Agentic AI goes live inside a high-volume, compliance-critical insurance workflow
A major European insurer has deployed Global AI's agentic platform to automate a document-heavy back-office process under strict regulatory oversight. The governed AI layer sits inside existing customer-facing channels and core systems, replacing a fully manual validation step. These workflows are among the hardest to automate in insurance due to audit sensitivity, regulatory scrutiny, and reputational exposure.
What was deployed
The platform runs as an on-premise orchestration environment within the insurer's enterprise security framework. It adheres to internal data governance, privacy controls, and supervisory requirements. Crucially, the system is built for deterministic outcomes-not probabilistic experimentation-which regulators increasingly expect.
Why this matters for insurers
This deployment proves agent-based systems can operate in audit-driven environments where transparency, repeatability, and governance carry the same weight as speed. It addresses a core objection many carriers raise: "Will AI increase risk or reduce it?" Here, the outcome was lower processing costs, faster resolution timelines, and reduced compliance risk through consistent, traceable validation.
Results delivered
- Standardized decision logic replaces discretionary manual review.
- Full audit visibility across every step of the validation workflow.
- Measurable cost reductions and shorter customer turnaround times.
- Improved compliance posture through governed execution and traceability.
Leadership view
Darko Horvat, chairman and CEO of Global AI, said this marks a shift beyond pilots: "This project validates that agentic AI is ready for enterprise-scale insurance operations, not just experimentation." He added that an on-premise orchestration model enabled automation of a complex, audit-sensitive workflow while preserving control, explainability, and regulatory alignment.
How to evaluate agentic AI for your operation
- Architecture: Prefer on-prem or private cloud with clear data residency controls.
- Determinism: Require explicit decision policies, versioned prompts, and reproducible runs.
- Auditability: Log inputs, outputs, tools used, model versions, and human interventions.
- Controls: Enforce human-in-the-loop for edge cases and policy exceptions.
- Security: Integrate with SSO, role-based access, key management, and data loss prevention.
- Compliance: Map workflows to internal policies and external rules (e.g., GDPR).
- Risk: Treat the platform under model risk management with periodic reviews and re-validation.
- Reliability: Define SLAs/SLOs for latency, throughput, and failure handling with safe fallbacks.
- Testing: Use gold-label test sets, counterfactuals, and stress tests before go-live.
- Change management: Version everything-policies, prompts, tools-and document approvals.
Metrics to track post-go-live
- Straight-through processing rate and exception rate by case type.
- Average handling time and end-to-end cycle time.
- Error rate, rework rate, and compliance findings.
- Cost per case and capacity uplift without headcount increases.
Regulatory context
For European carriers, privacy and supervisory expectations are table stakes. Ensure alignment with GDPR and adopt a risk framework such as the NIST AI Risk Management Framework to structure controls, testing, and monitoring.
What to do next
- Pick a high-volume, rules-heavy process with clear policy logic and frequent audits.
- Start with a governed agentic layer that augments existing systems rather than replacing them.
- Establish an AI governance board (ops, compliance, legal, security) before buildout.
- Run a controlled rollout with tight metrics and a fast feedback loop.
About Global AI
Global AI traces its roots to 2009 (formerly Wall Street Media Co.) and rebranded in October 2023 to focus on artificial intelligence and data-driven solutions. Its Agentic AI Platform targets regulated, mission-critical environments where compliance, security, and operational integrity outweigh speed. The company serves insurers, financial institutions, and asset managers seeking automation without surrendering oversight or audit control.
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