Real-Time Insights: Transform Claims

Key insights

• Claim Advisor (SharePoint Agent): Shrushti Shah demoed a custom agent that consolidates claims, policy, and incident documents from a SharePoint library into real-time, structured summaries and suggested follow-ups.
  
• Model-based field extraction: AI models pull key fields and auto-summarize complex claims documents to reduce manual data entry and speed adjuster reviews.
  
• Permission-scoped retrieval & privacy: The agent enforces SharePoint permissions so adjusters only access authorized data, supporting compliance and data security needs.
  
• Real-time insights & action roadmap: The solution delivers instant contextual insights and follow-up suggestions; current demos focus on retrieval only, with a roadmap to add action-taking via Copilot Studio.
  
• Microsoft 365 & Power Platform integration: Built on SharePoint and the Power Platform, the agent fits existing IT environments, follows licensing prerequisites, and scales with insurer workflows.
  
• Business impact: The approach speeds claims processing, improves accuracy, strengthens compliance, and lets insurers scale operations without matching headcount growth.
  

Overview: A live demo that points to faster claims work

Shrushti Shah demonstrated a prototype called the Claim Advisor during a Microsoft community call on July 1, 2025. The demo, presented as part of the Microsoft 365 & Power Platform program, showed how a SharePoint Agent can bring together claim, policy, and incident documents into a single, structured view for adjusters. Consequently, the tool delivers concise summaries and suggested next steps so adjusters can act faster and with more confidence.
Moreover, the session highlighted real-time processing and how integration with existing SharePoint document libraries can reduce the time spent searching for information. This article summarizes the video, explains the technology, and discusses practical tradeoffs and challenges for insurers considering adoption.

How the solution works in practice

The demo relied on model-based extraction to pull key fields from claims documents and then present those findings as structured, human-readable summaries. In addition, the agent used permission-scoped retrieval so adjusters only see data they are allowed to access, which preserves privacy and compliance. The system currently focuses on retrieval and summarization, while a roadmap aims to extend it to take actions via Copilot Studio in the future.
Therefore, adjusters receive a quick, consolidated view that links to source documents and suggests follow-ups. This design reduces manual copy-and-paste work and helps teams prioritize the tasks that matter most for each claim.

Security, governance, and licensing considerations

Importantly, the demo stressed privacy safeguards and permission checks to meet regulatory requirements common in insurance. Furthermore, the solution requires specific licensing and configuration within the Microsoft 365 ecosystem, so organizations must plan procurement and governance early. While these safeguards protect sensitive data, they also add setup complexity and may extend time-to-value for smaller teams.
Consequently, insurers must weigh the protection of customer data against the cost and effort of implementing comprehensive access controls. In practice, this means balancing security, compliance, and speed of deployment when choosing which claims to onboard first.

Benefits and tradeoffs for claims operations

The most visible benefit is efficiency: adjusters can close information gaps faster and reduce repetitive data entry, which directly lowers operational cost. At the same time, accuracy depends on the quality of field extraction models and the consistency of document formats, so insurers should expect some tuning and validation work. Moreover, while real-time summaries help triage cases, overreliance on automated suggestions without human oversight can introduce risks such as missed context or incorrect follow-up actions.
Thus, teams will need to design processes that combine AI-driven summaries with human review, especially for complex or high-value claims. In short, the balance between automation and human control determines whether the system improves throughput without sacrificing quality.

Roadmap, limits, and adoption challenges

The demo noted current limits: the agent performs retrieval-only operations today and does not yet take automated actions on claims. However, the plan to integrate with Copilot Studio envisions action-taking assistants that could open workflows, draft communications, or trigger approvals. Still, moving from retrieval to action raises new challenges, including stricter governance, auditability, and broader licensing needs.
Additionally, practical adoption will require careful change management, training, and integration with legacy systems. Insurers must also consider latency, model accuracy, and cost as they scale the tool across many claims and geographies.

Conclusion: practical next steps for insurers

Overall, the demo illustrates a meaningful step toward faster, data-driven claim handling by combining SharePoint document management with AI summarization. Yet while the potential gains are clear, organizations need to plan for licensing, governance, and model validation to fully realize those benefits. Therefore, insurers should pilot the approach on a subset of claims, measure accuracy and time savings, and iterate on permissions and workflows before broader rollout.
In the end, adopting a tool like the Claim Advisor offers clear efficiency advantages, but it also requires deliberate tradeoffs and sustained governance to ensure it delivers safe, reliable outcomes for both adjusters and policyholders.

Keywords

real-time claims processing, AI-powered claims adjustment, insurance claims automation, claims analytics platform, real-time fraud detection, predictive claims modeling, telematics-driven claims, customer-centric claims experience