As AI reshapes industries at an unprecedented pace, understanding how Responsible AI practices in enterprise have evolved is crucial. This opening panel explores the recent history of Responsible AI, unpacking key milestones, challenges, and opportunities that have defined its journey. Gain actionable insights to align your organization with the principles of ethical AI development and deployment.

-           Examining pivotal moments shaping the Responsible AI landscape and their implications for today’s enterprises.

-           Understanding how to embed ethical considerations into AI systems while balancing innovation and accountability.

-           Learning strategies to future-proof AI initiatives by addressing transparency, fairness, and stakeholder trust.

Emma Johnson

Executive Director, Head Responsible AI, Data Ethics
Standard Chartered Bank

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John Almasan

Senior Managing Director, Head of AI & Emerging Tech
Teachers Insurance and Annuity Association of America

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The generative AI landscape is advancing rapidly, but with innovation comes new risks and responsibilities. This session explores the evolving threats posed by Generative AI, the challenges of staying ahead in a dynamic environment, and strategies for embedding responsibility into every step of your AI journey.

-           Identifying Generative AI use cases and auditing them, implementing safeguards to mitigate risk.

-           Developing systems to track AI advancements and adapt strategies in a fast-evolving landscape.

-           Embedding responsibility in AI workflows, ensuring ethical practices align with innovation and business goals.

Slot reserved for sponsor partner

As AI models become integral to business operations, ensuring their reliability, fairness, and compliance is essential. This session explores best practices for managing model risks, minimizing failures, and embedding governance to drive responsible AI innovation.

-           Establishing a comprehensive model governance framework to monitor performance, bias, and ethical compliance effectively.

-           Conducting rigorous risk assessments, stress-testing models under diverse scenarios to identify vulnerabilities.

-           Implementing continuous validation protocols to ensure alignment with evolving regulations and organizational goals.

Dhagash Mehta

Head of Applied AI (AI, GenAI, Responsible AI) Research
BlackRock

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Regulation plays a crucial role in shaping responsible AI practices within businesses. This talk explores the importance and updates of many global regulatory frameworks in driving compliance, mitigating risks, and fostering trust in AI applications.

-       Keeping abreast of evolving AI regulations to ensure compliance and avoid legal repercussions.

-       Discussing the changes of the Trump administration; and the current jurisdictional approaches.

-       Establishing internal policies aligned with regulatory guidelines to promote responsible AI practices.

-       Collaborating with regulatory bodies and industry peers to influence responsible AI policies.

Kuljit Bhogal

Director, Corporate Counsel (AI Governance and Privacy)
Walmart Canada

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Michelle Grajales

Director, Responsible AI Program
HCA Healthcare

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Explore the vital synergy between Responsible AI and sustainability, focusing on AI's environmental footprint. Delve into strategies for mitigating carbon emissions, optimizing energy efficiency, and promoting ethical AI practices to build a sustainable future.

-       Implementing energy-efficient systems to minimize AI's carbon footprint and contribute to environmental preservation.

-       Leveraging renewable energy sources to power AI infrastructure and data centers, promoting sustainability in AI operations.

-       Integrating sustainability metrics into AI development processes to measure and mitigate environmental impact, prioritizing green AI practices.

Slot reserved for sponsor partner

Unlike some industries, responsible AI and model risk management isn’t new but generative AI has posed new, wider challenges. This panel will explore how financial institutions are deploying AI responsibly while fostering trust, mitigating risks, and maintaining competitive advantage.

-           Developing transparent AI systems to enhance fairness in credit scoring, fraud detection, and decision-making processes.

-           Aligning AI strategies with evolving financial regulations to avoid compliance pitfalls and reputational risks.

-           Implementing robust monitoring and auditing practices to identify and mitigate biases and systemic risks in real-time.

Aditya Anne

Senior Director, Enterprise AI Governance
Cibc

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John Almasan

Senior Managing Director, Head of AI & Emerging Tech
Teachers Insurance and Annuity Association of America

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As regulatory frameworks evolve, businesses face increasing pressure to ensure third-party AI systems meet ethical and legal standards. This session will delve into the complex dynamics between developers, deployers, and users, exploring strategies for navigating liability, compliance, and accountability in uncertain regulatory environments.

-           Establishing clear contracts and accountability frameworks to address liabilities in third-party AI system deployments.

-           Developing robust evaluation processes to assess vendor compliance with ethical and regulatory requirements.

-           Implementing continuous oversight to align third-party systems with emerging laws and organizational responsibility standards.

Aneta Osmola

Director, Data and AI Risk
Scotiabank

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Implementing AI governance is critical to managing risks, ensuring compliance, and unlocking Responsible AI’s potential. Learn how IHG established an AI governance framework that incorporates risk assessment, security, and enterprise-wide governance to align with evolving regulatory landscapes like the EU AI Act.

·       Establishing foundational governance processes to identify, assess, and manage AI risks across your organization.

·       Integrating third-party risk management and security into a holistic AI governance and compliance strategy.

·       Expanding from technical oversight to enterprise-wide governance with a scalable AI GRC (Governance, Risk, Compliance) framework.

Sterling Jackson

Director, AI & Technology Risk Management and Security Governance
IHG Hotels & Resorts

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Transforming Responsible AI (RAI) principles into actionable governance frameworks is a daunting yet essential challenge for large enterprises. This session shares an in-depth journey of implementing RAI governance, highlighting practical strategies to operationalize accountability, ethics, and compliance at scale.

-           Designing governance frameworks tailored to organizational structures, ensuring clarity in roles and responsibilities.

-           Building cross-functional collaboration to embed RAI principles into workflows, decision-making, and product development.

-           Leveraging scalable tools and metrics to monitor, assess, and continuously improve AI governance practices.

Aditya Anne

Senior Director, Enterprise AI Governance
Cibc

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Slot Reserved for Sponsor Partner, talk details to be announced

Establishing a data ethics framework is critical for responsibly governing how data is utilized, processed, and leveraged to train and deploy AI systems. In this talk, Kellye-Rae will explore strategies for building AI governance structures from scratch, ensuring transparency with partners, and embedding ethical practices across the organization.

• Developing governance processes to responsibly manage data collection, processing, and use in AI systems.
• Conducting thorough due diligence with AI partners, focusing on accountability, transparency, and robust engagement terms.
• Creating internal tools to standardize procurement, legal, and operational processes with ethical data practices.

Kellye-Raé Campbell

Global Head of Privacy, AI & Data Protection Regulations
Digicel Group

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As AI reshapes IT and data functions, risk-averse organizations face a delicate balancing act. This fireside chat between Tammye and Brian explores how institutions can responsibly evolve IT processes, develop talent, and embrace AI as an enabler—while navigating shifting guardrails and uncertain technological landscapes.

-       Building a collaborative, transparent IT culture to manage AI's rapid evolution and inherent risks effectively.

-       Upskilling teams to understand AI tools, fostering responsibility without requiring deep technical expertise.

-       Developing adaptive governance and data processes that keep pace with emerging AI technologies and challenges.

Tammye Garrett-Feeley

Chief Data Officer
UT Southwestern Medical Center

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Brian Evans

Chief Enterprise Architect
UT Southwestern Medical Center

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Ever go to conferences hoping for practical insights that can actually help you do responsible AI better day to day, but come away empty handed after yet another high-level discussion about the EU AI Act? Well this session is for you. It will be interactive, it will be fun, and most of all it will be a chance to get answers to your burning questions about how to survive and thrive as a responsible AI practitioner doing it for real in the fast-changing, complex world of AI.