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In a researcher’s test, one prompt was enough to take over every AgentCore agent in an AWS account region because the default role was too broad, and OpenAI found its own agents weakening the monitoring meant to watch them. Here are seven controls an AI workflow needs before anyone relies on it. Part 2 of Pilot to Production.
Half of Gartner’s top strategic technology trends for 2027 describe controls, not capabilities. Turn AI agent identity, coding agent harnesses, exposure remediation, context platforms and SovereignTech into five questions your estate should answer with evidence, and score yourself.
AI programmes rarely stall because the migration failed. They stall because the migration programme was quietly the operating model, and it ended. The case for a permanent platform team.
The major payment networks have spent the past year building rails so AI agents can pay as principals rather than tools. Before an agent is connected to a payment rail, enterprises need spend authority, scoped identity, auditability, and a hard stop – controls most have never had to build.
Enterprises have bought GPUs faster than they can use them, and much of that expensive compute now sits idle waiting on fragmented, ungoverned data. Here is why the AI bottleneck has moved from compute to data readiness, and what fixing the data layer actually requires.
Two AI agent breaches in five days – one through Hugging Face’s production infrastructure, one out of a supposedly isolated OpenAI test environment – show why containment built for humans and static code no longer holds. Here is what architectural governance fixes before an incident does it for you.
A survey of 107 enterprises found 69% let AI agents share credentials and 54% have already had an agent security incident or near-miss. Giving every agent its own scoped identity roughly halves the exposure – here is what good agent identity governance looks like.
Satya Nadella’s call for every firm to control its own learning loop is a warning about where AI value really flows. Your prompts, corrections and agent workflows are quietly teaching your provider’s model – here is how to keep that learning as an asset you own.
Leading AI models have converged into a utility, so advantage no longer comes from which model you buy but from getting it to run inside your own systems, data and approval chains. Vertex Agility CEO Mark Beard on why pilots die, why regulated businesses will pull ahead, and the one honest test of a real AI capability.
In June 2026 the most capable AI models began shipping through a government gate. Model risk is now a continuity and third-party-risk issue no SLA covers – here is how to build a portable, resilient model strategy.
Line-of-business software is moving inside the governed data platform, turning it into an application platform by default. Where your AI agents run is now a first-order strategy decision, and a hidden source of vendor lock-in.
