Eight major institutions published AI research for this year. Consultancies, a university, two vendors, a lab. Different methods, different samples, different incentives. They converge on one finding: the barrier to AI value is not the technology. It is the operating model around it.
Here is the list, with the one thing each report earns its place with.
BCG, AI Radar 2026. AI spending set to double, from 0.8 to about 1.7 percent of revenues, and nearly three-quarters of CEOs now the key AI decision maker. The gap: 62 percent of CEOs confident AI will pay off against 48 percent below the C-suite.
Deloitte, State of AI in the Enterprise 2026. Three adoption levels: 34 percent deep transformation, 30 percent process redesign, 37 percent surface deployment. Only the first reimagines the business rather than optimizing what exists. Governance is, in their words, the difference between scaling and stalling out.
Stanford HAI, The 2026 AI Index Report. The evidence base of the list, nine chapters, from research and development through policy and governance to public opinion. When you need the number rather than the narrative, it is usually in here.
McKinsey, Building the foundations for agentic AI at scale. Eight in ten companies call data a roadblock. The prescription, read closely, is governance: controls embedded not retrofitted, execution coordinated through layers that enforce rules.
IBM, 2026 Tech Leader Study. The control gap in hard numbers: 77 percent say adoption outpaces governance, two-thirds answer for systems they do not fully control, 54 agent incidents a year on average. And the counterweight: embedded controls correlate with 16 times more deployed agents.
Accenture with Wharton, The Age of Co-intelligence. Built on task-level analysis across 18 industries and more than 120 million workers. Its lasting line, as Fortune put it: intelligence may be scalable, accountability is not.
Microsoft, 2026 Work Trend Index. Active agents up 15-fold in a year, 18-fold in large enterprises. The organizational environment is associated with about twice the AI impact of individual mindset and behavior.
Anthropic, The 2026 State of AI Agents Report. The lab's own field view of agent deployments, with 80 percent of organizations reporting measurable ROI.
Read them all, or accept the compressed version: governance, data, accountability, workforce, process. Five foundations, none of them a model.
Our closing observation, from the EU seat: everything on that list that the reports recommend, the AI Act requires. Oversight, logging, transparency, AI literacy, named responsibility. AI literacy has applied since 2 February 2025, transparency since 2 August 2026, and the Annex III high-risk obligations land on 2 December 2027. The reading list and the legal text have converged. That should make the decision easier, not harder.
We turn the overlap into documents. klariq.eu.