How to get started with AI in highly regulated industries

Everybody is talking about AI, and many CEOs are loudly telling their department heads to implement AI, but often, knowing how and where to start is the first challenge to overcome. 

On 24 March, 2026, during All Access: AI Revolution in CX 2026, Mrunal Gangrade (pictured below), VP at JPMorgan Chase & Co, will explain how CX practitioners in highly regulated industries, such as banking, insurance, and fintech, can take those first crucial steps to success. 

As a recognized leader in artificial intelligence, machine learning, and cybersecurity – as well as an award-winning technologist – Gangrade is known for her clear, practical, and ethical perspective on the future of AI. She holds deep expertise in responsible and explainable AI, and builds intelligent systems that enhance digital trust, strengthen identity and access management, and improve decision-making in high-stakes financial and healthcare environments.

Ahead of her session, Operationalizing AI in CX: Practical steps, risks and guardrails, CX Network caught up with Gangrade to find out more about the session and talk about governance, regulation, and improving CX at scale using AI

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CX Network: Your session looks AI operationalization, governance, and practical considerations for fintech and regulated industries. What are some of the key points you will cover?

Mrunal Gangrade: In this session, I will talk about what it actually takes to put AI into production in fintech and other highly regulated industries, moving beyond theory to focus on real world execution.

I will cover how teams can take AI from pilot projects to enterprise scale systems, including model lifecycle management, monitoring, and handling model drift in a way that holds up to audits and regulatory scrutiny. I will also discuss practical AI governance, including explainability, model risk management, documentation, and validation, without slowing innovation.

A key part of the session will focus on trust, including how to build AI systems that are transparent, fair, and secure, with appropriate human oversight. I will share lessons learned from real fintech use cases such as fraud detection, identity and access management, and risk analytics, highlighting what worked, what did not, and why. 

Overall, the goal of this session is to provide clear and practical takeaways on how to build AI systems that are powerful, responsible, compliant, and ready for real world deployment.

CX Network: Our 2025 research into the Global State of CX found that 48 percent of organizations lack a company-wide approach to generative AI best practices and governance. Why is governance important and how can those 48 percent get started?

Mrunal Gangrade: In fintech, governance is essential because generative AI can directly impact financial decisions, customer trust, and regulatory compliance. Without clear governance, firms risk model bias, data privacy violations, unexplainable outcomes, and regulatory exposure, especially in areas like fraud detection, credit, and customer interactions.

For the 48 percent still getting started, the focus should be on defining clear ownership and accountability for AI across the organization, and aligning AI usage with existing risk, legal, and compliance frameworks. 

Establish baseline controls for data access, explainability, and human oversight, starting with the highest risk use cases. Governance can then evolve incrementally, enabling responsible innovation while maintaining trust and regulatory readiness.

CX Network: What is your take on how AI regulation is keeping up with innovation, particularly in regulated industries, such as finance and healthcare?

Mrunal Gangrade: AI regulation is struggling to keep pace with the speed of innovation, particularly in regulated industries like finance and healthcare where the stakes are high. Regulators are taking a principles-based approach, emphasizing transparency, accountability, data protection, and human oversight rather than prescribing specific technologies, which helps avoid stifling innovation.

As a result, organizations are often operating ahead of formal regulation. Those that proactively embed strong governance, explainability, and risk management into their AI systems are better positioned to adapt to evolving rules, manage risk, and maintain trust with regulators, customers, and patients.

CX Network: What’s the most rewarding or exciting aspect of working in CX right now?

Mrunal Gangrade: The most exciting aspect of working in CX right now is the ability to meaningfully improve experiences at scale using AI, while still keeping the human element at the center. We can move beyond reactive support to more personalized, proactive, and intelligent interactions that genuinely solve customer problems.

What makes it especially rewarding is doing this responsibly. When AI is designed with transparency, trust, and empathy in mind, it not only improves efficiency but also builds stronger, longer lasting relationships with customers.

CX Network: What do you believe to be the most important thing happening in CX in 2026?

Mrunal Gangrade: In 2026, the biggest change in CX will be the widespread use of generative AI throughout the entire customer experience. AI will move beyond simple chatbots and experiments to provide more personalized, seamless, and context-aware interactions across all channels. Companies that succeed will be the ones that balance innovation with strong governance, making sure AI is not only useful but also trustworthy, clear, and aligned with customer expectations.

This change is helping brands better understand and engage with customers in real time, offering more personalized experiences, smarter automation, and deeper insights, while raising the bar for what customers expect from digital interactions.

Mrunal Gangrade’s session takes place at 12:00 ET on 24th March and will include an audience Q&A, giving delegates the chance to put their own questions direct to Mrunal. Register to attend, here.