AI Modernization for Regulated Industries

In regulated industries, modernization is never just a speed play. It is a control challenge. Healthcare organizations, financial institutions and other compliance-heavy enterprises depend on systems that process claims, support payments, manage sensitive data and keep essential services running. These systems are deeply interconnected, often poorly documented and too critical to change carelessly. When compliance, auditability and continuity are non-negotiable, engineering has to work differently.

That is where Publicis Sapient brings a distinct approach. We help enterprises move from fragile legacy environments to modern platforms that ship reliably, integrate cleanly and improve over time. For regulated organizations, that means uncovering buried business logic, making dependencies visible, automating testing and embedding AI inside governed workflows from the start. The result is faster modernization without sacrificing the controls that high-stakes environments require.

Engineering changes when risk is part of every release

In healthcare, financial services and other regulated sectors, the biggest challenge is rarely a lack of ambition. It is a lack of safe visibility into what core systems actually do. Critical business rules may live in COBOL, batch jobs, copybooks, undocumented integrations or institutional memory. Teams know change is necessary, but every release introduces uncertainty when requirements are incomplete, dependencies are unclear and testing depends too heavily on manual effort.

That is why strong enterprise engineering starts with foundations first. Dependencies must be visible. Business rules must be documented. Testing must be automated. AI must be built in from the beginning, not bolted on after the fact. In regulated environments, this foundation is what makes modernization auditable, resilient and fit for production.

Sapient Slingshot makes legacy systems understandable before it makes them faster

Sapient Slingshot is central to this approach. It helps organizations modernize legacy systems by extracting hidden business logic, generating verified specifications, mapping dependencies and automating testing across the software development lifecycle. That matters in regulated industries because modernization is not just a code conversion exercise. It is a documentation, traceability and risk-reduction exercise.

Instead of forcing teams into risky rewrites based on incomplete understanding, Slingshot turns opaque systems into explainable assets. Functional specifications can be generated directly from legacy applications. Flowcharts, field mappings and dependency views help teams validate what matters. Test creation becomes faster and more consistent. Modernization moves ahead with clearer lineage from source logic to target-state design, code and quality validation.

This is how regulated enterprises avoid the false tradeoff between speed and control. They move faster because the system is more understandable, not because governance has been relaxed.

Sapient Bodhi embeds AI into governed workflows

Modernization creates the foundation, but enterprise value comes when AI operates safely inside real workflows. In regulated industries, AI cannot sit beside the business as an isolated pilot. It has to work within defined controls, support accountability and remain observable in production.

Sapient Bodhi helps make that possible. Bodhi embeds agents into governed workflows with role-based controls and monitoring in place, connecting AI to enterprise context, governed data and clear oversight from day one. Rather than introducing AI as a black box, Bodhi helps organizations orchestrate it inside workflows that can be reviewed, managed and improved over time.

For regulated organizations, that distinction matters. AI must support auditability, access control and operational confidence. Role-based permissions help ensure the right people see and act on the right information. Monitoring and observability help teams understand how AI is performing in production. Governance is not an extra layer added after deployment. It is part of the architecture.

Human-in-the-loop delivery keeps speed and control aligned

Publicis Sapient pairs AI acceleration with human validation at the points that matter most. Product owners validate generated specifications. Engineers review designs, code and tests. Business stakeholders confirm that critical logic has been preserved. Governance and compliance teams maintain oversight without slowing every step to a crawl.

This human-in-the-loop model is essential in regulated transformation. It keeps experts in control of high-impact decisions while allowing AI to handle time-intensive work across discovery, specification, testing and workflow execution. The goal is not manual effort for its own sake. The goal is expert judgment where it reduces risk, improves trust and supports production readiness.

Proof in healthcare and banking

The model is already delivering measurable outcomes in highly regulated environments.

In healthcare claims modernization, Publicis Sapient helped a leading U.S. healthcare company modernize decades-old COBOL systems used for claims processing. With Sapient Slingshot, the team transformed legacy COBOL into maintainable Java and React, auto-generated functional specifications and test cases, and enabled cloud-native deployment. Human-in-the-loop validation supported quality and compliance throughout the effort. The result was 3x faster migration, 10,000 screens modernized and a 30% reduction in modernization costs.

In financial services, Publicis Sapient helped a major British retail and commercial bank modernize complex mainframe batch feeds and payments-related systems built on Unisys COBOL. More than 350 files and nearly half a million lines of code were analyzed in eight weeks. Slingshot generated program overviews, flowcharts, detailed field mappings and fan-out diagrams that product owners could validate quickly. The engagement reduced manual code-to-spec effort by 70%, achieved 95% accuracy in generated specifications and increased migration speed by 40% to 50%.

These outcomes show what regulated buyers care about most: faster delivery can coexist with stronger control when modernization is grounded in traceability, verification and expert oversight.

Built for regulated scale

Publicis Sapient’s broader engineering model is designed for enterprises that cannot afford fragile change. We bring more than 30 years of experience shipping change and scaling software, with modernization delivered up to 3x faster across the software development lifecycle. Our approach starts by making systems visible, testable and governable. Then we embed AI where it can create value safely inside production workflows.

For regulated industries, that means:
This is not modernization that asks leaders to choose between agility and governance. It is engineering designed for the environments where both are mandatory.

Move faster without losing control

Regulated enterprises do not need unchecked acceleration. They need controlled acceleration. With Sapient Slingshot, Publicis Sapient helps make hidden systems visible, verified and ready for safe modernization. With Sapient Bodhi, we help embed AI inside governed workflows with the controls and monitoring required for production. With a human-in-the-loop delivery model, we help organizations increase speed while keeping expert oversight intact.

That is how Publicis Sapient helps healthcare, financial services and other regulated industries modernize with confidence: faster delivery, stronger traceability, better auditability and more resilient operations from the start.