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AI Cybersecurity: Protect Data, Agents and Operations
New
9 students

AI Cybersecurity: Protect Data, Agents and Operations

Manage prompt injection, data leakage, identity risk, malicious agents, vendors, incidents, and accountability
Created byDr. Law Payne
Last updated 10/2026
English

What you'll learn

  • Identify business risks from prompt injection, data leakage, model abuse, and AI agents.
  • Design identity, access, least-privilege, and human approval controls for AI workflows.
  • Evaluate AI vendors and plan monitoring, incident response, and escalation.
  • Build an AI security management system with ownership, controls, and measurable priorities.

Explore related topics

Course content

2 sections • 12 lectures • 1h 48m total length

  • The AI Threat Landscape for Leaders10:23

    This lecture explains attack surface, business impact, threat actors, asset inventory, risk ownership. Students apply the ideas to a realistic business decision, examine common failure modes, and complete a practical exercise they can use immediately.

  • Prompt Injection Data Leakage and Model Abuse10:34

    This lecture explains direct injection, indirect injection, sensitive disclosure, unsafe output, content provenance. Students apply the ideas to a realistic business decision, examine common failure modes, and complete a practical exercise they can use immediately.

  • Identity Access and Agent Security10:30

    This lecture explains nonhuman identities, least privilege, tool permissions, secrets management, segmentation. Students apply the ideas to a realistic business decision, examine common failure modes, and complete a practical exercise they can use immediately.

  • Vendor Risk Monitoring and Incident Response10:20

    This lecture explains vendor evidence, logging, detection signals, incident playbook, executive communication. Students apply the ideas to a realistic business decision, examine common failure modes, and complete a practical exercise they can use immediately.

  • Build the AI Security Management System10:24

    This lecture explains control framework, training, testing cadence, board reporting, ninety-day roadmap. Students apply the ideas to a realistic business decision, examine common failure modes, and complete a practical exercise they can use immediately.

  • Map Data Trust Boundaries and Consequential Actions6:57

    Map trusted instructions, untrusted customer content and consequential tool actions. Examine why an embedded request in a support ticket cannot authorize a customer export, and check actions as well as the final response. Apply the trust-boundary worksheet.

Requirements

  • No coding experience is required.
  • A willingness to apply the frameworks to a real or realistic business situation.
  • Access to common productivity software is helpful but not required.

Description

This course contains the use of artificial intelligence.





AI Cybersecurity: Protect Data, Agents and Operations gives professionals a structured system to recognize material AI threats and build a practical control system that protects data, operations, customers, and reputation.





The course is designed for executives, managers, business owners, consultants, compliance leaders, risk professionals, and technology decision makers. It moves beyond disconnected tips and tool demonstrations. Students learn how to define the business decision, organize evidence, design a practical workflow, evaluate quality, preserve human accountability, and connect activity to measurable results.





The continuing case follows a growing company that adopted copilots and AI agents faster than its access controls, vendor reviews, employee training, and incident procedures evolved. Every lecture includes a management framework, application guidance, quality controls, and an assignment learners can use in an organization, client engagement, career, or business.





Dr. Law Payne combines doctoral-level leadership education with substantial entrepreneurial, marketing, and teaching experience. He holds a Doctor of Business Administration specializing in Organizational Leadership and Development, a master’s degree in Educational Psychology, a master’s degree in Business, and a bachelor’s degree in Business Administration and Marketing. His professional experience includes nine-figure entrepreneurship, published work reaching more than one million copies, and growth leadership involving more than one billion dollars in managed sales.

Who this course is for:

  • Executives, managers, business owners, consultants, compliance leaders, risk professionals, and technology decision makers.
  • Professionals who want business value and responsible implementation rather than surface-level hype.
  • Professionals who want a structured, evidence-based approach instead of disconnected tips or tool demonstrations.
  • Leaders and learners who want to preserve human accountability while using artificial intelligence.

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