You can’t build your AI future on broken foundations

A joint study by Genpact and HFS Research surveyed over 2,000 enterprise executives, revealing that 85% of leaders believe their existing foundational elements—fragmented data, ungoverned processes, aging systems, and undertrained talent—are hindering their AI initiatives. Enterprises are allocating an average of 13% of their functional spend to AI, yet the underlying infrastructure is not prepared to support these investments. The research highlights four key areas of "enterprise debt" that collectively create a structural failure for AI adoption. Technology debt is significant, with core systems averaging 10 years in age, diverting developer time to maintenance rather than AI development. Data debt is prevalent, as most functional data is not AI-ready, requiring extensive reconciliation and preparation efforts. Process debt is evident, with 50% of enterprise processes needing manual intervention from start to finish, making reliable automation impossible without defined workflows. Finally, talent debt arises as broken systems force knowledge workers to spend their time managing dysfunction rather than focusing on decision-making and innovation.