Recent research conducted by the global EY organization, in collaboration with Oxford Economics, highlights a persistent artificial intelligence (AI) return on investment (ROI) trap. Many organizations remain stuck in pilots and point solutions, without end-to-end process redesign, mature governance or suitable KPIs. Architecture choices are pragmatic. Only a small minority of organizations are building their own large language models (LLMs), while most rely on external or hybrid models to move faster and reduce risk.

The new EY Technology Insights series outlines a practical execution agenda: Scale AI through processes not tools, strengthen governance, define and measure value, invest in AI-ready data and use AI to support AI governance, always with humans involved.

People and operating model shifts remain critical. Fewer than half of technology leaders feel confident in assessing AI readiness, underscoring the need for a dual-track approach that lifts productivity now while redesigning roles, workflows and culture for an AI-native future.

Explore how leading organizations are turning ambition into enterprise-scale results.