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Grounding uncertainty prevents fabricated specific claims. It would support safe answer when evidence is absent, not the stated current operational data rather than stale export.

Source stewardship reduces grounding in obsolete versions. It would support a current authoritative document reference, not the stated current operational data rather than stale export.

Citations allow checking statements against evidence. Its purpose is traceable grounded policy statement; the specified need is current operational data rather than stale export.

Connector refresh keeps indexed items aligned with source changes. The action is relevant to up-to-date external search index rather than secure retrieval of connected external content.

Runtime operations are distinct from search grounding over indexed material. This helps with live action against a business system instead of the required secure retrieval of connected external content.

Missing ACL mapping can lead to unintended search exposure. This helps with corrected external item authorization instead of the required secure retrieval of connected external content.

File labels provide authoritative classification state for retrieved work content. That addresses source-document classification evidence, whereas the current case requires restriction of classified generated content movement.

AI security telemetry can identify supported sensitive data interaction patterns. It is used for detection of sensitive prompt content; this scenario calls for restriction of classified generated content movement.

Controls on the underlying source govern what data a user can access. That addresses consistent source access enforcement, whereas the current case requires restriction of classified generated content movement.

Rights protection travels with the content when supported. It would support persistent financial-file control, not the stated removal of internal oversharing.

Data loss prevention provides incident context and prevention actions. Its purpose is outbound sensitive-mail incident response; the specified need is removal of internal oversharing.

DSPM for AI consolidates AI exposure findings and control opportunities. It would support AI-related data exposure reduction, not the stated removal of internal oversharing.

Human control mitigates high-impact automation risks. This helps with accountable irreversible account deletion instead of the required least-data disclosure by an AI tool.

Responsible AI transparency avoids misleading users about the system. This helps with informed AI output interpretation instead of the required least-data disclosure by an AI tool.

Purpose limitation and governance constrain sensitive processing. The action is relevant to accountable processing of customer information rather than least-data disclosure by an AI tool.

Anonymous links may create an unintended access path beyond tenant membership. It is used for closure of public sharing exposure; this scenario calls for stopping unintended broad directory access.

AI activity telemetry records supported user interactions and classifications. That addresses observational AI usage evidence, whereas the current case requires stopping unintended broad directory access.

A user cannot ground answers in inaccessible tenant files. That addresses diagnosing absent authorized source, whereas the current case requires stopping unintended broad directory access.

Copilot can surface already-accessible overshared content. It would support eliminating an inherited oversharing root cause, not the stated summarizing accessible mailbox content.

Security trimming and individual context yield different retrieved evidence. Its purpose is explaining user-specific Copilot answers; the specified need is summarizing accessible mailbox content.

Copilot respects effective user access rather than granting new file rights. It would support denying retrieval of an inaccessible source, not the stated summarizing accessible mailbox content.

Correctly mapped access lists are needed for secure external content retrieval. This helps with connector-grounded security trimming instead of the required preventing unapproved contractor discovery.

Grounding checks help distinguish actual retrieved facts from generated claims. The action is relevant to verification against authorized evidence rather than preventing unapproved contractor discovery.

Microsoft 365 Copilot accesses work content under the user's entitled resource scope. This helps with ordinary user-scoped work grounding instead of the required preventing unapproved contractor discovery.

Encrypted label permissions constrain eligible readers and service processing. That addresses enforcement of protected document rights, whereas the current case requires authorized summary of a labeled source.

Supported Copilot data controls can restrict processing of classified items. That addresses source-specific AI processing restriction, whereas the current case requires authorized summary of a labeled source.

Labels provide consistent handling guidance for sensitive work content. It is used for end-user classification of source data; this scenario calls for authorized summary of a labeled source.

Inclusive design helps avoid excluding people because of disabilities or circumstances. Its purpose is usable AI experience across abilities; the specified need is intelligible AI decision context.

Responsible AI fairness focuses on unjustified disparate treatment. It would support nondiscriminatory model behavior, not the stated intelligible AI decision context.

Robustness evaluation reduces harmful surprises and inconsistent operation. It would support dependable operation under atypical inputs, not the stated intelligible AI decision context.

Privacy principles reduce unnecessary processing and disclosure. This helps with protection of sensitive personal information instead of the required verified high-stakes summary accuracy.

Accountability identifies responsible humans for monitoring and correction. The action is relevant to clear ownership of AI failures rather than verified high-stakes summary accuracy.

Accountability retains control of high-impact actions with authorized decision-makers. This helps with human oversight of consequential action instead of the required verified high-stakes summary accuracy.