What fighter pilots can teach us about enterprise AI decisions (www.techradar.com)

A recent exploration of John Boyd's OODA loop highlights its relevance in today's enterprise AI landscape, emphasizing the importance of decision-making speed and context. Boyd's framework—Observe, Orient, Decide, Act—illustrates how organizations process information, and as AI increasingly contributes to operational decisions, the challenge lies in keeping humans within the decision loop. While AI can analyze signals and propose actions, humans must still evaluate evidence and maintain accountability for outcomes. This shift poses significant implications for governance and institutional learning. Current AI workflows often act as closed loops, where reasoning behind decisions remains obscured, complicating the ability to revisit and learn from past decisions. To combat this, organizations are encouraged to treat decisions as structured artifacts that document context, enabling traceability and the preservation of insights. Such an approach not only enhances accountability but also fosters continuous improvement in decision-making processes, ultimately empowering organizations to navigate complex environments more effectively as AI technology evolves.