Enterprise AI for regulated industries

Move from pilot to production without losing control

In regulated industries, the challenge is rarely whether AI can produce an impressive demo. The challenge is whether it can operate inside real controls, against real data, across real workflows and under real scrutiny.

For leaders in financial services, healthcare and the public sector, production AI has to do more than generate outputs. It has to respect policy, preserve traceability, support human oversight and stand up to audit. It has to work across fragmented systems, aging technology and organizational boundaries without creating new risk.

That is where many AI programs stall. The model may work, but the enterprise is not yet ready to put it to work at scale.

Publicis Sapient helps regulated organizations close that gap. With Sapient Bodhi, Sapient Slingshot and Sapient Sustain, we help enterprises move from isolated pilots to governed execution: orchestrating agents under central control, modernizing legacy systems without losing critical business logic and keeping operations resilient after deployment.

Why regulated AI programs get stuck

Regulated enterprises face a different production threshold than less constrained organizations. They cannot separate innovation from accountability.

Common blockers include:
These issues are especially acute in regulated industries because AI is not being deployed into a greenfield environment. It is being introduced into complex enterprises shaped by decades of systems, rules and operating practices.

Governed agent orchestration with Sapient Bodhi

Sapient Bodhi is built for the point where AI stops being a pilot and starts becoming part of the operating model.

Bodhi enables organizations to build, deploy and orchestrate enterprise-ready agents across systems, data and workflows with centralized governance. Rather than treating AI as a collection of disconnected tools, it provides a unified orchestration layer grounded in business context.

That matters in regulated environments because safe scale depends on more than model performance. It depends on structure.

With Bodhi, organizations can:
This is how AI moves from isolated use cases to repeatable execution.

The proof is already visible in regulated content environments. Publicis Sapient helped a global pharmaceutical company streamline content creation while maintaining regulatory compliance and improving speed and consistency across channels. In one healthcare marketing deployment, AI agents trained on brand, regulatory and medical context reduced content creation time by 90 percent while preserving governance controls across more than 30 markets. In another pharma content transformation, teams achieved 75 percent faster content production and up to 45 percent cost reduction.

The lesson is broader than content. In regulated industries, production AI succeeds when orchestration, context and control are designed together.

Modernize the foundation with Sapient Slingshot

In many regulated enterprises, AI readiness is constrained by legacy technology long before a model reaches production.

Core business rules often remain buried in undocumented code, mainframes and aging applications that were never designed for APIs, real-time data or AI-driven workflows. That creates a serious risk: organizations may want to automate or augment a process, but the logic that governs that process is difficult to see, validate or safely change.

Sapient Slingshot addresses that problem by recovering and modernizing the foundation beneath enterprise AI.

Slingshot reads existing code, extracts buried business logic, maps dependencies and turns what was previously opaque into verified, testable artifacts. It helps enterprises modernize and build software while preserving the rules that matter most.

For regulated organizations, that means greater confidence, less operational risk and stronger traceability during modernization.

Publicis Sapient has already demonstrated that value in complex banking and healthcare environments. A global retail and commercial bank used Slingshot to turn nearly three million lines of legacy COBOL into audit-ready specifications in eight weeks, reducing manual code-to-spec effort by 70 to 85 percent and achieving 95 percent specification accuracy. In healthcare, a major organization used Slingshot to modernize critical legacy systems, achieving 3x faster migration of legacy applications and cutting modernization costs by more than 50 percent. In another health claims modernization effort, Publicis Sapient modernized more than 10,000 legacy screens with human-in-the-loop validation to support quality, compliance and risk reduction.

For financial services, healthcare and the public sector, this is not just a technology upgrade. It is what makes governed AI execution possible. If critical policies, decision paths and service logic remain trapped in legacy systems, AI will struggle to scale safely.

Keep AI operations resilient with Sapient Sustain

Getting AI into production is only part of the challenge. In regulated environments, leaders also need confidence that the surrounding operations will remain stable, observable and cost-efficient as complexity grows.

Sapient Sustain helps organizations shift from reactive support to resilient, context-aware operations. It works across existing environments to anticipate issues, automate resolution and improve operational performance without forcing a disruptive rip-and-replace approach.

This matters for regulated enterprises because production AI increases both dependency and scrutiny. When workflows span agents, applications, infrastructure and human approvals, operational fragility becomes a business risk.

With Sustain, organizations can:
In practice, this has delivered measurable outcomes. Nissan used Sapient Sustain to add AI-powered monitoring, self-healing automation and real-time visibility without disrupting its existing technology stack, achieving 62 percent same-day issue resolution, 99.9 percent platform uptime and a 40 percent reduction in operational costs.

For public sector agencies and other highly scrutinized organizations, resilient operations are not a back-end concern. They are part of maintaining service continuity, public trust and execution discipline.

A practical path for regulated industries

Production AI in regulated industries requires more than governance language. It requires a governed operating model.

That model starts by identifying where AI can operate safely and where human oversight must remain in place. It requires governed data architectures with lineage and access controls built in. It requires modernization that makes buried business logic visible and testable. And it requires operational resilience so new AI-enabled workflows do not make already complex environments harder to run.

This is the role Publicis Sapient plays.

With more than 30 years of enterprise transformation experience, Publicis Sapient combines industry expertise with platforms built for enterprise context. Sapient Bodhi governs and orchestrates agents across real workflows. Sapient Slingshot modernizes legacy systems with full traceability. Sapient Sustain keeps the environment stable, resilient and improving after launch.

For leaders in financial services, healthcare and the public sector, the message is simple: moving from pilot to production does not require giving up control. It requires building control into how AI is designed, deployed and run.

That is how regulated enterprises turn AI from an experiment into measurable execution.