The U.S. government is at the forefront of shaping policies to address Responsible AI's challenges and opportunities. In this session, a regulatory representative will outline current initiatives, upcoming frameworks, and expectations for businesses in adopting AI responsibly.

-           Understanding evolving U.S. regulatory frameworks shaping AI governance, accountability, and compliance in enterprise settings.

-           Exploring public-private collaboration opportunities to align innovation with ethical and legal standards.

-           Learning actionable strategies to future-proof AI systems against emerging regulatory and societal requirements.

Merve Hickok

President & Policy Director
Center for AI & Digital Policy

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Implementing responsible AI governance is vital to balancing compliance with innovation in a rapidly evolving landscape. In this session, Amber and Gary will explore practical strategies for rolling out AI governance frameworks, including navigating global regulations and leveraging AI to enhance governance itself.

-           Applying the NIST AI Risk Management Framework and align with the EU AI Act for compliance.

-           Building a scalable, global AI governance program to address privacy, accountability, and customer concerns effectively.

-           Using AI tools to streamline governance processes, driving efficiency and maintaining an innovative edge.

Gary Brown

Chief Privacy Officer and AI Governance Corporate Lead
Westinghouse

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Amber Lesniak

Global Data Privacy & AI Governance
Westinghouse

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Most of the high-value use cases carry the more significant risk & involve interacting with people. Delve into the critical process of evaluating and testing high-risk AI systems, essential for safety and reliability. This panel explores opinions on taking innovative approaches, including red teaming and various types of monitoring, to ensure reliability.

-       Implementing red teaming techniques to challenge and validate AI systems' responses to unexpected inputs.

-       Continuously monitoring AI systems using both human and software-based methods to detect anomalies.

-       Investing in a multidisciplinary approach, combining people skills and technology, to ensure responsible AI outcomes.

-       Exploring the use of validation LLMs.

Slot reserved for sponsor partner

Responsible AI isn’t a one-time effort—it requires end-to-end oversight across its entire lifecycle. This session explores how enterprises can manage AI systems responsibly from conception through decommissioning, ensuring ethical, compliant, and effective outcomes at every stage.

-           Establishing governance frameworks for each AI lifecycle phase, ensuring accountability from design to decommissioning.

-           Integrating continuous monitoring and updates to mitigate risks and address evolving regulatory requirements.

-           Promoting transparency and ethical practices by embedding responsibility in every AI development and deployment step.

Nadia Wood

Senior Machine Learning Engineer
Mayo Clinic

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Arvind Thinagarajan

Vice President, Head of Enterprise Data Science & Analytics
Gannett

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Artificial Intelligence (AI) technologies have the potential to transform industries and businesses, but they also pose complex regulatory and ethical challenges. At Vanguard, we are committed to integrating responsibility at every stage of AI adoption and scaling. In this session, we will share our journey of building AI methodologies enabling responsible AI across the enterprise within AI development and implementation. We will discuss how a commitment to fairness, accountability, and transparency drives value while navigating these challenges.

In this session, we will cover the following topics:

1. Building scalable AI frameworks that prioritize fairness, transparency, and ethical decision-making in real-time.

2. Implementing training and inference monitoring to ensure that AI models are aligned with our values and principles.

3. Addressing the challenges of building and scaling responsible AI across the enterprise, including organizational, cultural, and technical considerations.

4. Sharing best practices and lessons learned from our journey, and discussing the future of responsible AI at Vanguard and beyond.

Join us for an insightful and engaging conversation about the importance of navigating the challenges of scaling responsible AI. We look forward to sharing our experiences and learning from the perspectives and insights of others in the field

Jithin Pradeep

Head of AI Research & Enterprise AI 
Vanguard

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Explore how responsible AI technologies can transform your business by fostering ethical innovation, improving operational efficiency, and driving sustainable growth.

-           Leveraging advanced responsible AI tools to boost productivity while ensuring fairness, transparency, and accountability.

-           Implementing scalable, ethical AI solutions designed to integrate seamlessly with your existing infrastructure.

-           Achieving measurable ROI with tailored AI applications that address your organization’s unique challenges responsibly.

Slot Reserved for Sponsor Partner

Identifying and analyzing the right use cases is key to harnessing AI's transformative potential responsibly. This session dives into practical approaches for auditing use cases, assessing potential risks, bias, hallucinations and integrating AI into workflows, achieving efficiencies, and navigating challenges to deliver measurable business value.

-           Evaluating workflows to identify high-impact use cases aligned with organizational goals and ethical considerations.

-           Prioritizing AI initiatives based on feasibility, ROI, and alignment with responsible innovation principles.

-           Establishing feedback loops to refine AI integration and adapt to evolving organizational needs.

Fernanda Del Castillo

Director, Responsible AI
Mastercard

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Aneta Osmola

Director, Data and AI Risk
Scotiabank

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As brands adopt AI to innovate content creation, maintaining authenticity and ethical responsibility becomes paramount. This session explores how businesses can leverage Responsible AI to create impactful, trustworthy content while safeguarding brand values and consumer trust.

-           Integrating Responsible AI practices to balance creativity with ethical standards and brand authenticity.

-           Utilizing transparency measures like watermarking and explainability to build trust in AI-generated content.

-           Fostering innovation through collaborative design processes that align AI outputs with brand identity and consumer values.

Bridget Esposito

Vice President, Head of Creative, Brand
Prudential

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The evolving regulatory environment presents both challenges and opportunities for businesses navigating Responsible AI. In this talk, Zachary will explore how companies can not only keep pace with regulations like the EU AI Act but also transform compliance into a competitive advantage, all while maintaining business viability.

• Building robust governance frameworks to exceed compliance requirements while balancing innovation and risk management.
• Leveraging regulatory demands as differentiators to build trust and foster customer loyalty.
• Fostering cross-functional accountability to embed Responsible AI principles into every aspect of your organization.

Zachary Hanif

Head of AI, Machine Learning and Software Development Platforms
Capital One

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Establishing and embedding a centralized approach to Responsible AI governance is key to driving consistency, accountability, and scalability in AI-driven enterprises. This session explores practical strategies to align governance frameworks with business goals, mitigate risks, and ensure sustainable AI innovation.

-           Designing a centralized governance structure to unify Responsible AI policies, processes, and oversight across departments.

-           Implementing clear accountability and reporting mechanisms to ensure compliance and build trust across stakeholders.

-           Fostering a culture of continuous learning and ethical AI innovation through training, audits, and stakeholder engagement.

Arvind Thinagarajan

Vice President, Head of Enterprise Data Science & Analytics
Gannett

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As AI evolves toward autonomous agents, ensuring these systems are both effective and ethical is paramount. This session explores the challenges and opportunities of developing specialized agents, balancing innovation with privacy and accountability.

• Designing specialized agents that emulate human expertise while adhering to ethical and privacy safeguards.
• Developing abstract model engines to enhance agent autonomy without compromising sensitive data.
• Implementing frameworks to monitor and mitigate risks in agent behavior and domain-specific applications.

Explore the critical implications of AI on employment and strategies for navigating this transformational shift. This panel discusses proactive approaches for businesses to openly discuss, understand & mitigate the impact on jobs while embracing AI innovation responsibly.

-       Investing in reskilling and upskilling programs to empower employees for future roles in AI-driven environments.

-       Fostering open communication channels to address concerns and ensure transparency about AI integration plans.

-       Implementing inclusive AI strategies that prioritize human well-being and job retention alongside technological advancement.

Sami Huovilainen

Managing Director - Head of Next Gen Analytics
Citi

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Eileen Vidrine

Former Chief Data & Artificial Intelligence Officer
US Department of the Air Force, Chief Data & AI Office

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