Governing AI Agents Like Teammates

​𝐆𝐨𝐯𝐞𝐫𝐧𝐢𝐧𝐠 𝐀𝐈 𝐀𝐠𝐞𝐧𝐭𝐬 𝐋𝐢𝐤𝐞 𝐓𝐞𝐚𝐦𝐦𝐚𝐭𝐞𝐬
You buy the licenses, flip the switch, and productivity follows — that's the SaaS playbook enterprises have run for two decades.

Agentic AI breaks it.

Agentic AI demos often look flawless: an agent triages a ticket, updates the CRM, drafts a proposal, and routes it for approval — all in seconds. Then someone asks how fast this can roll out everywhere. That's exactly the moment the risk begins.

Unlike an AI assistant or a copilot, which only carries content risk (a bad draft, a hallucinated fact), an AI agent takes action inside your systems — updating records, issuing payments, changing live data.
That's the 𝐬𝐡𝐢𝐟𝐭 𝐟𝐫𝐨𝐦 𝐜𝐨𝐧𝐭𝐞𝐧𝐭 𝐫𝐢𝐬𝐤 𝐭𝐨 𝐞𝐱𝐞𝐜𝐮𝐭𝐢𝐨𝐧 𝐫𝐢𝐬k, and it changes everything about how these systems need to be identified, monitored, and governed.

This session — grounded in HBR research on the operational, security, and legal gaps pening up in agentic AI deployments — makes the case for managing AI agents like a workforce, not installing them like software.

https://hbr.org/2026/03/to-scale-ai-agents-successfully-think-of-them-like-team-members

𝐖𝐡𝐚𝐭 𝐲𝐨𝐮'𝐥𝐥 𝐥𝐞𝐚𝐫𝐧:
-> Why traditional QA assumes deterministic software (same input, same output)--> and why probabilistic agents break that testing playbook entirely
-> How shared, broad-access service accounts recreate the exact failure mode that let one coding agent wipe a production database
-> What "context poisoning" looks like in practice — how one outdated-but-accurate document can trigger a company-wide compliance failure
-> Second-order prompt injection: how a malicious instruction picked up by a customer-facing agent gets trusted and executed by an internal agent with real database access
-> The "deterministic cage" pattern — letting AI reason over messy input while a hard-coded rules layer gates every action before execution
-> The autonomy ladder — a four-stage framework for scaling agent authority deliberately, with real examples of where companies like Klarna drew their escalation boundaries

𝐖𝐡𝐨 𝐬𝐡𝐨𝐮𝐥𝐝 𝐚𝐭𝐭𝐞𝐧𝐝:
Technology and business leaders provisioning agent access and identity. Engineering and platform teams building agentic workflows. Compliance and legal teams assessing liability exposure. Executives setting the pace of AI adoption.
If you've watched a flawless agent demo and wondered what happens when it hits your real data, your real systems, and your real regulatory exposure — this one's for you.