Agentic AI in Regulated Industries: Navigating Compliance, Security, and Risk

Agentic AI is rapidly redefining what’s possible in digital business transformation, but nowhere are its opportunities—and challenges—more pronounced than in highly regulated industries. Sectors like healthcare, financial services, and the public sector face unique hurdles: stringent data privacy laws, complex regulatory frameworks, and the imperative for explainable, auditable AI. Yet, these same industries stand to gain the most from agentic AI’s promise of automating complex workflows, reducing operational friction, and delivering better outcomes for customers, patients, and citizens.

What Is Agentic AI—and Why Does It Matter in Regulated Sectors?

Agentic AI refers to autonomous, multi-agent systems that can perceive context, make decisions, and execute multi-step tasks with minimal human intervention. Unlike traditional automation or even generative AI—which typically requires a human to act on its outputs—agentic AI can:

This leap in capability means agentic AI can orchestrate end-to-end business processes, delivering measurable value—if deployed with the right governance.

Unique Challenges in Regulated Industries

1. Data Privacy and Security

Regulated sectors handle sensitive personal and financial data. Agentic AI must comply with laws like HIPAA, GDPR, and sector-specific mandates. This requires:

2. Regulatory Compliance and Explainability

AI-driven decisions must be explainable and auditable. Regulators demand:

3. Integration with Legacy Systems

Many regulated organizations rely on decades-old technology. Agentic AI must bridge these silos, requiring:

4. Human Oversight and Trust

Unchecked autonomy is a risk. Human-in-the-loop frameworks are essential for:

Real-World Use Cases: Agentic AI in Action

Healthcare: Automated Prior Authorization

Prior authorization is a major bottleneck in healthcare, delaying treatment and increasing costs. Agentic AI can:

Impact: Reduces administrative costs by up to 50%, accelerates care delivery, and improves patient and provider satisfaction—all while maintaining compliance and auditability.

Financial Services: Real-Time Risk Assessment

Banks and insurers must assess risk instantly while meeting regulatory requirements. Agentic AI can:

Impact: Increases loan approval efficiency, reduces fraud, and enables 24/7 compliance monitoring—supported by explainable AI and robust audit trails.

Public Sector: Fraud Detection in Benefits Administration

Government agencies face mounting fraud in social security, unemployment, and tax programs. Agentic AI can:

Impact: Reduces improper payments, speeds up benefit approvals, and saves billions in taxpayer funds, while ensuring transparency and regulatory alignment.

Lessons Learned from Early Adopters

  1. Integration First: Agentic AI is only as powerful as the systems it can access. Early adopters prioritize seamless integration across platforms, often modernizing legacy systems as a prerequisite.
  2. Data Readiness: Clean, well-governed data is non-negotiable. Invest in data quality, governance, and real-time access to ensure AI agents make sound decisions.
  3. Human Oversight: Even as AI agents gain autonomy, human-in-the-loop frameworks remain essential for oversight, exception handling, and continuous improvement.
  4. Transparent Governance: Explainability, auditability, and compliance must be built in from day one—not bolted on after deployment.
  5. Change Management: Upskilling the workforce and fostering trust in AI-driven decisions are as important as the technology itself.

Readiness Checklist for Leaders

Before scaling agentic AI in regulated environments, assess your organization’s maturity across these dimensions:

  1. Data Readiness: Is your data clean, well-governed, and accessible across systems?
  2. Systems Integration: Are your legacy systems and APIs modernized for agentic workflows?
  3. Risk Management: Do you have ethical AI frameworks, human-in-the-loop oversight, and continuous monitoring in place?
  4. Workforce Upskilling: Are your teams trained to collaborate with AI, focusing on oversight, quality control, and creative problem-solving?
  5. Portfolio Approach: Are you balancing quick wins from generative AI with targeted investments in agentic AI for transformational value?

Actionable Guidance: How to Get Started

  1. Start with High-Value, Low-Risk Use Cases: Automate repetitive, low-stakes processes (e.g., claims intake, document verification) before scaling to mission-critical workflows.
  2. Invest in Data and Integration: Modernize your data estate and ensure interoperability across systems to unlock the full potential of agentic AI.
  3. Build Trust Through Transparency: Clearly communicate how AI agents make decisions, and maintain human oversight to foster trust among employees, customers, and regulators.
  4. Establish Robust Governance: Implement ethical AI guidelines, audit logging, and continuous monitoring to manage risk and ensure compliance.
  5. Plan for Change Management: Prepare your workforce for new ways of working, emphasizing upskilling and collaboration between humans and AI.

Why Publicis Sapient?

With decades of digital transformation expertise and a proven track record in regulated industries, Publicis Sapient partners with organizations to design, build, and scale agentic AI solutions that are secure, compliant, and tailored to sector-specific needs. Our proprietary platforms, such as Sapient Slingshot, accelerate system integration and workflow automation, while our human-centered approach ensures that technology augments—not replaces—human judgment.

Ready to put agentic AI to work in your regulated industry? Let’s connect.