📘 Free AB-620 Sample Questions
DRAG DROP -
Case Study -
This is a case study. Case studies are not timed separately from other exam sections. You can use as much exam
time as you would like to complete each case study. However, there might be additional case studies or other
exam sections. Manage your time to ensure that you can complete all the exam sections in the time provided. Pay
attention to the Exam Progress at the top of the screen so you have sufficient time to complete any exam sections
that follow this case study.
To answer the case study questions, you will need to reference information that is provided in the case. Case
studies and associated questions might contain exhibits or other resources that provide more information about
the scenario described in the case. Information provided in an individual question does not apply to the other
questions in the case study.
A Review Screen will appear at the end of this case study. From the Review Screen, you can review and change
your answers before you move to the next exam section. After you leave this case study, you will NOT be able to
return to it.
To start the case study -
To display the first question in this case study, select the "Next" button. To the left of the question, a menu
provides links to information such as business requirements, the existing environment, and problem statements.
Please read through all this information before answering any questions. When you are ready to answer a question,
select the "Question" button to return to the question.
Background -
Blue Yonder Airlines is a global carrier headquartered in Los Angeles, California, operating domestic and
international flights. The company serves millions of passengers annually through its website, mobile app, and call
centers. To improve customer service efficiency and reduce call center volume, Blue Yonder is deploying an AI
agent in Microsoft Copilot Studio.
The agent will handle customer inquiries across multiple channels – web chat, mobile app, and Microsoft Teams
(for internal support staff). It will answer questions, retrieve data from enterprise systems, and escalate to human
agents when needed.
The project is led by a cross-function team:
Product manager: Defines requirements and success metrics.
Lead agent author: Designs topics, intents, and generative behavior.
Flow designers: Build agent flows and integrations.
IT/security and compliance: Oversees identity, data protection, and Responsible AI (RAI) compliance.
Current environment -
Channels -
Public website: Embedded web chat
Mobile app: In-app chatbot -
Microsoft Teams: Internal support agent access
Identity and access -
Customers: Anonymous access for general inquiries (e.g., flight status, baggage policy).
Authentication is required for personal data access (e.g., bookings, loyalty points).
Internal staff: Authenticate via Microsoft Entra ID.
Data sources -
Reservation and Ticketing System (internal): REST API, no prebuilt connector with custom enterprise database.
Flight Status and Weather APIs (external): REST APIs with API keys.
Customer Support Knowledge Base: SharePoint library with PDFs and policy documents.
Loyalty Program Data: Stored in Dynamics 365 and Dataverse.
Travel Advisory Content: Uses REST API with partner services.
Integration mechanisms -
Custom connectors must be used for internal APIs that lack prebuilt connectors.
HTTP request nodes may be used for lightweight external APIs.
Knowledge sources must be used for unstructured content.
Agent flows must be used to encapsulate reusable logic (e.g., rebooking).
Business requirements -
Omnichannel support -
Deploy the agent across web, mobile, and Teams with a consistent user experience. The Teams deployment must
also support internal staff.
Self-service capabilities -
The agent must handle common inquiries such as:
Flight status -
Booking and rebooking -
Loyalty program questions -
Travel policies and baggage rules
Human escalation -
If the agent cannot resolve an issue or the user requests help, it must:
Escalate to a human agent.
Transfer the conversation transcript and relevant context.
Redact any sensitive personal data before escalation.
Knowledge integration -
The agent must use scalable methods for knowledge integration and must not rely on manually authored Q&A
topics for each document.
Performance metrics -
First-contact resolution: +25%
Tier-1 call deflection: ≥20%
Response time: 90% of queries answered within 30 seconds
Accuracy: ≥95% for known FAQs -
CSAT: ≥85% for AI-handled interactions
Technical requirements -
Platform constraints -
No custom code is permitted; only Copilot Studio's built-in tools may be used.
All backend logic must be implemented using agent flows.
Markdown must be used for formatting (e.g., bold, bullet points); HTML is not supported.
Authentication -
Sign-in is required for personal data access.
Anonymous access is allowed for general inquiries.
User identity must be used for data access; shared or builder credentials must not be used.
Compliance and security -
Power Platform DLP policies must be enforced to block unauthorized data flows.
Responsible AI content moderation filters must be enabled.
Prompt modifications must be added to enforce tone, disclaimers, and refusal behavior.
Disclaimers must be applied consistently across all generative responses. Manual edits to individual topics must
be avoided.
Monitoring and maintenance -
All conversations and actions must be logged for auditing.
Weekly reviews of transcripts and metrics must be conducted.
Issues and constraints -
API rate limits: External APIs (e.g., flight status) have usage limits. Agent flows must handle retries and caching to
avoid exceeding quotas.
Knowledge base limits: Copilot Studio has limits on the number and size of indexed documents. Large files must be
split or summarized.
Generative answer risks: Generative responses must be constrained to avoid policy violations. Prompt
modifications and filters must be used to enforce tone, safety, and compliance.
User input variability: Users phrase questions in diverse ways. Topics must include varied trigger phrases and
fallback handling.
Authentication UX: The agent must clearly explain when sign-in is required and handle transitions smoothly across
channels.
Problem statement -
Blue Yonder Airlines must deploy a secure, scalable, and policy-compliant AI agent using Microsoft Copilot Studio.
The agent must deliver accurate, helpful, and safe responses across multiple channels, integrate with enterprise
systems, and support both anonymous and authenticated users. It must adhere to strict data protection and
Responsible AI standards while improving customer service efficiency and satisfaction.
You need to configure the agent in Copilot Studio to meet Blue Vender's Responsible AI and data protection
requirements.
Which three actions should you perform in sequence? To answer, move the appropriate actions from the list of
actions to the answer area and arrange them in the correct order.
A
Correct Answer:
A.
Explanation:
Add custom prompt modifications
Why it's first: This is the base layer of safety. Custom instructions (or system prompts) establish the
fundamental boundaries, personality, and contextual rules for the generative Al model inside Microsoft
Copilot Studio.
It explicitly tells the LLM how to behave, what tone to maintain, and what topics or data sources are strictly
off-limits before any user interaction happens.
Configure content moderation filters
Why it's second: Once the core instructions are set, you apply real-time filtering layers. Content moderation
filters act as an active validation shield that monitors incoming user prompts and outgoing model completions.
It detects and blocks toxic, unsafe, or off-policy phrasing that a custom prompt alone might fail to stop,
completely satisfying the requirement that "filters must be used to enforce tone, safety, and compliance."
Conduct adversarial testing
Why it's last: Testing always occurs after all defensive measures and configuration changes have been
implemented.
Adversarial testing (commonly known as red-teaming) attempts to deliberately trick, bypass, or prompt-inject
the copilot. Performing this as the final step verifies that your prompt modifications and content moderation
filters actually function as intended under realistic stress scenarios before deployment.
Why the other choices are incorrect
Define Data Loss Prevention (DLP) policies: DLP policies control environment-level connectors and data flow
at the Power Platform administration tier, rather than controlling the specific conversational tone, safety, and
compliance filters inside a generative copilot.
Integrate with Microsoft Purview: While Purview is excellent for enterprise compliance and data lifecycle
auditing, the specific requirement explicitly emphasizes adjusting prompt instructions and filters directly
within the copilot architecture.
Disable generative answers: The case study specifically requires using generative answers safely
("Generative responses must be constrained ... "), so disabling them completely defeats the fundamental
purpose of the requested Al deployment.
DRAG DROP -
Case Study -
This is a case study. Case studies are not timed separately from other exam sections. You can use as much exam
time as you would like to complete each case study. However, there might be additional case studies or other
exam sections. Manage your time to ensure that you can complete all the exam sections in the time provided. Pay
attention to the Exam Progress at the top of the screen so you have sufficient time to complete any exam sections
that follow this case study.
To answer the case study questions, you will need to reference information that is provided in the case. Case
studies and associated questions might contain exhibits or other resources that provide more information about
the scenario described in the case. Information provided in an individual question does not apply to the other
questions in the case study.
A Review Screen will appear at the end of this case study. From the Review Screen, you can review and change
your answers before you move to the next exam section. After you leave this case study, you will NOT be able to
return to it.
To start the case study -
To display the first question in this case study, select the "Next" button. To the left of the question, a menu
provides links to information such as business requirements, the existing environment, and problem statements.
Please read through all this information before answering any questions. When you are ready to answer a question,
select the "Question" button to return to the question.
Background -
agent in Microsoft Copilot Studio.
agents when needed.
The project is led by a cross-function team:
Product manager: Defines requirements and success metrics.
Lead agent author: Designs topics, intents, and generative behavior.
Flow designers: Build agent flows and integrations.
Blue Yonder Airlines is a global carrier headquartered in Los Angeles, California, operating domestic and
international flights. The company serves millions of passengers annually through its website, mobile app, and call
centers. To improve customer service efficiency and reduce call center volume, Blue Yonder is deploying an AI
The agent will handle customer inquiries across multiple channels – web chat, mobile app, and Microsoft Teams
(for internal support staff). It will answer questions, retrieve data from enterprise systems, and escalate to human
IT/security and compliance: Oversees identity, data protection, and Responsible AI (RAI) compliance.
Current environment -
Channels -
Public website: Embedded web chat
Mobile app: In-app chatbot -
Microsoft Teams: Internal support agent access
Identity and access -
Customers: Anonymous access for general inquiries (e.g., flight status, baggage policy).
Authentication is required for personal data access (e.g., bookings, loyalty points).
Internal staff: Authenticate via Microsoft Entra ID.
Data sources -
Reservation and Ticketing System (internal): REST API, no prebuilt connector with custom enterprise database.
Flight Status and Weather APIs (external): REST APIs with API keys.
Customer Support Knowledge Base: SharePoint library with PDFs and policy documents.
Loyalty Program Data: Stored in Dynamics 365 and Dataverse.
Travel Advisory Content: Uses REST API with partner services.
Integration mechanisms -
Custom connectors must be used for internal APIs that lack prebuilt connectors.
HTTP request nodes may be used for lightweight external APIs.
Knowledge sources must be used for unstructured content.
Agent flows must be used to encapsulate reusable logic (e.g., rebooking).
Business requirements -
Omnichannel support -
Deploy the agent across web, mobile, and Teams with a consistent user experience. The Teams deployment must
also support internal staff.
Self-service capabilities -
The agent must handle common inquiries such as:
Flight status -
Booking and rebooking -
Loyalty program questions -
Travel policies and baggage rules
Human escalation -
If the agent cannot resolve an issue or the user requests help, it must:
Escalate to a human agent.
Transfer the conversation transcript and relevant context.
Redact any sensitive personal data before escalation.
Knowledge integration -
The agent must use scalable methods for knowledge integration and must not rely on manually authored Q&A
topics for each document.
Performance metrics -
First-contact resolution: +25%
Tier-1 call deflection: ≥20%
Response time: 90% of queries answered within 30 seconds
Accuracy: ≥95% for known FAQs -
CSAT: ≥85% for AI-handled interactions
Technical requirements -
Platform constraints -
No custom code is permitted; only Copilot Studio's built-in tools may be used.
All backend logic must be implemented using agent flows.
Markdown must be used for formatting (e.g., bold, bullet points); HTML is not supported.
Authentication -
Sign-in is required for personal data access.
Anonymous access is allowed for general inquiries.
User identity must be used for data access; shared or builder credentials must not be used.
Compliance and security -
Power Platform DLP policies must be enforced to block unauthorized data flows.
Responsible AI content moderation filters must be enabled.
Prompt modifications must be added to enforce tone, disclaimers, and refusal behavior.
Disclaimers must be applied consistently across all generative responses. Manual edits to individual topics must
be avoided.
Monitoring and maintenance -
All conversations and actions must be logged for auditing.
Weekly reviews of transcripts and metrics must be conducted.
Issues and constraints -
API rate limits: External APIs (e.g., flight status) have usage limits. Agent flows must handle retries and caching to
avoid exceeding quotas.
Knowledge base limits: Copilot Studio has limits on the number and size of indexed documents. Large files must be
split or summarized.
Generative answer risks: Generative responses must be constrained to avoid policy violations. Prompt
modifications and filters must be used to enforce tone, safety, and compliance.
User input variability: Users phrase questions in diverse ways. Topics must include varied trigger phrases and
fallback handling.
Authentication UX: The agent must clearly explain when sign-in is required and handle transitions smoothly across
channels.
Problem statement -
Blue Yonder Airlines must deploy a secure, scalable, and policy-compliant AI agent using Microsoft Copilot Studio.
The agent must deliver accurate, helpful, and safe responses across multiple channels, integrate with enterprise
systems, and support both anonymous and authenticated users. It must adhere to strict data protection and
Responsible AI standards while improving customer service efficiency and satisfaction.
You need to evaluate whether the current configuration decisions for the Blue Yonder Copilot agent comply with
the company's security and governance policies.
Which compliance status should you assign to each configuration decision? To answer, move the appropriate
compliance statuses to the correct configuration decisions. You may use each compliance status once, more than
once, or not at all. You may need to move the split bar between panes or scroll to view content.
NOTE: Each correct selection is worth one point.
A
Correct Answer:
A.
Explanation:
(Compliant): Baggage policies are public informational data. Allowing unauthenticated (anonymous) access
for standard customer service FAQs is completely secure and follows standard architectural practices.
(Non-compliant): Utilizing ungrounded open web searches introduces severe risks of hallucinations and off-
policy responses. This directly violates the case study's core mandate that generative answers must be
securely constrained.
(Non-compliant): As established in the safety deployment requirements, custom system instructions (RAI
prompts) are mandatory to enforce the specific tone, safety compliance, and operational boundaries of the
company. Relying solely on default settings is insufficient.
(Non-compliant): Employing a single shared administrator credential for all internal backend access breaches
basic Zero Trust security guidelines and data privacy principles (Least Privilege). It allows users to potentially
bypass data access controls or view internal data they are not authorized to see.
Case Study -
This is a case study. Case studies are not timed separately from other exam sections. You can use as much exam
time as you would like to complete each case study. However, there might be additional case studies or other
exam sections. Manage your time to ensure that you can complete all the exam sections in the time provided. Pay
attention to the Exam Progress at the top of the screen so you have sufficient time to complete any exam sections
that follow this case study.
To answer the case study questions, you will need to reference information that is provided in the case. Case
studies and associated questions might contain exhibits or other resources that provide more information about
the scenario described in the case. Information provided in an individual question does not apply to the other
questions in the case study.
A Review Screen will appear at the end of this case study. From the Review Screen, you can review and change
your answers before you move to the next exam section. After you leave this case study, you will NOT be able to
return to it.
To start the case study -
To display the first question in this case study, select the "Next" button. To the left of the question, a menu
provides links to information such as business requirements, the existing environment, and problem statements.
Please read through all this information before answering any questions. When you are ready to answer a question,
select the "Question" button to return to the question.
Background -
Blue Yonder Airlines is a global carrier headquartered in Los Angeles, California, operating domestic and
international flights. The company serves millions of passengers annually through its website, mobile app, and call
centers. To improve customer service efficiency and reduce call center volume, Blue Yonder is deploying an AI
agent in Microsoft Copilot Studio.
The agent will handle customer inquiries across multiple channels – web chat, mobile app, and Microsoft Teams
(for internal support staff). It will answer questions, retrieve data from enterprise systems, and escalate to human
agents when needed.
The project is led by a cross-function team:
Product manager: Defines requirements and success metrics.
Lead agent author: Designs topics, intents, and generative behavior.
Flow designers: Build agent flows and integrations.
IT/security and compliance: Oversees identity, data protection, and Responsible AI (RAI) compliance.
Current environment -
Channels -
Public website: Embedded web chat
Mobile app: In-app chatbot -
Microsoft Teams: Internal support agent access
Identity and access -
Customers: Anonymous access for general inquiries (e.g., flight status, baggage policy).
Authentication is required for personal data access (e.g., bookings, loyalty points).
Internal staff: Authenticate via Microsoft Entra ID.
Data sources -
Reservation and Ticketing System (internal): REST API, no prebuilt connector with custom enterprise database.
Flight Status and Weather APIs (external): REST APIs with API keys.
Customer Support Knowledge Base: SharePoint library with PDFs and policy documents.
Loyalty Program Data: Stored in Dynamics 365 and Dataverse.
Travel Advisory Content: Uses REST API with partner services.
Integration mechanisms -
Custom connectors must be used for internal APIs that lack prebuilt connectors.
HTTP request nodes may be used for lightweight external APIs.
Knowledge sources must be used for unstructured content.
Agent flows must be used to encapsulate reusable logic (e.g., rebooking).
Business requirements -
Omnichannel support -
Deploy the agent across web, mobile, and Teams with a consistent user experience. The Teams deployment must
also support internal staff.
Self-service capabilities -
The agent must handle common inquiries such as:
Flight status -
Booking and rebooking -
Loyalty program questions -
Travel policies and baggage rules
Human escalation -
If the agent cannot resolve an issue or the user requests help, it must:
Escalate to a human agent.
Transfer the conversation transcript and relevant context.
Redact any sensitive personal data before escalation.
Knowledge integration -
The agent must use scalable methods for knowledge integration and must not rely on manually authored Q&A
topics for each document.
Performance metrics -
First-contact resolution: +25%
Tier-1 call deflection: ≥20%
Response time: 90% of queries answered within 30 seconds
Accuracy: ≥95% for known FAQs -
CSAT: ≥85% for AI-handled interactions
Technical requirements -
Platform constraints -
No custom code is permitted; only Copilot Studio's built-in tools may be used.
All backend logic must be implemented using agent flows.
Markdown must be used for formatting (e.g., bold, bullet points); HTML is not supported.
Authentication -
Sign-in is required for personal data access.
Anonymous access is allowed for general inquiries.
User identity must be used for data access; shared or builder credentials must not be used.
Compliance and security -
Power Platform DLP policies must be enforced to block unauthorized data flows.
Responsible AI content moderation filters must be enabled.
Prompt modifications must be added to enforce tone, disclaimers, and refusal behavior.
Disclaimers must be applied consistently across all generative responses. Manual edits to individual topics must
be avoided.
Monitoring and maintenance -
All conversations and actions must be logged for auditing.
Weekly reviews of transcripts and metrics must be conducted.
Issues and constraints -
API rate limits: External APIs (e.g., flight status) have usage limits. Agent flows must handle retries and caching to
avoid exceeding quotas.
Knowledge base limits: Copilot Studio has limits on the number and size of indexed documents. Large files must be
split or summarized.
Generative answer risks: Generative responses must be constrained to avoid policy violations. Prompt
modifications and filters must be used to enforce tone, safety, and compliance.
User input variability: Users phrase questions in diverse ways. Topics must include varied trigger phrases and
fallback handling.
Authentication UX: The agent must clearly explain when sign-in is required and handle transitions smoothly across
channels.
Problem statement -
Blue Yonder Airlines must deploy a secure, scalable, and policy-compliant AI agent using Microsoft Copilot Studio.
The agent must deliver accurate, helpful, and safe responses across multiple channels, integrate with enterprise
systems, and support both anonymous and authenticated users. It must adhere to strict data protection and
Responsible AI standards while improving customer service efficiency and satisfaction.
You need to deploy the Blue Yonder Copilot agent to the public website and Microsoft Teams while ensuring
compliance with the company's security and Responsible AI requirements.
Which two actions should you perform before making the agent available on both channels? Each correct answer
presents part of the solution.
NOTE: Each correct selection is worth one point.
A
Configure prompt modifications to enforce tone, disclaimers, and refusal behavior at the system level.
B
Manually add disclaimers to each topic before publishing.
C
Embed the web channel and then rely on channel-level settings to enforce content moderation.
D
Configure Power Platform DLP policies to restrict unauthorized data connectors.
E
Publish the agent and then enable Responsible AI filters individually for each channel.
Correct Answer:
A. Configure prompt modifications to enforce tone, disclaimers, and refusal behavior at the system level.
Explanation:
A. Configure prompt modifications to enforce tone, disclaimers, and refusal behavior at the system level.
D. Configure Power Platform DLP policies to restrict unauthorized data connectors.
Action A (Responsible AI Compliance): Relying on system-level prompt modifications ensures that regardless
of the topic or channel (Public Web or Microsoft Teams), the generative AI model inherently follows enterprise
guardrails regarding tone, required disclaimers, and refusal bounds.
Action D (Security Compliance): Power Platform Data Loss Prevention (DLP) policies act as the security
firewall. They control and block unauthorized connectors at the environment tier, preventing the copilot from
accidentally leaking or retrieving data through non-compliant external channels.
Why the other options are incorrect
answers.
on distinct channels.
B is an operational nightmare; manually updating individual topics fails to secure globally generated AI
C & E are architectural misconceptions; content moderation and Responsible AI filters in Microsoft Copilot
Studio are centrally managed at the agent/system tier before publication, rather than handled piece-by-piece on distinct channels.
Case Study -
This is a case study. Case studies are not timed separately from other exam sections. You can use as much exam
time as you would like to complete each case study. However, there might be additional case studies or other
exam sections. Manage your time to ensure that you can complete all the exam sections in the time provided. Pay
attention to the Exam Progress at the top of the screen so you have sufficient time to complete any exam sections
that follow this case study.
To answer the case study questions, you will need to reference information that is provided in the case. Case
studies and associated questions might contain exhibits or other resources that provide more information about
the scenario described in the case. Information provided in an individual question does not apply to the other
questions in the case study.
A Review Screen will appear at the end of this case study. From the Review Screen, you can review and change
your answers before you move to the next exam section. After you leave this case study, you will NOT be able to
return to it.
To start the case study -
To display the first question in this case study, select the "Next" button. To the left of the question, a menu
provides links to information such as business requirements, the existing environment, and problem statements.
Please read through all this information before answering any questions. When you are ready to answer a question,
select the "Question" button to return to the question.
Background -
agent in Microsoft Copilot Studio.
agents when needed.
Blue Yonder Airlines is a global carrier headquartered in Los Angeles, California, operating domestic and
international flights. The company serves millions of passengers annually through its website, mobile app, and call
centers. To improve customer service efficiency and reduce call center volume, Blue Yonder is deploying an AI
The agent will handle customer inquiries across multiple channels – web chat, mobile app, and Microsoft Teams
(for internal support staff). It will answer questions, retrieve data from enterprise systems, and escalate to human
The project is led by a cross-function team:
Product manager: Defines requirements and success metrics.
Lead agent author: Designs topics, intents, and generative behavior.
Flow designers: Build agent flows and integrations.
IT/security and compliance: Oversees identity, data protection, and Responsible AI (RAI) compliance.
Current environment -
Channels -
Public website: Embedded web chat
Mobile app: In-app chatbot -
Microsoft Teams: Internal support agent access
Identity and access -
Customers: Anonymous access for general inquiries (e.g., flight status, baggage policy).
Authentication is required for personal data access (e.g., bookings, loyalty points).
Internal staff: Authenticate via Microsoft Entra ID.
Data sources -
Reservation and Ticketing System (internal): REST API, no prebuilt connector with custom enterprise database.
Flight Status and Weather APIs (external): REST APIs with API keys.
Customer Support Knowledge Base: SharePoint library with PDFs and policy documents.
Loyalty Program Data: Stored in Dynamics 365 and Dataverse.
Travel Advisory Content: Uses REST API with partner services.
Integration mechanisms -
Custom connectors must be used for internal APIs that lack prebuilt connectors.
HTTP request nodes may be used for lightweight external APIs.
Knowledge sources must be used for unstructured content.
Agent flows must be used to encapsulate reusable logic (e.g., rebooking).
Business requirements -
Omnichannel support -
Deploy the agent across web, mobile, and Teams with a consistent user experience. The Teams deployment must
also support internal staff.
Self-service capabilities -
The agent must handle common inquiries such as:
Flight status -
Booking and rebooking -
Loyalty program questions -
Travel policies and baggage rules
Human escalation -
If the agent cannot resolve an issue or the user requests help, it must:
Escalate to a human agent.
Transfer the conversation transcript and relevant context.
Redact any sensitive personal data before escalation.
Knowledge integration -
The agent must use scalable methods for knowledge integration and must not rely on manually authored Q&A
topics for each document.
Performance metrics -
First-contact resolution: +25%
Tier-1 call deflection: ≥20%
Response time: 90% of queries answered within 30 seconds
Accuracy: ≥95% for known FAQs -
CSAT: ≥85% for AI-handled interactions
Technical requirements -
Platform constraints -
No custom code is permitted; only Copilot Studio's built-in tools may be used.
All backend logic must be implemented using agent flows.
Markdown must be used for formatting (e.g., bold, bullet points); HTML is not supported.
Authentication -
Sign-in is required for personal data access.
Anonymous access is allowed for general inquiries.
User identity must be used for data access; shared or builder credentials must not be used.
Compliance and security -
Power Platform DLP policies must be enforced to block unauthorized data flows.
Responsible AI content moderation filters must be enabled.
Prompt modifications must be added to enforce tone, disclaimers, and refusal behavior.
Disclaimers must be applied consistently across all generative responses. Manual edits to individual topics must
be avoided.
Monitoring and maintenance -
All conversations and actions must be logged for auditing.
Weekly reviews of transcripts and metrics must be conducted.
Issues and constraints -
API rate limits: External APIs (e.g., flight status) have usage limits. Agent flows must handle retries and caching to
avoid exceeding quotas.
Knowledge base limits: Copilot Studio has limits on the number and size of indexed documents. Large files must be
split or summarized.
Generative answer risks: Generative responses must be constrained to avoid policy violations. Prompt
modifications and filters must be used to enforce tone, safety, and compliance.
User input variability: Users phrase questions in diverse ways. Topics must include varied trigger phrases and
fallback handling.
Authentication UX: The agent must clearly explain when sign-in is required and handle transitions smoothly across
channels.
Problem statement -
Blue Yonder Airlines must deploy a secure, scalable, and policy-compliant AI agent using Microsoft Copilot Studio.
The agent must deliver accurate, helpful, and safe responses across multiple channels, integrate with enterprise
systems, and support both anonymous and authenticated users. It must adhere to strict data protection and
Responsible AI standards while improving customer service efficiency and satisfaction.
You need to configure the Blue Yonder Copilot agent's responses in accordance with the company's content
control and platform requirements.
Which two actions should you perform? Each correct answer presents part of the solution.
NOTE: Each correct selection is worth one point.
A
Add required disclaimer text inside each individual topic.
B
Configure prompt instructions that include disclaimer text.
C
Use Markdown syntax within response content.
D
Insert HTML formatting directly into topic responses.
E
Duplicate disclaimer text across reusable topics.
Correct Answer:
B. Configure prompt instructions that include disclaimer text.
Explanation:
B. Configure prompt instructions that include disclaimer text.
C. Use Markdown syntax within response content.
Action B (Content Control Compliance): Adding required disclaimer instructions at the system prompt level
ensures that the underlying generative model consistently appends or enforces the necessary legal and
safety compliance guidelines globally, preventing the need to manually update static topics.
Action C (Platform Requirement Compliance): Microsoft Copilot Studio natively supports and recommends
Markdown syntax within response message nodes. It ensures content renders consistently (such as bolding,
lists, and hyperlinks) across both the public website channel and Microsoft Teams.
Case Study -
This is a case study. Case studies are not timed separately from other exam sections. You can use as much exam
time as you would like to complete each case study. However, there might be additional case studies or other
exam sections. Manage your time to ensure that you can complete all the exam sections in the time provided. Pay
attention to the Exam Progress at the top of the screen so you have sufficient time to complete any exam sections
that follow this case study.
To answer the case study questions, you will need to reference information that is provided in the case. Case
studies and associated questions might contain exhibits or other resources that provide more information about
the scenario described in the case. Information provided in an individual question does not apply to the other
questions in the case study.
return to it.
To start the case study -
A Review Screen will appear at the end of this case study. From the Review Screen, you can review and change
your answers before you move to the next exam section. After you leave this case study, you will NOT be able to
To display the first question in this case study, select the "Next" button. To the left of the question, a menu
provides links to information such as business requirements, the existing environment, and problem statements.
Please read through all this information before answering any questions. When you are ready to answer a question,
select the "Question" button to return to the question.
Background -
Blue Yonder Airlines is a global carrier headquartered in Los Angeles, California, operating domestic and
international flights. The company serves millions of passengers annually through its website, mobile app, and call
centers. To improve customer service efficiency and reduce call center volume, Blue Yonder is deploying an AI
agent in Microsoft Copilot Studio.
The agent will handle customer inquiries across multiple channels – web chat, mobile app, and Microsoft Teams
(for internal support staff). It will answer questions, retrieve data from enterprise systems, and escalate to human
agents when needed.
The project is led by a cross-function team:
Product manager: Defines requirements and success metrics.
Lead agent author: Designs topics, intents, and generative behavior.
Flow designers: Build agent flows and integrations.
IT/security and compliance: Oversees identity, data protection, and Responsible AI (RAI) compliance.
Current environment -
Channels -
Public website: Embedded web chat
Mobile app: In-app chatbot -
Microsoft Teams: Internal support agent access
Identity and access -
Customers: Anonymous access for general inquiries (e.g., flight status, baggage policy).
Authentication is required for personal data access (e.g., bookings, loyalty points).
Internal staff: Authenticate via Microsoft Entra ID.
Data sources -
Reservation and Ticketing System (internal): REST API, no prebuilt connector with custom enterprise database.
Flight Status and Weather APIs (external): REST APIs with API keys.
Customer Support Knowledge Base: SharePoint library with PDFs and policy documents.
Loyalty Program Data: Stored in Dynamics 365 and Dataverse.
Travel Advisory Content: Uses REST API with partner services.
Integration mechanisms -
Custom connectors must be used for internal APIs that lack prebuilt connectors.
HTTP request nodes may be used for lightweight external APIs.
Knowledge sources must be used for unstructured content.
Agent flows must be used to encapsulate reusable logic (e.g., rebooking).
Business requirements -
Omnichannel support -
Deploy the agent across web, mobile, and Teams with a consistent user experience. The Teams deployment must
also support internal staff.
Self-service capabilities -
The agent must handle common inquiries such as:
Flight status -
Booking and rebooking -
Loyalty program questions -
Travel policies and baggage rules
Human escalation -
If the agent cannot resolve an issue or the user requests help, it must:
Escalate to a human agent.
Transfer the conversation transcript and relevant context.
Redact any sensitive personal data before escalation.
Knowledge integration -
The agent must use scalable methods for knowledge integration and must not rely on manually authored Q&A
topics for each document.
Performance metrics -
First-contact resolution: +25%
Tier-1 call deflection: ≥20%
Response time: 90% of queries answered within 30 seconds
Accuracy: ≥95% for known FAQs -
CSAT: ≥85% for AI-handled interactions
Technical requirements -
Platform constraints -
No custom code is permitted; only Copilot Studio's built-in tools may be used.
All backend logic must be implemented using agent flows.
Markdown must be used for formatting (e.g., bold, bullet points); HTML is not supported.
Authentication -
Sign-in is required for personal data access.
Anonymous access is allowed for general inquiries.
User identity must be used for data access; shared or builder credentials must not be used.
Compliance and security -
Power Platform DLP policies must be enforced to block unauthorized data flows.
Responsible AI content moderation filters must be enabled.
Prompt modifications must be added to enforce tone, disclaimers, and refusal behavior.
Disclaimers must be applied consistently across all generative responses. Manual edits to individual topics must
be avoided.
Monitoring and maintenance -
All conversations and actions must be logged for auditing.
Weekly reviews of transcripts and metrics must be conducted.
Issues and constraints -
API rate limits: External APIs (e.g., flight status) have usage limits. Agent flows must handle retries and caching to
avoid exceeding quotas.
Knowledge base limits: Copilot Studio has limits on the number and size of indexed documents. Large files must be
split or summarized.
Generative answer risks: Generative responses must be constrained to avoid policy violations. Prompt
modifications and filters must be used to enforce tone, safety, and compliance.
User input variability: Users phrase questions in diverse ways. Topics must include varied trigger phrases and
fallback handling.
Authentication UX: The agent must clearly explain when sign-in is required and handle transitions smoothly across
channels.
Problem statement -
Blue Yonder Airlines must deploy a secure, scalable, and policy-compliant AI agent using Microsoft Copilot Studio.
The agent must deliver accurate, helpful, and safe responses across multiple channels, integrate with enterprise
systems, and support both anonymous and authenticated users. It must adhere to strict data protection and
Responsible AI standards while improving customer service efficiency and satisfaction.
You need to configure the agent in Copilot Studio to use internal and external partner knowledge sources to
answer user questions about the airline services.
Which two actions should you perform? Each correct answer presents part of the solution.
NOTE: Each correct selection is worth one point.
A
Use a Microsoft Graph connector to index the partner's travel advisory content.
B
Write individual Q&A pairs for each document as separate topics.
C
Enable unrestricted web search for the agent.
D
Add the internal policy documents as a knowledge source.
Correct Answer:
A. Use a Microsoft Graph connector to index the partner's travel advisory content.
Explanation:
Use a Microsoft Graph connector to index the partner's travel advisory content.
For structured or third-party partner data (like external travel advisory sites or repositories), a Microsoft
Graph connector is the ideal modern solution. It indexes the external data directly into the enterprise search
index, allowing Copilot Studio to safely ingest and query partner information without exposing it to the open
web.
D. Add the internal policy documents as a knowledge source.
Adding the internal policy documents directly as native knowledge sources in Copilot Studio allows the agent
to immediately use Retrieval-Augmented Generation (RAG) to ground answers based only on approved,
private company content.
Case Study -
This is a case study. Case studies are not timed separately from other exam sections. You can use as much exam
time as you would like to complete each case study. However, there might be additional case studies or other
exam sections. Manage your time to ensure that you can complete all the exam sections in the time provided. Pay
attention to the Exam Progress at the top of the screen so you have sufficient time to complete any exam sections
that follow this case study.
To answer the case study questions, you will need to reference information that is provided in the case. Case
studies and associated questions might contain exhibits or other resources that provide more information about
the scenario described in the case. Information provided in an individual question does not apply to the other
questions in the case study.
A Review Screen will appear at the end of this case study. From the Review Screen, you can review and change
your answers before you move to the next exam section. After you leave this case study, you will NOT be able to
return to it.
To start the case study -
To display the first question in this case study, select the "Next" button. To the left of the question, a menu
provides links to information such as business requirements, the existing environment, and problem statements.
Please read through all this information before answering any questions. When you are ready to answer a question,
select the "Question" button to return to the question.
Background -
Blue Yonder Airlines is a global carrier headquartered in Los Angeles, California, operating domestic and
international flights. The company serves millions of passengers annually through its website, mobile app, and call
centers. To improve customer service efficiency and reduce call center volume, Blue Yonder is deploying an AI
agent in Microsoft Copilot Studio.
The agent will handle customer inquiries across multiple channels – web chat, mobile app, and Microsoft Teams
(for internal support staff). It will answer questions, retrieve data from enterprise systems, and escalate to human
agents when needed.
The project is led by a cross-function team:
Product manager: Defines requirements and success metrics.
Lead agent author: Designs topics, intents, and generative behavior.
Flow designers: Build agent flows and integrations.
IT/security and compliance: Oversees identity, data protection, and Responsible AI (RAI) compliance.
Current environment -
Channels -
Public website: Embedded web chat
Mobile app: In-app chatbot -
Microsoft Teams: Internal support agent access
Identity and access -
Customers: Anonymous access for general inquiries (e.g., flight status, baggage policy).
Authentication is required for personal data access (e.g., bookings, loyalty points).
Internal staff: Authenticate via Microsoft Entra ID.
Data sources -
Reservation and Ticketing System (internal): REST API, no prebuilt connector with custom enterprise database.
Flight Status and Weather APIs (external): REST APIs with API keys.
Customer Support Knowledge Base: SharePoint library with PDFs and policy documents.
Loyalty Program Data: Stored in Dynamics 365 and Dataverse.
Travel Advisory Content: Uses REST API with partner services.
Integration mechanisms -
Custom connectors must be used for internal APIs that lack prebuilt connectors.
HTTP request nodes may be used for lightweight external APIs.
Knowledge sources must be used for unstructured content.
Agent flows must be used to encapsulate reusable logic (e.g., rebooking).
Business requirements -
Omnichannel support -
Deploy the agent across web, mobile, and Teams with a consistent user experience. The Teams deployment must
also support internal staff.
Self-service capabilities -
The agent must handle common inquiries such as:
Flight status -
Booking and rebooking -
Loyalty program questions -
Travel policies and baggage rules
Human escalation -
If the agent cannot resolve an issue or the user requests help, it must:
Escalate to a human agent.
Transfer the conversation transcript and relevant context.
Redact any sensitive personal data before escalation.
Knowledge integration -
The agent must use scalable methods for knowledge integration and must not rely on manually authored Q&A
topics for each document.
Performance metrics -
First-contact resolution: +25%
Tier-1 call deflection: ≥20%
Response time: 90% of queries answered within 30 seconds
Accuracy: ≥95% for known FAQs -
CSAT: ≥85% for AI-handled interactions
Technical requirements -
Platform constraints -
No custom code is permitted; only Copilot Studio's built-in tools may be used.
All backend logic must be implemented using agent flows.
Markdown must be used for formatting (e.g., bold, bullet points); HTML is not supported.
Authentication -
Sign-in is required for personal data access.
Anonymous access is allowed for general inquiries.
User identity must be used for data access; shared or builder credentials must not be used.
Compliance and security -
Power Platform DLP policies must be enforced to block unauthorized data flows.
Responsible AI content moderation filters must be enabled.
Prompt modifications must be added to enforce tone, disclaimers, and refusal behavior.
Disclaimers must be applied consistently across all generative responses. Manual edits to individual topics must
be avoided.
Monitoring and maintenance -
All conversations and actions must be logged for auditing.
Weekly reviews of transcripts and metrics must be conducted.
Issues and constraints -
API rate limits: External APIs (e.g., flight status) have usage limits. Agent flows must handle retries and caching to
avoid exceeding quotas.
Knowledge base limits: Copilot Studio has limits on the number and size of indexed documents. Large files must be
split or summarized.
Generative answer risks: Generative responses must be constrained to avoid policy violations. Prompt
modifications and filters must be used to enforce tone, safety, and compliance.
User input variability: Users phrase questions in diverse ways. Topics must include varied trigger phrases and
fallback handling.
Authentication UX: The agent must clearly explain when sign-in is required and handle transitions smoothly across
channels.
Problem statement -
Blue Yonder Airlines must deploy a secure, scalable, and policy-compliant AI agent using Microsoft Copilot Studio.
The agent must deliver accurate, helpful, and safe responses across multiple channels, integrate with enterprise
systems, and support both anonymous and authenticated users. It must adhere to strict data protection and
Responsible AI standards while improving customer service efficiency and satisfaction.
You need to ensure that every AI-generated response from the agent in Copilot Studio includes a disclaimer that
complies with the company's security and governance policies.
Which two actions should you perform? Each correct answer presents part of the solution.
NOTE: Each correct selection is worth one point.
A
Add a greeting message that includes the disclaimer.
B
Add a prompt modification in the generative answers node settings.
C
Create a disclaimer topic that always runs first.
D
Disable generative answers and use only pre-authored responses.
E
Edit every topic's first message to include the disclaimer.
Correct Answer:
A. Add a greeting message that includes the disclaimer.
Explanation:
A. Add a greeting message that includes the disclaimer.
B. Add a prompt modification in the generative answers node settings.
Action B (Core Enforcer): Adding a custom instruction or prompt modification within the generative answers
node settings (or the global copilot-level custom instructions that govern it) is the only way to dynamically
force the LLM to consistently append or integrate the compliance disclaimer into every single piece of
content it dynamically generates via Retrieval-Augmented Generation (RAG).
Action A (User Experience & Governance Alignment): In enterprise security and compliance frameworks, a
prompt modification should always be accompanied by a transparent upfront disclosure. Providing the legal
disclaimer in the initial Greeting message ensures the user is legally notified of the Al's nature at the
absolute start of the session, establishing a compliant user experience foundation.
DRAG DROP -
Case Study -
This is a case study. Case studies are not timed separately from other exam sections. You can use as much exam
time as you would like to complete each case study. However, there might be additional case studies or other
exam sections. Manage your time to ensure that you can complete all the exam sections in the time provided. Pay
attention to the Exam Progress at the top of the screen so you have sufficient time to complete any exam sections
that follow this case study.
To answer the case study questions, you will need to reference information that is provided in the case. Case
studies and associated questions might contain exhibits or other resources that provide more information about
the scenario described in the case. Information provided in an individual question does not apply to the other
questions in the case study.
A Review Screen will appear at the end of this case study. From the Review Screen, you can review and change
your answers before you move to the next exam section. After you leave this case study, you will NOT be able to
return to it.
To start the case study -
To display the first question in this case study, select the "Next" button. To the left of the question, a menu
provides links to information such as business requirements, the existing environment, and problem statements.
Please read through all this information before answering any questions. When you are ready to answer a question,
select the "Question" button to return to the question.
Background -
Blue Yonder Airlines is a global carrier headquartered in Los Angeles, California, operating domestic and
international flights. The company serves millions of passengers annually through its website, mobile app, and call
centers. To improve customer service efficiency and reduce call center volume, Blue Yonder is deploying an AI
agent in Microsoft Copilot Studio.
agents when needed.
The project is led by a cross-function team:
Product manager: Defines requirements and success metrics.
Lead agent author: Designs topics, intents, and generative behavior.
Flow designers: Build agent flows and integrations.
Data sources -
The agent will handle customer inquiries across multiple channels – web chat, mobile app, and Microsoft Teams
(for internal support staff). It will answer questions, retrieve data from enterprise systems, and escalate to human
IT/security and compliance: Oversees identity, data protection, and Responsible AI (RAI) compliance.
Current environment -
Channels -
Public website: Embedded web chat
Mobile app: In-app chatbot -
Microsoft Teams: Internal support agent access
Identity and access -
Customers: Anonymous access for general inquiries (e.g., flight status, baggage policy).
Authentication is required for personal data access (e.g., bookings, loyalty points).
Internal staff: Authenticate via Microsoft Entra ID.
Reservation and Ticketing System (internal): REST API, no prebuilt connector with custom enterprise database.
Flight Status and Weather APIs (external): REST APIs with API keys.
Customer Support Knowledge Base: SharePoint library with PDFs and policy documents.
Loyalty Program Data: Stored in Dynamics 365 and Dataverse.
Travel Advisory Content: Uses REST API with partner services.
Integration mechanisms -
Custom connectors must be used for internal APIs that lack prebuilt connectors.
HTTP request nodes may be used for lightweight external APIs.
Knowledge sources must be used for unstructured content.
Agent flows must be used to encapsulate reusable logic (e.g., rebooking).
Business requirements -
Omnichannel support -
Deploy the agent across web, mobile, and Teams with a consistent user experience. The Teams deployment must
also support internal staff.
Self-service capabilities -
The agent must handle common inquiries such as:
Flight status -
Booking and rebooking -
Loyalty program questions -
Travel policies and baggage rules
Human escalation -
If the agent cannot resolve an issue or the user requests help, it must:
Escalate to a human agent.
Transfer the conversation transcript and relevant context.
Redact any sensitive personal data before escalation.
Knowledge integration -
The agent must use scalable methods for knowledge integration and must not rely on manually authored Q&A
topics for each document.
Performance metrics -
First-contact resolution: +25%
Tier-1 call deflection: ≥20%
Response time: 90% of queries answered within 30 seconds
Accuracy: ≥95% for known FAQs -
CSAT: ≥85% for AI-handled interactions
Technical requirements -
Platform constraints -
No custom code is permitted; only Copilot Studio's built-in tools may be used.
All backend logic must be implemented using agent flows.
Markdown must be used for formatting (e.g., bold, bullet points); HTML is not supported.
Authentication -
Sign-in is required for personal data access.
Anonymous access is allowed for general inquiries.
User identity must be used for data access; shared or builder credentials must not be used.
Compliance and security -
Power Platform DLP policies must be enforced to block unauthorized data flows.
Responsible AI content moderation filters must be enabled.
Prompt modifications must be added to enforce tone, disclaimers, and refusal behavior.
Disclaimers must be applied consistently across all generative responses. Manual edits to individual topics must
be avoided.
Monitoring and maintenance -
All conversations and actions must be logged for auditing.
Weekly reviews of transcripts and metrics must be conducted.
Issues and constraints -
API rate limits: External APIs (e.g., flight status) have usage limits. Agent flows must handle retries and caching to
avoid exceeding quotas.
Knowledge base limits: Copilot Studio has limits on the number and size of indexed documents. Large files must be
split or summarized.
Generative answer risks: Generative responses must be constrained to avoid policy violations. Prompt
modifications and filters must be used to enforce tone, safety, and compliance.
User input variability: Users phrase questions in diverse ways. Topics must include varied trigger phrases and
fallback handling.
Authentication UX: The agent must clearly explain when sign-in is required and handle transitions smoothly across
channels.
Problem statement -
Blue Yonder Airlines must deploy a secure, scalable, and policy-compliant AI agent using Microsoft Copilot Studio.
The agent must deliver accurate, helpful, and safe responses across multiple channels, integrate with enterprise
systems, and support both anonymous and authenticated users. It must adhere to strict data protection and
Responsible AI standards while improving customer service efficiency and satisfaction.
You need to determine which authentication model should be applied to each Blue Yonder Copilot interaction
scenario to comply with the company's security and governance requirements.
Which authentication requirement should you apply to each scenario? To answer, move the appropriate
authentication requirements to the correct user scenarios. You may use each authentication requirement once,
more than once, or not at all. You may need to move the split bar between panes or scroll to view content.
NOTE: Each correct selection is worth one point.
A
Correct Answer:
A.
Explanation:
Baggage allowance is general, non-sensitive public information. Customers should be able to view these
details directly on a public website without creating an account or logging in, making Allow anonymous
access the appropriate choice.
Reviewing personal upcoming trips involves accessing Personally Identifiable Information (PII) and private
booking records. To ensure data privacy, the copilot must securely identify who the user is by forcing a
customer sign-in using an account.
Since an internal customer support representative is accessing the system within the company's internal
tenant (Microsoft Teams) to view sensitive loyalty customer profiles, they must authenticate securely via the
enterprise identity provider system, which is Microsoft Entra ID.
DRAG DROP -
A company has an existing custom connector that is approved and available in the environment. A builder wants an
agent in Copilot Studio to call the connector during a conversation to retrieve information from an internal system.
To meet the business needs, the solution must meet the following requirements:
The agent must make the connector available for topic steps.
The agent must run the connector call with a valid connection.
The connector call must receive the required input values at runtime.
You need to configure the agent so the custom connector can be used as a tool.
What should you configure for each requirement? To answer, move the appropriate configurations to the correct
requirements. You may use each configuration once, more than once, or not at all. You may need to move the split
bar between panes or scroll to view content.
NOTE: Each correct selection is worth one point.
A
Correct Answer:
A.
Explanation:
In Microsoft Copilot Studio, actions or connectors must be registered or enabled within the bot's plugin
architecture to become visible. Choosing Add the connector as a tool in the agent allows authors to select
and execute the custom connector inside regular topic authoring canvas steps.
Connectors are definitions of APIs, but they cannot authenticate or talk to a backend without a concrete
security context. You must Create or reuse a connection for the connector to establish valid authentication
credentials (like OAuth or API keys) so the engine can execute the request successfully.
For a custom connector tool to dynamically fetch accurate data (such as searching for a flight using a specific
booking ID), data collected from the user during the chat session must pass into the API request. You Map
topic variables to the tool inputs to satisfy this requirement.
DRAG DROP -
A company needs to ground an agent in Copilot Studio answers using live enterprise data from a supported system
via a Microsoft Power Platform connector.
To meet the business needs, the builder must meet the following requirements:
Authenticate using a valid connection.
Add the connector as a real-time knowledge source.
Select the tables for knowledge grounding.
You need to add a Power Platform connector as a real-time knowledge source for the agent.
In which order should you perform the actions? To answer, move all actions from the list of actions to the answer
area and arrange them in the correct order.
A
Correct Answer:
A.
Explanation:
Select Add knowledge from the agent Knowledge experience.
Start from the agent configuration area. The Knowledge experience is where you add external data sources.
Select the real-time connector from the Add knowledge dialog.
In the Add knowledge dialog, choose the appropriate connector type. For REST API data, select the real-time
connector option so the agent can retrieve information dynamically rather than storing a static copy.
Select Sign in and create a new connection or reuse an existing connection.
The connector requires authentication. You either create a new connection by providing credentials/details or
select an existing connection that already has the required authentication settings.
Select the tables to include as the knowledge source.
After the connection is established, the available data objects/tables exposed by the connector are displayed.
Choose which tables or data entities should be available to the agent as knowledge.
Select Add to agent to complete the connection.
Confirm the selection and attach the configured knowledge source to the agent. The agent can now use the
connected REST API data when responding to user queries.
HOTSPOT -
You deploy an agent in Microsoft Copilot Studio that triggers a cloud flow to update customer re
Dataverse.
You observe the following after deploying the agent:
Several runs fail due to a temporary authentication issue.
The flow continues to trigger and generate additional failed runs.
You must:
Stop additional failed executions while troubleshooting.
Process a failed execution after resolving the authentication issue.
Validate if the most recent executions succeeded immediately after resolution.
You need to use the appropriate monitoring and management actions to restore normal flow ope
successful execution.
Which action should you perform for each requirement? To answer, select the appropriate options
area.
NOTE: Each correct selection is worth one point.
A
Correct Answer:
A.
Explanation:
Disable the flow.
Disabling the flow prevents the trigger from firing and stops any new runs from being created while you
investigate the issue. Deleting the flow is permanent, canceling only affects one run, and modifying the trigger
condition is unrelated to temporarily stopping executions.
Resubmit the run.
After fixing the authentication problem (for example, updating the connection), use Resubmit the run to
execute the failed flow instance again. This retries the same inputs without waiting for a new trigger event.
Review the Activity history.
The Activity history (Run history) displays the latest flow executions, including their status (Succeeded,
Failed, Running), timestamps, and error details. This is the quickest way to verify whether the issue has been
resolved. Analytics provides aggregated trends rather than immediate run-by-run validation.
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