In 2023, IBM laid off nearly 8,000 employees—primarily from its HR division—as part of a cost-cutting and efficiency-boosting initiative powered by its AI platform, AskHR. This tool was designed to automate routine HR functions such as payroll management, leave approvals, and documentation. IBM aimed to automate 94% of HR tasks with this system, assuming human involvement would become largely unnecessary.

AI Can’t Replace Human Empathy
Despite the ambitious automation, IBM soon realized that the remaining 6% of tasks—those requiring emotional intelligence, discretion, and complex judgment—could not be handled by AI. The absence of human input led to growing inefficiencies, a decline in employee satisfaction, and service quality issues. AskHR lacked the empathy and nuance necessary for critical interactions, showing the limitations of AI in sensitive, people-centric domains.

IBM’s Rehiring and Strategic Shift
Ironically, IBM’s workforce did not shrink as expected. The company began rehiring to fill gaps left by automation, focusing on roles in software development, sales, marketing, and client relations—positions that demand creativity, critical thinking, and interpersonal skills. CEO Arvind Krishna emphasized that automation freed up resources, which were then reinvested in high-value human roles rather than being used just to cut costs.

Industry-Wide Implications and Lessons Learned
IBM’s experience sends a powerful message across industries. While automation enhances efficiency, it is not a complete replacement for human insight. Similar trends have been seen at other companies like Duolingo, which had to rehire staff after relying too heavily on AI chatbots. The AskHR platform, despite managing over 11.5 million employee interactions in 2024, still fell short in delivering the depth of human touch needed in HR.

The Future of AI and Human Collaboration
This episode reignites the debate on automation and its boundaries. AI is effective for repetitive tasks, but strategic, emotional, and complex decisions still need humans. As businesses race to embrace AI, IBM’s case stands as a reminder that the best results often come from a hybrid approach—leveraging AI for efficiency while preserving the irreplaceable value of human judgment.