Agentic AI has been trending for almost two years, and deployment continues to rise.
Anthropic’s “2026 State of AI Agents” report, for example, stated that 57% of the 500 U.S. companies surveyed were deploying agents for multi-stage workflows, and 56% planned to deploy agents for research and reporting in 2026.
Coding agents seem to be the fastest-growing agentic AI use case so far. An OpenAI paper from a few days ago found that the number of active Codex users had grown more than fivefold in the first half of 2026.
From an AI governance perspective, increased autonomy, access rights, and integration layers introduce new risks and vulnerabilities that do not seem to be fully acknowledged or addressed by most companies deploying AI agents today.
According to this Deloitte report, while 74% of companies plan to deploy agentic AI within two years, only 21% of organizations have a mature model for governing autonomous AI agents.
Bad AI governance is bad for business, and companies know it.
A PwC survey asked the question, “What challenges are getting in the way of realizing value from AI agents?” Among the top-ranked reasons were cybersecurity, lack of trust in AI agents, human oversight, accountability, compliance, and legal concerns.
With that in mind, and to support companies’ agentic AI governance efforts, today I’m launching my AI Policy Masterclass on Agentic AI Governance, based on Singapore’s Model AI Governance Framework for Agentic AI, the world’s first framework in this area, which was updated last month.
This Masterclass and the accompanying reading list will be available to paid subscribers until August 2.
👉 You can find the recommended reading list for this Masterclass here.
