Building Member Trust Using Responsible AI: How to Get It Right 

Artificial intelligence (AI) is quickly becoming foundational to the future of healthcare. From automating claims reviews to powering proactive care management, AI has the potential to help health plans operate more efficiently, serve members more effectively, and drive better outcomes at scale. But for all this opportunity, AI also introduces a new level of scrutiny—especially in healthcare—where data sensitivity, regulatory risk, and clinical impact are high.

A 2024 McKinsey survey shows 85% of healthcare leaders have started or are thinking about using Generative AI (GenAI), yet concerns around privacy, bias, and lack of transparency remain key barriers to widespread adoption. For health plans, these concerns are real and valid.

As AI becomes more embedded in payer operations, health plans must ensure that innovation is paired with responsibility. That’s why responsible AI isn’t just a buzzword—it’s a business imperative.

Why Responsible AI Matters in Healthcare

Healthcare is unlike any other industry when it comes to the ethical stakes of automation. AI decisions here don’t just affect margins or marketing. They can influence a member’s access to care, a provider’s reimbursement, or the outcome of a care intervention.

The emphasis on responsible AI acknowledges this reality, encouraging payers and other healthcare organizations to build systems that are:

• Safe and secure
• Transparent and explainable
• Fair and unbiased
• Compliant with evolving regulations

In the 2025 HealthEdge® consumer study, 64% of healthcare consumers said they were open to the use of AI in health insurance. But many also expressed concerns about how their data would be used and how decisions would be made on their behalf. That lack of trust presents a serious challenge for adoption—one that can only be addressed through responsible design and deployment.

“The path to AI adoption starts with trust. That’s why every AI strategy in healthcare must begin with ethics, governance, and transparency,” says Rob Duffy, HealthEdge Chief Technology Officer. Read his full perspective here.

And regulators are watching, too. The NIST AI Risk Management Framework and evolving federal guidance from the Centers for Medicare and Medicaid Services (CMS) and the Federal Trade Commission (FTC) highlight the increasing need for auditable, fair, and ethical AI practices.

Strategies for Implementing Responsible AI in Healthcare

1. Prioritize Data Privacy and Security

Protecting sensitive health information is non-negotiable. Health plans must ensure that AI systems are built on secure architectures, with robust encryption, permission-based access compliant with HIPAA and other regulatory standards.

At HealthEdge, we implement strict privacy controls at every stage of AI development and data handling because responsible innovation starts with secure foundations.

2. Mitigate Algorithmic Bias

Biased algorithms can result in inequitable care, inaccurate risk scoring, or unfair coverage decisions. To mitigate this, health plans should:

• Ensure models are trained on diverse and representative datasets
• Conduct continuous testing and validation
• Include diverse stakeholder input across AI development cycles

HealthEdge’s AI teams embed fairness checks and bias detection into our model review process, ensuring every system we build is safe and equitable for users.

3. Ensure Transparency and Explainability

One of the most common concerns from providers and members alike is, “How did the AI reach this decision?” In healthcare, that question needs a clear and credible answer.

Solutions like HealthEdge Source™ use large language models (LLMs) to explain discrepancies in payment integrity in plain language. This helps users understand “the why” behind administrative and clinical decisions, enhancing confidence in the tools and streamlining the appeals process.

4. Collaborate with Stakeholders

AI systems are only as good as the real-world insights they incorporate. HealthEdge engages clinicians, business users, data scientists, and customers early and often to ensure our AI reflects the complexities of healthcare.

We also partner with leading ethical AI innovators like Codoxo and Gynisus, integrating advanced solutions into our platforms to enhance accuracy, reduce fraud, and maintain ethical standards.

5. Commit to Ongoing Monitoring

Responsible AI is not a one-time exercise—it’s a lifecycle commitment. Models must be retrained, monitored, and governed continuously to avoid drift, degradation, or unintended consequences.

The HealthEdge Approach: AI with Integrity

As HealthEdge becomes an AI-native enterprise, we’ve made responsible AI use a cornerstone of our strategy. We believe that innovation must serve people: our customers, our employees, and the members they support.

Our approach includes:

• Adhering to the NIST AI Risk Management Framework
• Embedding explainable AI in platforms like HealthEdge Source and GuidingCare®
• Investing in workforce transformation through internal AI education and upskilling
• Protecting consumer trust while driving real-world results like improved accuracy and reduced administrative burden

“We’re not just building powerful tools. We’re building confidence in how those tools are used,” says Andrew Witkowski, Senior Director of Machine Learning, who leads the HealthEdge Workforce Transformation Lab.

Practical Advice for Health Plan Leaders

Responsible AI isn’t just an ethical priority—it should be considered a competitive advantage. Health plans that embrace trust-first innovation will be better positioned to scale automation, personalize member experiences, and improve outcomes.

Here’s how to get started:

• Conduct an AI ethics audit to identify risks and blind spots
• Educate your teams on transparency, bias, and explainability
• Partner with trusted vendors who put responsibility at the core of their AI strategy

Next Steps: Innovation That Earns Trust

AI will power healthcare’s future, but only if it earns the trust of the people it serves. Responsible AI offers a path forward: one that’s ethical, effective, and sustainable.

At HealthEdge, we’re committed to leading by example. Join us as we build smarter systems and a smarter healthcare ecosystem. Explore our AI strategy and solutions today.