Dive Brief:
- The 2,000 largest public companies globally are collectively sitting on trillions of dollars in untapped value from artificial intelligence investments, with progress stymied by internal operational weaknesses such as poor data quality and inefficient processes, according to a report from technology firm Genpact and global research and advisory firm HFS Research.
- Many companies have yet to address the foundational problems limiting AI investment returns, the study released Monday found.
- “AI is exposing every weakness enterprises have spent decades learning to live with,” Phil Fersht, founder and CEO of HFS Research, said in a statement. “Poor process discipline, fragmented data, legacy technology and talent gaps are no longer operational nuisances. They are now direct barriers to growth, productivity and competitiveness.”
Dive Insight:
The study estimates that the world’s top 2,000 public companies collectively have nearly $18 trillion in unlocked value tied to unresolved “enterprise debt” — a combination of outdated technology, poor-quality data, inefficient processes and workforce readiness gaps.
HFS and Genpact said they calculated the aggregate value at stake by applying respondent-reported revenue uplift and cost reduction estimates across the combined revenue base of the Global 2000.
The report argues that technology, data, process and talent debts are interconnected and often reinforce one another. Poor data quality can hinder process improvements, while outdated technology can make it more difficult to deploy AI tools effectively. Workforce skill gaps further complicate efforts to address the other challenges.
“These interconnected enterprise debts do not appear on financial statements, yet they are quietly keeping agentic AI trapped in pilot purgatory,” the report said.
Organizations that successfully address these issues could achieve about 8% faster annual revenue growth and reduce costs by 16% annually, according to the study.
The research found that proven organizations do not address enterprise debt in a linear sequence. Instead, they operate at what the report calls “dual velocities,” working to fix foundational weaknesses while simultaneously pursuing higher-impact transformation initiatives.
The report notes that while these investments rarely deliver immediate quarterly results, they build the organizational capacity needed for other initiatives to scale and compound over time — balancing the CFO’s focus on near-term performance with the CEO’s mandate for longer-term transformation.
Eighty-five percent of leaders surveyed by HFS and Genpact said enterprise debt is actively constraining the value generated by AI initiatives, while more than half said their organizations lack a funded plan to address the issue.
Only 6% of respondents were classified as “proven debt resolvers” — organizations that have established, implemented and measured enterprise debt reduction programs at scale.
“Proven resolvers treat debt resolution and agentic transformation as one program, owned at the top, funded as a portfolio, and sequenced to build capability, not just fix visible pain,” the report said.
