{"id":17410,"date":"2026-07-22T13:00:26","date_gmt":"2026-07-22T11:00:26","guid":{"rendered":"https:\/\/tricise.com\/?p=17410"},"modified":"2026-07-22T17:07:16","modified_gmt":"2026-07-22T15:07:16","slug":"governed-orchestration-automic-v26","status":"publish","type":"post","link":"https:\/\/tricise.com\/fr\/governed-orchestration-automic-v26\/","title":{"rendered":"Governed Orchestration: Making Agentic AI Operational With Automic V26"},"content":{"rendered":"
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Broadcom and Enterprise Management Associates (EMA) ran a joint webinar on 6 July 2026 called Making Agentic AI Operational<\/em>, and its central claim is governed orchestration: embedding AI-driven decisions inside workflows that are already auditable and policy-bound. The framing inverts the usual pitch, because it treats the barrier to enterprise AI as operational trust rather than model capability. The session is now available on demand, and it is worth an hour whether or not V26 is already on your roadmap.<\/p>

What governed orchestration actually means<\/h3>

The session pairs Dan Twing, President and COO at EMA, with Automic product manager Kaj Wierda, drawing on EMA research<\/strong><\/a> and the Automic V26 release. The through-line is unglamorous and correct: most organisations already orchestrate ITOps scheduling, DevOps pipelines and DataOps\/MLOps workflows across mainframe, distributed and hybrid environments. The safe route into AI is therefore to extend that existing orchestration, governance and execution over AI agents and APIs, not to stand up a parallel stack beside it. Broadcom’s own phrasing is that workload automation is evolving from scheduling into a broader enterprise control layer.<\/p>

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Why it matters to your Automic V26 decision<\/h3>

If Automic V26 is on your roadmap, this is the strategic case for it. Agentic AI, APIs and orchestration are converging, and governed orchestration is how you keep human oversight, auditability and rollback while letting AI take on real work.<\/p>

In V26 that principle has a concrete shape. AI-driven decision-making is wrapped in the role-based access controls, audit trail and security protocols the platform already enforces, so an autonomous remediation step answers to the same rules as any scheduled job. There is no separate regime to police; the existing controls simply extend to a new object type.<\/p>

5 questions to answer <\/span>before you switch it on<\/span><\/h3>

The direction of travel here is clear enough. What varies is how fast any given estate can follow it. A platform can offer governed AI execution on day one; whether your team can approve, audit and roll back an autonomous action on day one depends on your policies rather than your release version.<\/p>

EMA’s research is blunt about why that matters. Roughly 30% of organisations report hitting incorrect or problematic AI outcomes frequently, and more than 75% have already had to correct or roll back an AI-driven action. Worth settling first:<\/p>