IBM survey reveals the gap between AI investment and business results

IBM‘s survey of 2,000 CEOs reveals a significant reality gap in AI investment outcomes, with just 25% of initiatives delivering expected returns. Despite this shortfall, enterprises are doubling down on AI investments over the next two years, particularly in AI agents that can automate entire tasks across multiple systems. This dichotomy between underwhelming results and accelerating investment highlights both the fear of missing out driving corporate AI strategies and the complex implementation challenges enterprises face.

The big picture: Only a quarter of AI initiatives have delivered the expected return on investment according to IBM’s survey, revealing a stark contrast between AI hype and business reality.

• Despite 75% of AI investments underperforming, CEOs expect to more than double their AI investment growth rate over the next two years.
• Just 16% of enterprise AI initiatives have successfully scaled across entire organizations, indicating widespread deployment challenges.

Key drivers: Fear of missing out is pushing nearly two-thirds of companies to adopt AI technologies before determining their actual business value.

• 64% of respondents admitted their organizations have adopted technologies before figuring out whether they’ll actually benefit the business.
• Despite implementation challenges, 85% of surveyed executives remain optimistic their GenAI investments will eventually pay off, though most believe it will take at least two more years.

Current adoption limitations: Most enterprises are implementing AI in highly targeted ways rather than transformative enterprise-wide deployments.

• 65% of CEOs are prioritizing AI use cases based on potential return on investment rather than broader strategic considerations.
• Half of respondents report struggling with a growing tangle of disconnected or piecemeal AI technologies.

Beyond cost-cutting: Just over half (52%) of CEOs report their organizations are realizing value from GenAI investments beyond simple cost reduction.

• 61% of executives say they’re already adopting AI agents – systems that automate entire tasks by connecting multiple tools, models and data sources.
• These agent systems operate with varying degrees of human oversight, representing a more sophisticated approach than traditional chatbots or image generators.

Implementation challenges: Organizations face significant technical, financial and human resource obstacles in scaling their AI initiatives.

• The high cost of AI hardware, whether cloud-based or on-premises, remains a persistent barrier to implementation.
• More than half of participants struggle to balance funding existing operations with investing in innovation when unexpected changes occur.

Workforce implications: AI adoption is creating significant changes in enterprise staffing requirements and skill needs.

• More than half of surveyed CEOs report hiring for entirely new AI-related positions that didn’t exist a year ago.
• The study suggests over a third of the broader workforce may need retraining or reskilling within the next three years to support AI initiatives.