How Persistent helped a leading U.S. retirement and savings services provider move from fragmented AI adoption to a governed GenAI operating model across engineering and customer operations.

A leading U.S. retirement and savings services provider supports employers, financial institutions and individual savers through recordkeeping, plan administration and government savings program services. As digital demand grew across its technology organization, the client needed a more scalable way to improve engineering productivity, standardize GenAI adoption and extend AI-led efficiency beyond software delivery into customer-facing operations.

When AI Adoption Could No Longer Remain Team-Led

The client’s engineering organization operated across roughly 40 scrum teams and 320 engineers working on multiple technology stacks. Early copilot-style adoption created pockets of productivity, but the gains remained inconsistent because teams lacked a governed, enterprise-wide model for enablement, usage tracking and repeatable adoption.

Without a standardized GenAI operating model, the organization risked leaving productivity improvements trapped within individual teams. Fragmented tooling, uneven adoption and limited reporting made it harder to accelerate release cycles, manage delivery costs and scale AI-led efficiency across the broader enterprise. The client needed to move from experimentation to an adoption model that could be governed, measured and replicated across engineering and business operations.

A Governed GenAI Model Built for Engineering Scale

Persistent designed a phased path to enterprise GenAI adoption, beginning with an organization-wide GitHub Copilot rollout across engineering teams in 2023–24. The rollout was supported by a dedicated GenAI Hub and Playground, giving teams a structured environment to experiment, learn and apply AI-assisted engineering practices.

Engineering Productivity Center of Excellence

Building on the initial rollout, Persistent established an Engineering Productivity Center of Excellence to bring consistency, governance and reporting to GenAI adoption. The CoE introduced a structured rollout framework and role-based enablement across Admin, Developer and Champion tracks, helping standardize AI-assisted engineering practices across approximately 40 scrum teams and 320 engineers. 

Multi-Stack Enablement Across Engineering Teams

The enablement model was designed for a diverse engineering environment spanning Java/Spring, ASP.NET/C#/SQL, React/Angular and Python/Playwright. This helped the client scale GenAI adoption across teams with different technology contexts rather than limiting adoption to a single stack or use case.

SASVA-Led Acceleration and Adoption Analytics

To scale adoption further, Persistent deployed its proprietary SASVA accelerators, extending GenAI productivity tooling and CI/CD adoption analytics across Azure and AWS environments. This expanded the program to more than 450 associates across three business units and helped convert AI enablement into a more measurable engineering productivity capability.

AI Beyond Engineering

Persistent also extended the governed GenAI approach into customer-facing operations by implementing Agent Assist and Customer Assist bots for the contact center, along with marketing automation capabilities. This helped the client expand AI-led efficiency beyond engineering and bring the same structured adoption model to customer operations.

Enterprise GenAI Adoption with Measured Productivity Gains

With Persistent, the client was able to improve developer productivity by 20% through standardized, governed Copilot and GenAI adoption. The client also saved 40% of manual effort using SASVA accelerators for automated development and testing tasks.

The engagement enabled 450+ associates on GenAI across three business units and scaled adoption to 320+ engineers across roughly 40 scrum teams. By combining role-based enablement, governance, adoption reporting and reusable accelerators, the client created a repeatable model for applying GenAI across engineering at enterprise scale.

The program also extended AI-driven efficiency into customer operations through Agent Assist, Customer Assist and marketing automation. This broadened the impact of the engagement from developer productivity to a more enterprise-wide AI adoption model spanning engineering and revenue-facing functions.

From GenAI Adoption to Repeatable Enterprise Productivity

Persistent helped the client move from isolated AI experimentation to a governed productivity model that could be adopted, measured and scaled across teams. By combining Copilot enablement, an Engineering Productivity Center of Excellence, SASVA accelerators and customer operations automation, Persistent enabled the client to turn GenAI into a repeatable enterprise capability rather than a collection of disconnected pilots.

For the client, the value was not only in adopting GenAI tools, but in creating the governance, enablement and reporting structure needed to scale AI responsibly across engineering and beyond. The engagement demonstrates how Persistent helps enterprises convert early AI momentum into measurable productivity, operational consistency and a foundation for broader AI-led transformation.