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Decision context
The practical risk of an AI agent depends on what it can see, decide, communicate, change, approve, and execute, so governance must be designed around authority and consequence.
Dream Beyond Education
AI governance workshop
AI Governance & Agent Authority Workshop
The practical risk of an AI agent depends on what it can see, decide, communicate, change, approve, and execute, so governance must be designed around authority and consequence.
Education decision path
How AI Governance & Agent Authority Workshop moves from a live decision to a clearer next step
The sequence connects the program's decision context, learning outcomes, working agenda, and follow-on evidence.
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Decision context
The practical risk of an AI agent depends on what it can see, decide, communicate, change, approve, and execute, so governance must be designed around authority and consequence.
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Learning outcomes
This workshop gives business and technical stakeholders a shared method for deciding how much authority an AI agent should receive. Participants map a workflow, classify authority, define tools and permissions, identify approval points, establish identity and audit requirements, and plan human handoff and escalation.
- Classify proposed agents using the Dream Beyond 5-Level Agent Authority Model.
- Separate information access, recommendation authority, approval authority, and action authority.
- Define tools, permissions, identity, auditability, approval, escalation, and human handoff.
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Working agenda
The session moves through a defined sequence so participants can connect the operating problem to a clearer technology decision.
- Map workflow and consequence
- Classify agent authority
- Design control points
- Turn governance into a decision
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Follow-on evidence
A documented review of use cases, data readiness, authority boundaries, governance gaps, and implementation priorities.
- 5-Level Agent Authority Model
- Agent Authority Explorer
- AI Agent Authority research
The program clarifies decisions and next questions. Attendance, certifications, continuing-education credits, and implementation outcomes are never implied by this visual.
What participants should understand
Use the session to improve the decision before implementation begins.
This workshop gives business and technical stakeholders a shared method for deciding how much authority an AI agent should receive. Participants map a workflow, classify authority, define tools and permissions, identify approval points, establish identity and audit requirements, and plan human handoff and escalation.
Learning outcomes
A useful session should change the questions the team asks next.
- Classify proposed agents using the Dream Beyond 5-Level Agent Authority Model.
- Separate information access, recommendation authority, approval authority, and action authority.
- Define tools, permissions, identity, auditability, approval, escalation, and human handoff.
- Identify readiness gaps and conditions that should be satisfied before additional authority is granted.
Working agenda
Move from the operating problem to a clearer technology decision.
Map workflow and consequence
Document decisions, actions, systems, people, and failure consequences shaping the governance boundary.
Classify agent authority
Determine whether the agent observes, recommends, acts with approval, acts within boundaries, or receives delegated authority.
Design control points
Define access, tools, permissions, approvals, identity, logging, escalation, rollback, and human handoff.
Turn governance into a decision
Identify readiness gaps, pilot boundaries, ownership, and conditions for granting more authority.
Supporting authority
The curriculum is connected to published Dream Beyond research and working frameworks.
5-Level Agent Authority Model
The canonical authority model used to classify real agent responsibilities.
ExploreAgent Authority Explorer
An interactive technical demonstration of authority levels and control expectations.
ExploreAI Agent Authority research
Research on tools, permissions, autonomy, identity, approvals, and auditability.
ExploreFollow-on path
Turn learning into evidence when a real decision needs to be made.
AI Readiness & Agent Authority Assessment
A documented review of use cases, data readiness, authority boundaries, governance gaps, and implementation priorities.
Explore the next stepCommon questions
Is this primarily a policy workshop?
No. It connects governance to enforceable system design including tools, permissions, APIs, approvals, identity, logs, escalation, and fallback.
Does the workshop make an AI system compliant?
No. Compliance depends on the specific system, data, jurisdiction, contracts, security controls, operating procedures, and appropriate review.
Request the session
Design the workshop around the decision your team is facing.
Share the audience and the decision or learning goal. Dream Beyond can then determine whether this program, a different education track, or a more evidence-based assessment is the right next step.