Role-Based Programme
RB0595

Microsoft Copilot Studio for Risk & Internal Audit

Build Governed AI Agents for Risk, Controls & Audit Workflows

IMAGE REQUIRED
Duration
8 Hours
Level
Basic
Delivery
Instructor-Led
Format
Workshop

Programme Objectives

  • Build foundational proficiency in using Copilot Studio for risk-management and internal-audit support scenarios.
  • Create agents grounded in approved policies, control frameworks, procedures, audit guidance, and organizational knowledge.
  • Apply structured topics, generative orchestration, tools, and agent flows to support repeatable risk and audit processes.
  • Use evaluation and analytics to assess agent quality, identify weak responses, and improve reliability.
  • Understand governance, access control, data protection, human approval, and evidence-validation requirements for risk-sensitive AI workflows.

Tools covered

Microsoft Copilot StudioGenerative OrchestrationTopicsKnowledge SourcesSharePointDataverseTools & ConnectorsAgent FlowsEvent TriggersEvaluationAnalyticsPower Platform EnvironmentsData Policies

Who should attend

  • Risk Managers
  • Enterprise Risk Management Professionals
  • Internal Audit Managers
  • Internal Auditors
  • Risk Analysts
  • Control Assurance Professionals
  • Compliance Risk Professionals
  • Operational Risk Professionals
  • Technology Risk Professionals
  • IT Audit Professionals
  • Governance, Risk & Control Professionals
  • Audit & Risk Transformation Professionals

Prerequisites & Participant Readiness

  • Basic understanding of risk-management or internal-audit processes
  • Familiarity with policies, controls, findings, evidence, and remediation activities
  • Basic understanding of generative AI concepts is helpful
  • Familiarity with Microsoft 365 or Power Platform is beneficial
  • No coding expertise required
  • Access to Microsoft Copilot Studio is recommended for hands-on activities

TOC Modules

Concepts
  • Understanding agents, instructions, topics, knowledge, tools, triggers, and channels
  • Identifying suitable applications across risk, controls, audit, and assurance workflows
  • Differentiating AI-assisted analysis from formal audit judgement and risk ownership
  • Understanding where deterministic controls are preferable to generative reasoning
Practical activities
  • Exploring a sample Copilot Studio agent
  • Mapping a risk or audit process to agent capabilities
  • Creating a simple agent purpose and scope
  • Building Risk Need → Agent Capability → Human Review → Outcome workflow

Scenarios

Internal Control & Policy Assistant

Auditor Query → Copilot Studio → Approved Policy / Control Knowledge → Grounded Response → Source Verification → Auditor Judgement

Participants create a controlled knowledge agent that helps users locate relevant policies, control requirements, and procedures without allowing AI-generated responses to replace formal audit conclusions.

Audit Finding & Remediation Follow-Up Agent

Audit Finding → Structured Topic → Owner & Due Date → Agent Flow → Human Approval → Overdue Trigger → Escalation → Analytics

Participants build a workflow that captures remediation information, routes approved actions, identifies overdue items, and escalates exceptions while preserving human ownership of final audit status.

## Current Capability Reference

Microsoft Copilot Studio's current **generative orchestration** uses an LLM-driven planning layer that interprets intent and dynamically selects relevant **tools, topics, knowledge sources, child agents, and triggers**. Microsoft also notes that sensitive actions can be placed behind approval controls, which is important for risk and audit use cases.

Copilot Studio currently provides extensive **security and governance controls**, including data residency, data loss prevention, environment routing, security warnings, real-time risk assessment, customer-managed encryption keys, and centralized governance through Microsoft Agent 365 for organizations that adopt it.

Power Platform **data policies** can govern how agents interact with organizational data and can allow or block capabilities such as individual connectors, channels, knowledge sources, unauthenticated usage, and other agent features. Microsoft states that data-policy enforcement now applies across Copilot Studio tenants rather than being optional for exempted agents.

Microsoft recommends separating Copilot Studio development through **Power Platform environments**, with distinct development, testing, and production boundaries, role-based access, controlled connectors, gated release processes, and documented governance requirements.

For enterprise governance, Microsoft's current management guidance recommends explicitly defining **approved connectors, tools and MCP servers, production-review processes, prompt and knowledge guardrails, long-term ownership, monitoring, and telemetry** before production deployment.

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