What's Happening?
A recent EY-Parthenon survey indicates that while artificial intelligence (AI) is boosting productivity across companies globally, many chief executives are finding it difficult to translate these efficiency gains into higher profits and sustainable growth.
The report emphasizes that the true benefit of AI lies not merely in cost reduction but in achieving greater and improved output. Key drivers of productivity identified include AI-enabled tools and redesigned workflows, with the most significant results observed when new technologies are integrated into fundamentally reworked processes rather than simply added to existing systems. Despite nearly all CEOs reporting productivity gains over the past year, almost a quarter noted that these benefits were being absorbed by operational complexity, regulatory demands, risk management, and increased workloads. This raises questions about companies' ability to convert technological advancements into lasting business value, especially as executives navigate slowing economic growth, geopolitical uncertainties, and rapid technological shifts.
Why It's Important?
The struggle to convert AI-driven productivity into tangible growth and profit has significant implications for U.S. industries and the broader economy. If companies cannot effectively leverage AI for sustained financial improvement, the anticipated economic boost from AI adoption may be diminished. This challenge affects various stakeholders: businesses risk falling behind competitors who successfully integrate AI for strategic growth, while investors may see lower returns if efficiency gains don't translate into bottom-line improvements. The report highlights a potential 'productivity divide' between organizations that strategically reinvest their newfound capacity and those that allow it to be lost in complexity. This could lead to a widening gap in market leadership and profitability, impacting employment trends and the overall economic landscape as companies grapple with where to invest and how to position themselves for growth in a volatile environment.
What's Next?
Companies are faced with critical decisions regarding their AI strategies. EY suggests that future productivity gains will depend on businesses redesigning their operating models, reorganizing work, and deliberately redirecting the capacity created by AI. This includes measuring outcomes rather than just technology adoption, streamlining workflows, and pre-determining how productivity gains will fund expansion, innovation, workforce development, or shareholder returns. A significant challenge lies in the financial case for AI, as only 16% of CEOs have detailed, real-time visibility into AI costs and high confidence in assessing returns on investment. Without clear financial metrics, AI projects risk meeting technical goals but weakening business performance. Addressing skills shortages is also crucial, as 47% of CEOs believe their organizations are not developing skills fast enough, and 72% expect skills shortages to be a greater barrier to growth than capital access within three years.
Beyond the Headlines
The report touches upon deeper implications, particularly concerning employment and workforce development. Four out of five CEOs anticipate AI will have a greater impact on job roles, skills, and work organization than on overall workforce size in the next three years. This suggests a shift where AI agents perform more duties independently, leading to tasks being separated from traditional job roles and workflows being reorganized. While this could enable growth with fewer employees, it necessitates significant adaptation of operating models. The ethical and cultural dimensions involve ensuring employees understand the consequences of automation and providing genuine training pathways and employment opportunities. The 'skills challenge' extends beyond hiring AI specialists to developing domain experts, managers capable of overseeing AI, and employees who can critically use AI. This calls for a continuous reinvestment cycle in both technology and human capital, emphasizing the importance of combining foundational, digital, and complementary skills with organizational capacity.
