Closing the AI ambition gap: From executive priority to enterprise value

AI has won executive attention. But it’s yet to win a place in the operating model.

Artificial intelligence (AI) has moved decisively onto the business agenda. Global research from Argon & Co found that 43% of respondents consider AI significantly or very significantly material to their organisation’s success, rising to nearly seven in ten among executive functions. Even outside the executive team, 85% see AI as at least partially material. Yet organisational maturity has not kept pace with this confidence.

Almost one-third of respondents are running pilots or proofs of concept with mixed results. A further 26% are creating value through individual use cases but struggling to scale, while a quarter are still exploring tools and ideas without knowing where to focus. Only 9% say AI is embedded into core business processes and delivering measurable value.

The more consequential gap is between ambition and execution. Only 9% of respondents have a clear AI strategy with defined build-versus-buy decisions, while more than half of AI initiatives are led by Data and AI or IT teams rather than the business functions responsible for the outcomes they are intended to improve.

Closing this gap requires organisations to define business outcomes, redesign processes and decisions, establish trustworthy data and governance, and create shared accountability across business and technical teams.

The challenge is to turn AI from a series of promising applications into an enterprise capability that consistently delivers measurable value.