trinidad, Belize, and Colombia, said, “So yes, on some workflows AI now costs more than the labor it was supposed to save.” Kuber Sharma, Senior Director at UiPath, noted that organizations routinely leave ongoing maintenance work off the AI side of the ledger, adding, “Models drift, edge cases accumulate, and someone has to own the ongoing engineering work.” Jacob Ferguson, President of Ferguson Industrial Company, cited hidden costs including “Data preparation, monitoring, cybersecurity, compliance, and integrating AI into existing workflows.” Liu concluded, “Training and maintaining an AI system can be more expensive and demanding than training an employee.” As companies deployed more AI tools, operating expenses rose, and at call centers, higher call volume increased AI costs.