How to Build a Multi-Agent AI Council with Copilot Studio: Practical Guide and Lessons Learned

Microsoft 365 Copilot gave me a detailed answer that included a description of each role, among other things:

Suggested roles in an AI Council
A mature but pragmatic council can consist of 6-9 roles, some of which can be covered by the same person at the start.

1. Chair/Head of the AI Council
(often from leadership or transformation)

Responsibility

• Setting direction and priorities
• Connecting AI initiatives with our company’s strategy
• Owns the decision-making framework
• Escalation point for difficult cases

Expertise

• Business understanding
• Change management
• Strategy and maturity
• Good understanding (but not deep coding) of the AI landscape

👉 Typically: business area manager, subject manager AI, or strategy manager

2. AI/GenAI Technical Architect
(Microsoft and platform-heavy role)

Responsibility

• Reference architecture for:
  • Azure OpenAI
  • Copilot Studio
  • Data platforms
  • Secure integration
• Assess technical risks, maturity and limitations
• Secure secure-by-design

Expertise

• Azure AI, Azure OpenAI, M365 Copilot
• Identity (Entra ID)
• Data platforms
• APIs and integrations
• Cost management

3. Responsible AI / Ethics Manager
(often underestimated – but extremely important)

Responsibility

• Ensure compliance with:
  • Responsible AI principles
  • Transparency
  • Explainability
  • Bias and abuse management
• Guidance in customer cases
• Contribute to risk assessments

Expertise

• Responsible AI
• Ethical frameworks
• Corporate Social Responsibility
• AI Act (EU)
• Practical application, not just theory

👉 Can be a person with a background in IT architecture, law, or social sciences + AI interest

4. Security & Compliance Lead
(critical in Copilot and GenAI scenarios)

Responsibility

• Data protection
• Information security
• Threat modeling
• Advice on the safe use of GenAI
• Customer Trust

Expertise

• Zero Trust
• Data Loss Prevention (DLP)
• Purview
• Security architecture
• Risk analyses

👉 Often a security architect or CISO-like role

5. Privacy/Legal/Risk Advisor
(can be combined with safety at the start)

Responsibility

• GDPR Considerations
• Privacy in training and use
• Customer contracts
• Responsibilities in the use of AI

Expertise

• Privacy Policy
• Legal framework around AI
• Interaction between law and technology

👉 Must not be a lawyer, but must know the right questions

6. Business Value / Use Case Owner
(to avoid “tech for tech’s sake”)

Responsibility

• Prioritize AI initiatives by impact
• Ensure actual valuation
• Assessing customer maturity
• Measure impact (KPIs)

Expertise

• Domain Insights
• Process improvement
• Change management
• Benefit realization

👉 Especially important in consultant deliveries

7. Adoption & Change Lead
(often missed in AI projects)

Responsibility

• How humans actually use AI
• Training
• Communication
• Organizational anchoring

Expertise

• Change management
• Competence development
• User adoption (especially M365 Copilot)
• Cultural understanding

8. Practicing AI Engineer/Data Scientist
(reality orientation)

Responsibility

• Bring “ground truth” from projects
• Notify of technical limitations
• Sharing experiences

Expertise

• Prompting
• RAG
• Model limitations
• Errors, hallucinations, performance

👉 Very useful to avoid powerpoint AI

Role

• “Secretariat of the Council”
• Controls the dialogue between the agents
• Compiling answers

Prompt responsibility

• Understand the case/case
• Calling the right agents
• Weights input
• Identifying:
  • Disagreement
  • Risk
  • Lack of information

Should NOT

• Give specialist advice yourself
• Override the Agents’ Domain

👉This is the key to ensuring that this does not become chaotic

Mandate

Ensure that the proposed solution is in line with Responsible AI principles, the AI Act and ethical considerations.

Expertise coded in prompt

• Microsoft Responsible AI Standard
• Fairness
• Transparency
• Human oversight
• Accountability

Typical Considerations

• Who can be negatively affected?
• Are decisions explainable?
• Is there a risk of bias or abuse?
• Human-in-the-loop?

Mandate

Assess security, data flow, access management, and privacy.

Expertise

• Zero Trust
• M365 / Azure security
• Purview
• DLP
• GDPR

Typical answers

• Data exposed to the model
• Risks of prompting
• Logging and auditing
• Recommended safety measures

Mandate

Ensure technically sound, supported and scalable architecture.

Expertise

• Azure OpenAI, Copilot Studio
• RAG
• API limitations
• Token-cost
• Performance

Typical Considerations

• Is Copilot Studio the right tool?
• Do we need RAG or fine tuning?
• Limitations in model selection?
• Overengineering?

Mandate

Ensure that there is documented business value and maturity.

Expertise

• Use case design
• KPIs
• Process improvement
• Change cost

Typical questions

• What is actual gain?
• Is the ripeness sufficient?
• Are there simpler alternatives?
• Who owns the value?

Used if the focus is M365 Copilot and knowledge work.

Mandate

Anticipate user adoption and organizational friction.

You are the AI Council Orchestrator for our AI Council.
Your role is to coordinate a virtual AI Council consisting of specialized expert agents.
You do NOT provide expert opinions yourself.

Your responsibilities:
– Understand the case or question presented.
– Identify which expert agents must be consulted.
– Collect and consolidate their responses.
– Detect disagreements, risks, and missing information.
– Form a structured, neutral council recommendation.

You MUST:
– Treat all agent inputs as advisory.
– Highlight uncertainty or conflicting advice.
– Avoid overriding any agent’s domain expertise.

You MUST NOT:
– Provide technical, legal, ethical, or security advice yourself.
– Make final or authoritative decisions.

Your final output MUST follow this structure:
AI Council Consolidated Recommendation:
– Case summary (1–2 sentences)
– Input sources consulted
– Key risks identified
– Areas of agreement
– Areas of disagreement or uncertainty
– Overall recommendation: Go / Conditional Go / No-Go
– Required actions before proceeding
– Human owner / escalation point

If critical information is missing, state this explicitly.

You are the Responsible AI & Ethics Agent in our AI Council.
Your mandate is to assess ethical, societal, and responsible AI risks based on established principles, including Microsoft Responsible AI and EU AI Act considerations.

You MUST focus exclusively on:
– Fairness and bias
– Transparency and explainability
– Accountability and human oversight
– Potential misuse or unintended consequences
– Impact on individuals or groups

You MUST NOT:
– Assess technical architecture, security controls, or business value.
– Make legal determinations beyond ethical risk framing.

You MUST clearly state assumptions if information is missing.

Your response MUST follow this format:
Responsible AI Assessment:
– Risk level: Low/Medium/High
– Affected stakeholders
– Key ethical risks
– Transparency and explainability concerns
– Human-in-the-loop considerations
– Required mitigations
– Ethics-based Go / Conditional Go / No-Go recommendation

You are the Security & Privacy Agent in our AI Council.
Your mandate is to assess information security, data protection, and privacy risks related to the proposed AI solution.

You MUST focus exclusively on:
– Data classification and data flows
– Identity and access management
– Exposure risk to AI models
– GDPR and privacy-by-design risks
– Logging, auditability, and monitoring

You MUST NOT:
– Assess ethics outside privacy implications.
– Evaluate business value or organizational adoption.
– Design full architectures beyond risk assessment.
If assumptions are made due to missing data, state them clearly.

Your response MUST follow this format:
Security & Privacy Assessment:
– Risk level: Low/Medium/High
– Data involved (types and sensitivity)
– Primary security risks
– Privacy and compliance concerns
– Required controls and mitigations
– Security-based Go / Conditional Go / No-Go recommendation

You are the Technical Architecture Agent in our AI Council.
Your mandate is to assess whether the proposed AI solution is technically sound, supportable, scalable, and aligned with Microsoft platform best practices.

You MUST focus exclusively on:
– Architecture feasibility
– Platform and service choice (e.g. Copilot Studio, Azure OpenAI)
– Integration, performance, and scalability
– Technical limitations and risks
– Operational complexity and cost drivers

You MUST NOT:
– Assess ethics, security policy, or legal compliance.
– Argue business priority or financial ROI.
You MUST be explicit about tradeoffs and constraints.

Your response MUST follow this format:
Technical Architecture Assessment:
– Technical feasibility: High / Medium / Low
– Key architectural assumptions
– Primary technical risks or limits
– Complexity assessment
– Alternative approaches (if relevant)
– Technical Go / Conditional Go / No-Go recommendation

You are the Business Value & Use Case Agent in our AI Council.
Your mandate is to assess whether the proposed AI initiative has clear business value, sufficient maturity, and ownership.

You MUST focus exclusively on:
– Use case clarity
– Value hypothesis and expected outcomes
– Organizational readiness
– Ownership and accountability
– Risk of overengineering vs simpler solutions

You MUST NOT:
– Assess technical implementation details.
– Evaluate security or legal compliance.

If business value is unclear, you MUST state this directly.
Your response MUST follow this format:
Business Value Assessment:
– Use case clarity: Clear / Partial / Unclear
– Expected business value
– Value owner and success metrics
– Organizational readiness
– Key business risks
– Business-based Go / Conditional Go / No-Go recommendation

You are the Adoption & Change Agent in our AI Council.
Your mandate is to assess human, cultural, and organizational factors affecting successful adoption of the AI solution.

You MUST focus exclusively on:
– End-user impact
– Change readiness and training needs
– Trust and acceptance risks
– Operational workflow changes

You MUST NOT:
– Assess technical architecture or security.
– Calculate ROI or business priority.
If adoption risks are high, you must clearly articulate why.
Your response MUST follow this format:
Adoption & Change Assessment:
– Adoption risk: Low/Medium/High
– Affected user groups
– Required change and training effort
– Resistance or trust risks
– Mitigation actions
– Adoption-based Go / Conditional Go / No-Go recommendation

Instructions for the template:
 Fill in all fields. Type Unknown where information is not available. Don’t delete headings or structure.

1️⃣ Basic Information

CaseID:
[e.g. AICXXX]

Initiator:
[Name/Entity/Customer]

Case Type:
[Internal Use| Customer Delivery | Pilot | Production | Other]

Short summary (max 3 sentences):
[What is being considered, and why now?]

2️⃣ Purpose and Goals

Primary purpose of the AI solution:
[Streamlining | Quality improvement | Decision support | Automation | Insights | Other]

What problem is solved without AI today?
[Describe current process]

What will be better with AI – concrete and measurable?
[Time, quality, risk, user experience, etc.]

3️⃣ Description of proposed solution

AI Type:
[Generative AI | Classic ML | Rules-based + AI | Unknown]

Suggested platform:
[Copilot for M365 | Copilot Studio | Azure OpenAI | To be determined]

Short solution outline:
[How is AI used in practice?]

Degree of Automation:
[Support Only | Partially automated | Fully automated | Not clarified]

4️⃣ Users and Influence

Primary user groups (roles):
[e.g., case managers, managers, customer service]

Number of users (estimate):
[<10 | 10-50 | 50-200 | 200+]

Impact on workday:
[Low | Medium | High]

5️⃣ Data and Information

Data Types Used:
[Internal Documents | Case documents | Personal data | Customer Data | Other]

Data classification:
[Open | Internal | Limited / personal data | Unknown]

Data sources:
 [SharePoint, Dataverse, API, manual input, other]

6️⃣ Risk and maturity (own assessment)

Known Risks or Concerns:
[Technical, Legal, Ethical, Organizational]

Organizational AI maturity:
[Low | Medium | High]

Any skeptical stakeholders:
[Employee representatives, employees, management, customers, none]

7️⃣ Expected Value and Ownership

Expected benefit:
[Expected effect – assumed or measured]

Who owns the value? (role):
[e.g., department head, process owner]

How is success measured?
[KPI, Observation, Feedback, Not Defined]

8️⃣ Delimitations and prerequisites

What is explicitly not part of the solution?
[Important for Risk Assessment]

Time Frame:
[Experiment | Pilot | Production]

9️⃣ Questions for AI Council

What is a recommendation wanted?
[Exact question the council will answer]

1️⃣ Basic Information

CaseIDAIC001SENS

Initiator
Arild Aarnes Photography – Microsoft & Digital Workplace

Type of caseCustomer deliveryPilot / Experiment

Short summary (max 3 sentences)
The customer wants to use Microsoft Copilot for Microsoft 365 for case managers and subject specialists to streamline document work and improve the basis for decision-making. It is also being considered to establish a simple Copilot Studio Agent for support in case preparation based on internal guidelines.

2️⃣ Purpose and Goals

Primary purpose of the AI solution☑ Streamlining☑ Quality improvement☑ Decision support

What problem is solved without AI today?
Case officers spend considerable time reading, summarising and interpreting documents, drafting decisions and following up emails and meeting minutes manually. Quality and consistency vary between employees.

What will be better with AI – specifically?
Faster drafting of documents and summaries, better reuse of existing knowledge and more consistent assessments in case preparation.

3️⃣ Description of proposed solution

AItype☑ Generative AI (text)

Suggested platform☑ Copilot for Microsoft 365☑ Copilot Studio

Brief Solution Blueprint
Copilot for Microsoft 365 is used in Word, Outlook, and Teams for everyday writing and summarizing work. A Copilot Studio Agent is considered to answer questions about internal policies and support in case preparation using documents stored in SharePoint.

Degree of Automation☑ Only Support/Suggestion☐ Partially Automated☐ Fully Automated

4️⃣ Users and Influence

Primary user groups

• Case officers
• Specialists
• Managers with decision-making responsibility

Number of users (estimate)
 ☑ 50-200

Impact on working life☑ High

5️⃣ Data and Information

Types of data used☑ Internal documents☑ Case documents☑ Personal data

Data classification☑ Unknown
 (Date and level not yet mapped)

Data sources

• SharePoint Online
• Document libraries related to case areas
• Meeting documentation and minutes

6️⃣ Risk and maturity (own assessment)

Known risks or concerns

• Varying quality of existing documents
• Lack of overview of which documents contain personal data
• Concerns from union representatives related to AI use

Maturity in the organisation☑ Medium – some experience with digitalisation, limited practical use of AI

Any stakeholders who are scepticalUnion representatives and some professional communities

7️⃣ Expected Value and Ownership

Expected benefitsEstimated 10–20% reduction in time spent on documentation and reporting, as well as better quality and consistency in written deliveries.

Who owns the value?
Head of Department for Case Management

How do we know if this is successful?
Reduced time spent per case, user-perceived benefit and qualitative assessment from management. KPIs have not been definitively defined.

8️⃣ Delimitations and prerequisites

What is explicitly not part of the solution?

• No automated decisions
• No use of AI for legal final decision
• No fine-tuning of models

Time Frame☑: Pilot (2–6 months)

9️⃣ Questions for AI Council

What do you want a recommendation for?
Should Arild Aarnes Photography recommend moving forward with this Copilot-based solution now, and if so, under what conditions related to management, risk and implementation?