Rethinking Life, Annuity and Benefits PAS Systems Part 4

 Insurance Workflow and Process in the Age of Agentic AI

The Problem with Legacy Workflows

A fundamental component of insurance processing is workflow. Historically, older Policy Administration Systems (PAS) integrated workflows directly into the core system, providing full access to all capabilities and shared data. While initially efficient, this architecture became problematic as non-expert users required access to core functionalities, driving a demand for better customer experiences (CX) for both end-customers and internal staff.

This led to the rise of specialized vendors focused on extending, simplifying, or securing workflows outside the core admin system.

The drive to modern, deconstructed PAS demands a fresh perspective on workflow design, especially as Agentic AI becomes central to new operational strategies. Traditional workflows are often fragile, built on rigid, bespoke APIs or legacy screen scraping, making them susceptible to failure with any system change. A modern approach must embrace an ecosystem-centric architecture for end-to-end insurance processes.

The Deconstructed Policy Administration Architecture

In a modern, deconstructed PAS, the System of Record (SOR) focuses primarily on transactions, not end-to-end workflows.

The expectation is that all external access—customer-facing, distribution-facing, and customer service group—will be mediated through an extended workflow layer that connects to the SOR, the calculation engine, and other contributing systems (e.g., billing and claims).

What makes this possible today are two trends that are making real headway in the insurance technology industry:

• API-First Approach: Some innovative insurers are thinking the comprehensive end-to-end platform approach, looking to API-first for more flexibility and easier ecosystem access. A modular, API-first approach is critical for successful deconstruction.

• Coreless Vendors: A growing number of insurance process vendors are adopting a "coreless" strategy. They intentionally avoid providing the SOR and calculation engine, choosing instead to own everything around it, treating the core functions as technical capabilities accessed via APIs. This model aligns perfectly with the deconstructed architecture.

Design by Chuck Johnston Rendering by NotebookLM

A Layered Approach to Agentic Workflow

Building an application pattern using these principles requires a distinct, layered approach to workflow, tailored for specific roles and expertise.

1. The Cockpit Layer (Expert-Centric)

The Cockpit Layer is the closest to the SOR, calculation engine, and ancillary systems. It is the domain of the expert user.

This layer provides deep, granular control over core systems via interfaces that require significant expertise in both the business process and system operation.

It enables execution of legitimate, complex transactions that require expertise and approval authority. This includes high-impact actionsactions like overriding premium processing, granting extended grace periods (e.g., during a disaster) and adjusting errors with a material financial impact on the policy.

Due to the deterministic and high-authority nature of the work, and the expertise of the users in this role Generative AI functions primarily as an advisor, second set of eyes, and regulatory/compliance oversight tool, potentially flagging transactions that require additional internal approvals.

2. The Service Layer (Internal & Partner-Facing)

The Service Layer is designed for internal customer service representatives, distribution staff (including new business processing and service), and third-party services (TPAs) like billing or claims administrators.

 Generative AI is critical for providing detailed product and contractual information and real-time coaching on scenario handling and regulatory compliance. Also, agentic AI can prepare transactions (e.g., drafting the necessary paperwork for a policy loan or surrender and setting up the multiple transactions necessary in draft form) based on the customer interaction.

Agentic AI transaction execution requires human sign-off at the service desk level or higher, at least for today.

For TPAs, the insurer may provide a complete workflow system or APIs. In the API scenario, a robust security and authorization layer is mandatory to protect internal systems from errors or bad actors.

This group does not have access to the Cockpit layer.

3. The Customer Journey Layer (End-Customer-Facing)

The final layer focuses on the end-customer experience (CX).

This layer requires excellent CX software backed by extensive, curated customer information and secure transaction connectivity back to the core SOR. Consumers require strong guardrails to simplify complex insurance transactions and protect the consumer from unintended consequences.

Generative AI plays a dominant role by helping customers easily access information and perform self-service tasks leveraging Agentic AI heavily with service desk oversight which will gradually shift from approval of every transaction to quality control and exception handling over time.

It is important to remember a key premise of this series of articles is that it is based on what is available now or in early 2026. Agentic AI’s ability to play a much bigger role in insurance workflow going forward is evident but currently most of the solutions I believe are likely to succeed are taking a hybrid Gen AI and rules-based approach that will evolve over time as the technology matures.

This is the end of the “Rethinking Life, Annuity and Benefits PAS Systems” series for now.

Thank you for your attention and good luck deconstructing.