From Fragmented Legacy Systems to an Intelligent Operating Layer
For large enterprises, growth ambitions increasingly collide with a messy reality: decades of legacy systems, disconnected tools, and inconsistent processes. Nowhere is this more visible than in insurance, where sprawling advisor networks and complex products sit on top of siloed software. Traditional transformation programs have focused on digitizing individual workflows, but that approach rarely delivers true operational standardization across markets. AI agents for enterprise environments are shifting the paradigm. Instead of replacing core systems outright, agent-based platforms layer intelligence on top of existing infrastructure, orchestrating data, workflows, and decisions in real time. This architecture allows organizations to keep their mission-critical legacy systems while gaining an adaptive, AI-driven “brain” that coordinates front- and back-office activities. As demand for AI rises far faster than most firms can rebuild their technology stacks, this model offers a pragmatic, scalable path to legacy system integration and enterprise-wide operational standardization.
100,000 Insurance Agents, 20 Markets, One AI-Orchestrated Platform
The growth challenge facing one global insurance group illustrates the stakes. Its network of more than 100,000 advisors, built over a century and spanning 20 countries, had become a bottleneck. Advisors were juggling fragmented tools, scattered customer data, and inconsistent product information, relying mainly on personal experience instead of unified, data-driven guidance. Despite substantial untapped potential, growth stagnated. An AI-powered platform, iSuite, developed by Vietnamese engineers, tackled the issue not by adding yet another point solution but by unifying core sales processes into a single environment. AI agents guided the entire journey—from customer engagement and advisory to policy issuance—using real-time data instead of ad hoc judgment. Within a year, new contract value rose by 33 per cent and the number of MDRT-qualified advisors increased by 25 per cent, while decision-making became more consistent and processing times shortened across the network.
Agent-Based Architecture: Standardization Without Rip-and-Replace
The core innovation behind platforms like iSuite is their agent-based architecture. Rather than forcing enterprises to rip out entrenched core systems, AI agents sit as an overlay, coordinating tasks, data flows, and decisions across heterogeneous applications. In the insurance case, this meant embedding AI into every interaction between the company, its agents, and customers, effectively creating a new operational layer above existing systems. The result is real-time operational standardization: agents ensure that every advisor follows consistent, optimized steps while still adapting to local market specifics. For insurers, this model also supports insurance software automation in areas such as onboarding, product recommendation, and policy issuance. Critically, the platform can scale to orchestrate workflows for more than 100,000 distributed users while maintaining governance and compliance. This shows how AI agents in enterprise environments can deliver immediate value without the disruption and risk of full-system replacement projects.
Automating Claims: AI Agents in Back-Office Transformation
Agent-based AI is not only reshaping sales; it is also transforming back-office operations such as claims. At a Europe-based global insurer, fragmented workflows and heavy manual processing led to long settlement times and rising costs. Using a similar approach, the entire claims value chain was redesigned with AI agents orchestrating every step, from claim intake and assessment through to payout. Integrated Intelligent Document Processing and automated rule engines allowed documents, rules, and decisions to flow seamlessly in real time, eliminating many manual handoffs. Processing efficiency increased by 60 per cent and customer satisfaction reached 96.3 per cent. This illustrates how insurance software automation can be achieved without discarding existing systems: AI agents bridge gaps between legacy platforms, standardize decision logic, and enforce consistent service levels. For enterprises, it is a blueprint for modernizing critical operations while preserving hard-earned investments in legacy infrastructure.
Vietnamese AI Steps Onto the Global Enterprise Stage
Behind these deployments is a notable shift in the global enterprise software market: emerging AI innovators are no longer just implementers; they are platform creators. iSuite, built by Vietnamese engineers at FPT, has been rolled out to more than 10 insurers and insurtech companies worldwide, supported by two decades of industry experience with over 200 insurance clients and a team of more than 3,000 experts. Recognized with the “AI & Machine Learning Innovation” award at InsurInnovator Connect Asia 2026, the platform demonstrates that competitive advantage now hinges less on size and more on how intelligently an organization operates. McKinsey research shows most enterprises are stuck at pilot-stage AI adoption, with deep deployment rarely exceeding 10 per cent of functions. Platforms like iSuite address this execution gap, translating AI ambition into fully operationalized, scalable systems that align technology, data, and people across complex global enterprises.