A vital question for organizations is: How do they measure success? As companies grow larger and more complex, determining what metrics to use to evaluate performance gets harder.

Traditionally, defining key performance indicators, or KPIs, has been the job of senior executives, who relied on their own judgement, intuition, and experience. But legacy KPIs often score performance on suboptimal or even wrong measures. As companies amass ever-larger, more diverse sets of data, legacy metrics based primarily on human judgment will be less and less likely to align performance dynamics with desired outcomes. KPIs need to become smarter.

AI can help by allowing companies to use their own data to better understand what drives performance. In the process, AI can also change how organizations measure, analyze, and align performance, replacing static, legacy metrics with dynamic, smart KPIs that offer more detailed and accurate descriptions of what is actually going on in a business and what is likely to happen next.

To understand how executives are using AI to improve strategic measurement and outcomes, and how their organizations have adapted to AI-enabled KPIs, Boston Consulting Group (BCG) and MIT Sloan Management Review teamed up to conduct a global survey of over 3,000 managers representing more than 25 industries across 100 countries. We also conducted 17 executive interviews to gain greater context and insight into the experience of individual firms using AI to transform their KPIs.

Our research found that leaders who use AI to prioritize, organize, and share KPIs see improved alignment across units or functions, which in turn drives better overall results. Smarter KPIs can operate as an organizational GPS of sorts, streamlining decision-making and impetus across teams. But how do companies use AI to create and manage new smart KPIs?