Join us for AI for Cybersecurity and Privacy Leaders: Strategy, Execution, and Impact, part of the EDUCAUSE Leadership Series. This three-session experience combines synchronous sessions, asynchronous content, and meaningful conversation to support practical learning at the intersection of AI, cybersecurity, and privacy.
Schedule
- Session 1: Monday, March 2, 2026 | 12:00 noon–1:00 p.m. ET
- Session 2: Wednesday, March 4, 2026 | 12:00 noon–2:00 p.m. ET
- Session 3: Monday, March 9, 2026 | 12:00 noon–2:00 p.m. ET
Sessions
Session 1 | AI Essentials
This session introduces cybersecurity and privacy leaders to core artificial intelligence concepts that inform strategic decision-making. Participants will clarify what AI is—systems performing tasks that mimic human intelligence—and distinguish between narrow, general, and generative AI through security-focused examples. The session explores how machine learning and natural language processing drive applications like threat detection, anomaly identification, and phishing prevention. It also examines how generative AI tools such as GANs and Transformers both strengthen defenses and create new risks, including deepfakes and AI-powered social engineering. Real-world examples in fraud detection, compliance monitoring, and loss prevention highlight AI’s dual role as a powerful security asset and potential threat, preparing leaders to make informed, responsible adoption decisions.
Learning Outcomes:
- Distinguish between narrow, general, and generative AI in cybersecurity contexts.
- Identify how AI supports threat detection and compliance monitoring.
- Explain how machine learning and language models are used in security operations.
- Recognize the opportunities and risks of generative AI for security and privacy leaders.
Session 2 | AI Applications and Implementation
This session explores real-world implementations and strategic deployment approaches for cybersecurity leaders. Through case studies from Amazon, JPMorgan Chase, Siemens, and Walmart, participants will see how AI drives operational efficiency, risk management, predictive maintenance, and loss prevention—offering direct parallels to security operations. The session outlines how to build AI capabilities within security teams, identify quick wins, define success metrics, and manage stakeholder expectations. Key considerations include data quality, vendor evaluation, privacy, and balancing custom versus commercial solutions. Participants leave with practical guidance on planning, resourcing, and measuring ROI for AI-enabled security initiatives.
Learning Outcomes:
- Identify how organizations apply AI to enhance security operations and risk management.
- Recognize key success factors for implementing AI within security teams and infrastructure.
- Evaluate data, vendor, and privacy considerations that shape effective AI deployment.
- Outline practical steps for planning, resourcing, and measuring AI initiatives.
Session 3 | AI Governance, Ethics, and Strategic Planning
This session explores the governance, ethics, and regulatory dimensions of AI in cybersecurity and privacy programs. Participants will examine key ethical principles—transparency, accountability, fairness, and privacy—and how bias, data quality, and measurement errors affect threat detection accuracy. The discussion highlights major regulatory frameworks, including the EU AI Act, U.S. Executive Order 14110, and relevant ISO standards, with emphasis on compliance obligations for high-risk AI systems. Participants also learn how to design governance frameworks, apply privacy-by-design principles, and build oversight mechanisms to ensure responsible AI adoption in security contexts.
Learning Outcomes:
- Explain core ethical principles guiding responsible AI in cybersecurity and privacy.
- Identify how bias and data quality issues affect AI-driven security outcomes.
- Recognize key AI governance and regulatory requirements shaping security programs.
- Outline steps to develop governance frameworks and oversight processes for AI use.