AI adoption is accelerating and governance is still catching up. AI agents are moving from concept to real-world deployment, now acting within workflows and making decisions on behalf of organizations. As their role expands, clarity around authority and oversight is becoming essential. Our latest report with the World Economic Forum introduces the Agent Capability and Authorization Profile (ACAP): a framework to bring structure and consistency to how AI agents are deployed and governed. It enables organizations to make delegated action explicit, auditable, and scalable, moving from isolated pilots to more controlled, enterprise-wide adoption. The question is no longer what AI can do, it’s how we govern it at scale. Read ‘AI Agents in Action: A playbook for trusted adoption, authorization and scaling’: https://bit.ly/3PYasLv #WEF #MakeItReal
La gouvernance est souvent le parent pauvre des déploiements IA. Dans des secteurs comme la sécurité physique, où les agents IA prennent des décisions en temps réel (détection d'intrusion, levée de doute automatique), le cadre ACAP répond à une vraie question de responsabilité. Qui valide l'action de l'agent quand une alarme se déclenche à 3h du matin sur un site distant ?
The bottleneck isn't capability, it's authorization. We've been building automated workflows for years (welcome series, cart abandonment, churn prevention) that act on behalf of organizations without ever formalizing delegation rules. What can the system decide alone? What needs a human checkpoint? The ACAP framework introduced here, scope, authority, consequential events, controls, is the structure most automation projects are missing. Before scaling agents, clarify governance. That's where trust is built.
AI adoption challenges are increasingly becoming governance challenges. As autonomous systems gain authority, the critical question shifts from capability to decision structure, escalation paths, and execution consistency. At scale, organizations rarely fail because of intelligence limitations. They fail because governance cannot keep pace with delegated decision-making . Execution ultimately depends on decision architecture.
Many organizations are discovering that scaling AI isn't just a technology challenge but it's a governance challenge. Frameworks that make AI actions explicit and auditable will play a key role in enterprise-wide adoption.
Love the focus on clear authority that’s what unlocks adoption.
Very relevant. The governance of AI agents is becoming a central issue as their autonomy increases. The ACAP framework provides a structured and essential approach to scaling with confidence.
Well said ! Nobody can deny that the hype of AI was frustrating for most of us . But , the question is no longer about AI replacing automated tasks or jobs , it’s about the ethics and how we can govern the use of our data .
This feels like one of the most important conversations in AI right now. The challenge is no longer whether agents can take action, it's how organizations define what they are allowed to do, under what conditions, and with what level of oversight. As AI agents move deeper into business workflows, governance becomes less about model safety and more about authorization, accountability, and auditability. The organizations that scale agentic AI successfully will likely be the ones that treat governance as infrastructure, not an afterthought.
The framing here lands the question precisely. The shift from "what AI can do" to "how we govern it at scale" is the architectural inflection of 2026. ACAP names the policy layer. Authorization profiles, delegated action boundaries, audit-grade traceability. The architectural question that follows is where ACAP-compliant behavior actually gets enforced at runtime. Profiles describe what agents may do. The orchestration layer underneath is what makes that enforceable across the systems, workflows, and humans that the agent has to interact with. Policy without execution is documentation. Execution without policy is risk. ACAP gives the policy. The orchestration layer makes it operational. Strong reference point for the agent governance conversation.