Companies save cash with AI, but less than expected

A new Bain & Co. survey of 951 global companies reveals that most are falling short of their AI-driven cost-saving goals despite rising investments. Among those tracking savings, 37% aimed for 11%–20% reductions but only 29% succeeded, while 17% targeted 21%–30% savings, with just 10% reaching that level. Even companies expecting modest 10% or lower savings saw 40% fall into that category instead. Bain notes that while AI tools function, their value often fails to materialize, yet 90% of firms are still expanding budgets—this time toward more complex, autonomous AI agents. Currently, only 7% of surveyed companies deploy fully autonomous AI agents in production, despite executives envisioning end-to-end automation. Bain warns that misaligned expectations—such as CFOs approving projections that don’t match real-world performance—risk perpetuating inefficiencies. Nearly half (44%) plan to fund new AI investments using savings from prior automation programs, a strategy Bain calls unsustainable without proven returns. The survey highlights systemic barriers, with 41% of respondents citing inadequate data access and integration as the top obstacle. Bain points out the irony: despite global spending of hundreds of billions on data modernization over a decade, companies still struggle with fragmented systems. The firm advises prioritizing AI-driven workflow automation—such as replacing manual data consolidation and reporting—to unlock faster value. Bain’s report emphasizes that companies often overestimate AI’s immediate impact, particularly when relying on projections over actual performance. The pattern mirrors past automation waves, where unrealized savings led to repeated cycles of underdelivered returns. To break the trend, Bain recommends focusing AI on high-value, repeatable tasks where manual processes currently dominate, rather than waiting for data infrastructure to improve organically.