Decidr US AI Readiness Index 2026: high conviction, real investment, a gap that's defining the next phase
Decidr today released its US AI Readiness Index Report 2026, a current snapshot of AI adoption across American businesses that shows strong momentum but uneven readiness.
Based on a February 2026 survey of 1,226 decision-makers, the report tracks where businesses are investing, how urgently they're moving, and how security and compliance, integration, and skills gaps continue to stand in the way.
Investment is flowing, urgency is high, and the expectation of what AI can deliver over the next twelve months is stronger than it has ever been.
The research also surfaces three risks that will define the next phase of AI adoption: tool sprawl, operational brittleness and an execution gap that widens the longer investment outpaces infrastructure.
"The question keeping executives up at night isn't whether AI matters anymore. It's how to actually make it work," said David Brudenall, Co-CEO of Decidr.
The Index finds:
- 80% are already investing in people or projects committed to driving AI use in the business
- 88% expect AI to have a greater impact over the next 12 months
- 68% of current AI value still comes from assistants and copilots
- 73% of businesses experience delays because critical knowledge lives with too few people
The barriers slowing progress aren't a lack of belief — they're practical: security and compliance concerns (31%), data quality (26%), budget constraints (25%) and unclear ROI (22%). None of them are unique to AI. But none of them yield to another productivity tool either.
While eight in ten American businesses actively investing in AI, most of the value they're getting still comes from chatbots and copilots helping individuals work faster, not from AI running inside the business itself, which is
Beneath those barriers sits a structural problem the report flags as one of its most important findings: critical process knowledge lives in people's heads rather than in systems.
Workflows aren't documented, handoffs aren't visible, and decisions depend on whoever happens to know how things work. That's a problem that predates AI — but one that determines whether AI can scale.
The report segments the market into four readiness profiles.
- Trailblazers (26%) are already moving AI into their operating infrastructure.
- White Knucklers (21%) have the urgency and the strategy but are meeting heavy friction in execution.
- Tinkerers (33%) — the largest group — are experimenting across specific workflows without a formal operating model.
- Sleepwalkers (20%) are yet to find a practical entry point.
The 54% in the middle two categories represent the defining challenge of the current market: genuine intent, limited execution.
The pattern holds at enterprise level too. Larger businesses are further ahead on confidence and strategy — 92% say they understand what AI can do, and 69% have a clear roadmap — but 55% still say implementation would be difficult, higher than the SME figure of 46%.
The report argues the next phase of adoption will be won by businesses that move beyond tool use and build the operational foundation for AI to work at scale: documented workflows, connected data and orchestration that ties it all together.
"American businesses have crossed the hardest threshold — they've committed," said Brudenall. "The organisations that build the right operational foundation now are the ones that will outperform with AI, not just use it."
