Preparing Enterprise Data for AI and Microsoft Copilot Success
A U.S. based insurance group deployed Microsoft Copilot and discovered its answers reflected outdated policy wordings, unreachable legacy records, and years of inherited oversharing. Artic Consulting assessed readiness, remediated the content estate, opened legacy policy and claims data through a governed access layer, and corrected permissions before wider rollout — giving underwriting and claims teams AI answers they could verify and trust.
Client Overview
Our client is a U.S. based insurance group underwriting commercial property, casualty, and specialty lines through a network of brokers, regional service centers, and claims operations.
Leadership had approved Microsoft Copilot for underwriting, claims, and corporate teams, expecting faster policy research, quicker claim file summaries, and less manual document handling. Early usage told a different story. Copilot answered confidently from whatever content it could reach, and much of what it could reach was outdated, duplicated, or never intended to be widely visible.
The issue was not the assistant. It was the estate underneath it. Policy records lived in a decades-old administration platform, claim documentation sat in scanned archives, and underwriting knowledge was scattered across team sites accumulated over years of acquisitions.
The organization needed to prepare its data before expanding AI further.
Requirements
The organization wanted trustworthy AI answers grounded in accurate, properly permissioned business content.
Trusted Data Foundation
Make underwriting, policy, and claims information discoverable and reliable for AI-assisted work.
Legacy Estate Modernization
Expose records held in aging administration and document platforms without a disruptive core replacement.
Permission and Sensitivity Controls
Ensure Copilot surfaces content only to users entitled to see it under regulatory and contractual obligations.
Sustainable Data Governance
Keep content accurate, labelled, and owned as AI usage widens across lines of business.
Challenges:
As Copilot reached more employees, the quality of its answers exposed long-standing weaknesses in how information was stored, classified, and shared.
Unreliable Source Content
Superseded policy wordings, expired endorsement templates, and abandoned drafts sat alongside current versions with no signal distinguishing them.
Records Locked in Legacy Platforms
Policy and claims history lived in systems built long before AI, with limited APIs, inconsistent identifiers, and scanned documents carrying no usable text layer.
Overly Broad Access Inherited Over Time
Team sites created during earlier reorganizations and acquisitions carried permissions far wider than current policy would allow, and Copilot made that exposure visible immediately.
No Clear Content Ownership
Large portions of the document estate had no named steward responsible for accuracy, retention, or removal.
Growth Constraints
AI Answers Only as Good as the Estate
Copilot could reason across the organization’s content instantly, but scattered records, legacy repositories, and inherited permissions meant confident answers could not be safely trusted.
Our solution
Artic Consulting sequenced the work so that every expansion of Copilot rested on content that was accurate, permissioned, and owned.
Copilot Readiness Assessment
Examined the document estate, repository sprawl, oversharing patterns, duplication levels, and retention gaps to determine which business areas were ready for AI grounding and which required remediation first.
Content Remediation and Lifecycle Cleanup
Retired superseded wordings, consolidated duplicate repositories, archived dormant sites, and applied retention rules so obsolete underwriting and claims material stopped competing with current records.
Legacy Data Access Layer
Built an integration layer that surfaced policy and claims records from the administration platform through governed, read-optimized structures in Microsoft Fabric, avoiding a core system replacement while making authoritative records reachable.
Document Digitization and Enrichment
Applied OCR and structured extraction to scanned claim files, then indexed them through Azure AI Search with metadata for line of business, policy period, and document type so retrieval returned the right file rather than the nearest match.
Sensitivity Labelling and Access Correction
Used Microsoft Purview and SharePoint Advanced Management to classify regulated and confidential content, correct inherited oversharing, and restrict Copilot grounding to entitled audiences.
Data Stewardship Model
Assigned named owners by line of business, with review cadences covering accuracy, labelling, retention, and approval of new content sources entering the AI estate.
We assumed our Copilot results were a tuning problem. They were a data problem. Artic showed us exactly which content was safe to ground against, fixed what wasn’t, and gave our teams a way to keep it that way.
Chief Data Officer.
Organizational benefits
Grounded, Verifiable Answers
Underwriters and claims staff received Copilot responses drawn from current, authoritative records rather than superseded material.
Legacy Records Made Usable
Policy and claims history held in aging platforms became accessible to AI experiences without replacing the systems of record.
Reduced Oversharing Exposure
Inherited permissions were corrected before wider rollout, limiting the risk of regulated content surfacing to unintended audiences.
Searchable Claims Archive
Digitized and enriched claim documentation became retrievable in seconds instead of requiring manual file review.
Clear Content Accountability
Every grounded source had an owner responsible for keeping it accurate and appropriately classified.
Repeatable Readiness Path
New lines of business could be onboarded to Copilot through a defined remediation and governance sequence.
Conclusion
The organization did not need a better assistant. It needed content its assistant could safely rely on.
By assessing readiness before expansion, remediating the document estate, opening legacy records through a governed access layer, and correcting permissions ahead of rollout, Artic Consulting helped the insurer turn a promising deployment into dependable daily support for underwriting and claims work.
The organization now treats data readiness as the prerequisite for every AI initiative it approves, rather than a problem discovered after go-live.
Prepare Your Data Before You Scale Copilot
Assess content quality, legacy accessibility, and permission exposure so your AI investments return answers your teams can act on.
