A recent study by Duke University’s Fuqua School of Business and the Federal Reserve Banks of Richmond and Atlanta highlights a gap between perceived and realized benefits of artificial intelligence in corporate performance. Based on a survey of nearly 750 executives, CFOs reported average productivity gains of 1.8% in 2025, driven by AI adoption. However, when measured against revenue and employment data, the actual impact appears more limited across industries through 2026.
This disconnect points to a “productivity paradox,” where operational improvements are visible internally but have yet to translate into stronger top-line growth. The findings suggest that while companies are increasing efficiency, financial outcomes remain delayed due to the gradual implementation and incomplete integration of AI systems.
For finance leaders, the results reinforce the importance of evaluating AI investments with a longer-term lens. Many organizations accelerated AI spending in late 2025, but benefits such as pricing adjustments and revenue expansion are still unfolding, indicating a potential one-year lag between deployment and measurable returns. Gains also vary by sector, with greater improvements in high-skill services like finance, while manufacturing and construction show slower progress. The study advises CFOs to adopt multi-year evaluation frameworks that capture sustained value creation rather than relying on short-term return metrics, ensuring disciplined investment decisions amid rising expectations around AI-driven performance.
