Responsible AI Isn't Optional: New Strategies for Risk Management Success with Rohan Sen

In today's rapidly evolving technological landscape, organizations face a critical challenge: how to harness the transformative power of AI while effectively managing its inherent risks. In The Power of AI in Risk Episode 7, an insightful episode of Risk Management: Brick by Brick, host Jason Reichl sits down with Rohan Sen, Principal in PwC's Data Risk and Privacy Practice, to explore the delicate balance between AI innovation and responsible implementation.

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The Evolution of AI Risk Management

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The conversation begins with a fundamental truth that's reshaping corporate strategy: AI is no longer optional. As Rohan Sen explains, "Saying no to AI is sort of bearing your head in the sand a little bit, just given how inevitable the march of this technology is." This reality demands a new approach to risk management—one that enables innovation while maintaining robust controls.

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The Three Pillars of Responsible AI

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Rohan Sen outlines a comprehensive framework built on three essential pillars:

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1. Unified Risk Taxonomy

Organizations must establish a common language for understanding and evaluating AI risks across all departments. This standardized approach ensures consistent risk assessment while allowing for department-specific weightings based on unique concerns.

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2. Digital Centralization

"If you don't know what your AI footprint is, there's not a whole lot you're gonna be able to do to manage the risk around it," Rohan Sen emphasizes. This means moving beyond spreadsheets to create centralized, digital platforms that track all AI implementations.

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3. Continuous Monitoring

Unlike traditional software, AI systems require ongoing evaluation. "This is not a place where you can build it and let it go," Rohan Sen warns, highlighting the need for persistent testing and adaptation.

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Managing Third-Party AI Risk: A New Frontier

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One of the most compelling discussions centers on third-party AI risk management. Rohan Sen shares a revealing example of a healthcare organization that unknowingly implemented AI-enabled equipment, highlighting the hidden risks in vendor relationships.

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Key Strategies for Third-Party Risk Management:

• Regular vendor reevaluation
• Updated contractual frameworks
• Consistent standards across internal and external AI
• Compensating controls for limited-access scenarios

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The Rise of the Hybrid Risk Manager

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Perhaps one of the most significant insights from the conversation is the evolution of the risk management role itself. Rohan Sen describes the emergence of a new type of professional: the hybrid risk manager who combines technical expertise with traditional risk management skills.

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"The people who are gonna be successful are ones that know both worlds," Rohan Sen explains, suggesting an 80/20 or 70/30 split between technical and risk management knowledge.

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Practical Implementation Steps

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For organizations looking to implement responsible AI practices, Sen recommends:

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1. Start with Digitization

• Create centralized tools for tracking AI implementations
• Establish clear workflows and documentation processes
• Maintain comprehensive AI inventories

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2. Develop Clear Policies

• Distinguish between personal and corporate AI use
• Establish guidelines for data handling
• Create notification protocols for AI implementations

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3. Build Monitoring Systems

• Implement continuous testing protocols
• Develop metrics for AI performance evaluation
• Create feedback loops for system improvement

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Looking Ahead: The Future of AI Risk Management

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The conversation concludes with Rohan Sen's optimistic yet practical vision for the future: "Foster innovation. There's a lot of very cool opportunities that AI affords us that we could only dream about a couple of years ago as risk people."

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Key Takeaways for Risk Leaders:

• Embrace AI as an enabler rather than a threat
• Build flexible frameworks that support innovation
• Maintain consistent risk management standards
• Invest in continuous monitoring and adaptation

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Conclusion: A Balanced Approach

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The key to successful AI implementation lies not in avoiding risk but in managing it effectively. As organizations continue to navigate the AI revolution, the principles of responsible AI provide a crucial framework for balancing innovation with risk management.

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Rohan Sen's parting advice encapsulates this balanced approach: "Foster innovation... manage your risk, and that's gonna get us to a great spot." This perspective offers a practical path forward for organizations seeking to harness AI's potential while maintaining appropriate controls.

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The future of AI in business isn't about choosing between innovation and safety, it's about creating frameworks that enable both. Through responsible AI practices, organizations can build the foundation for sustainable technological advancement while protecting their interests and stakeholders.

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To learn more about how Responsible AI is shaping the future of risk management, tune in to this episode of Brick by Brick.

👉 Spotify: https://spoti.fi/4iXZQVn
👉 Apple Podcasts: https://apple.co/3EXwngi

Podcast Host: Jason Reichl
Executive Producer: Don Halliwell

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