Most Companies still struggle to turn strategy into action. Our interviews with 20+ C-suite leaders reveal four selfreinforcing gaps: fragmented language, ad-hoc processes, static tools and inadequate capabilities, all reinforcing each other into what we call “the Strategy Chasm”. We show that these gaps violate Ashby's law of requisite variety: the business environment is more complex than the organisation's ability to respond. We prescribe a dual fix. First, a universal, machine-readable Strategy Ontology that distils half a century of research and practice into a common language. Second, AI strategy co-pilots, built on knowledge graphs which converts the universal strategy ontology in a machine-readable standard, and linked to LLM agents which can proficiently process language. This is a technical architecture which has already been implemented in other knowledge-intensive sectors where standard ontologies exist (e.g. legal services or pharmaceutical research). The strategy co-pilots amplify managerial insight, synthesising context, critiquing drafts and suggesting strategic options in real time. With this paper, we suggest design principles for the Strategy Ontology and a visual representation: the Strategy in Action Canvas. The result is a scafolding for a computable, continuously learning, strategy system that compresses planning cycles from months to days.
The author(s) have not employed any Generative AI tools.