Governing AI Agents: Three Levers for Executive Control

A three-hour working session for leadership teams who have AI agents heading toward business-critical workflows — and who need a practical model for what "under control" means before the next budget round.

Audience: business leaders, technology leaders, risk and compliance leaders, and transformation sponsors. Groups of 6–14 work best; virtual or on-site.

Last reviewed: October 2026.

Learning objectives

Read an agentic AI initiative and see its control structure — objectives, boundaries, authority — in five minutes.
Ask the questions that separate a governed workflow from an impressive demo.
Evaluate a pilot proposal's evidence plan before approving a budget.
Leave with a shared vocabulary your technology, risk and business teams can actually use together.

The three levers

Rewards and objectives

What the workflow is actually optimising, and how that objective reads under pressure. Mis-set objectives are the quietest failure in agentic systems: the agent pursues the metric you wrote, not the outcome you meant. We work through how to state objectives that survive ambiguity — and how to detect when pursuit of them has gone wrong.

The product-management failure, in agent form: optimising the metric you wrote, not the outcome you meant.

Explicit prohibitions and constraints

What the workflow must never do, expressed where it can actually be enforced — machine-checkable policy, not a paragraph of instructions. The session covers what a checkable constraint looks like, and why 'the model was told not to' is not a control.

The security-engineering rule: a control that is not enforced is documentation.

Earned authority: permissions and escalation

How much authority the workflow has earned — bounded tool access, review gates, and escalation to named humans when confidence or policy requirements are not met. Authority grows with evidence, not enthusiasm.

Least privilege, applied to software that makes decisions: authority is granted on evidence and reviewed, like any access.

Format and preparation

Session

Three hours, interactive: short inputs, then worked scenarios on your own initiatives. Not a lecture.

Participants

6–14 people who own decisions about AI workflows. Mixed business / technology / risk groups get the most from it.

Preparation

A short pre-read and a 10-minute questionnaire so scenarios reflect your real initiatives, not generic examples. See a synthetic sample pre-read.

Sample agenda (3 hours)

30 min Framing and the three levers
60 min Scenario worked on your own initiative
15 min Break
45 min Threat-and-authority exercise
30 min Shortlist and next steps

Fee: scoped to preparation and customisation, quoted before you commit. Design-partner rate available for first cohorts in exchange for a candid debrief.

Example decision scenarios

The proposal that almost sent itself

A bid-desk agent drafts well. Marketing wants it to submit directly. What questions should the leadership team ask before anyone says yes — and what evidence would justify the next increment of authority?

The support tier that got cheaper

Triage moved to a model. Cost per ticket fell; two escalations per week go to the wrong team. Is that a quality problem, a routing problem, or an authority problem — and who decides when the exception rate is acceptable?

The vendor who promises control

A supplier's product sheet claims 'guardrails, RBAC and auditability'. What would you actually need to see demonstrated before signing, and what would you test in the first 30 days?

The email that gave the agent new instructions

A support agent reads inbound customer email. One message contains text addressed to the agent, not the human. What can it reach, what should stop it, and who finds out? What would you need to see before accepting that risk?

The launch the demo justified

The pilot's demo went well and the sponsor wants a full launch next quarter. What acceptance criteria would a disciplined product team set, and what evidence would separate "ready" from "impressive"?

What you leave with

A shared vocabulary for agent governance across technology, risk and business teams.
A set of risk questions to apply to every AI workflow proposal.
A shortlist of your workflows most worth assessing first.

Honest limits: a workshop does not make an organisation compliant, and it does not make autonomous operation safe. It gives leadership a model, a vocabulary and a shortlist — the assessment does the workflow-level work.

Your facilitator

Suman Kar, principal at Banbreach. 20 years in product security and incident response for firms; handled multiple databreaches; expert witness. 15 years of product experience from device drivers, to desktop apps, as well as SaaS with installed userbase in millions. They have run security and engineering leadership sessions for executive audiences" /> and will tailor the scenarios to your real initiatives.

Read the full biography

Enquire about the Executive Workshop

Who is the workshop for, and what decision are you working toward? We will confirm dates, preparation and whether the session should be virtual or on-site.