AI is transforming business and creating risks most leaders aren't prepared for.
AI Security Essential For Business Leaders
Develop the AI governance, AI risk management, and AI cybersecurity skills that executives and senior leaders responsible for AI strategy genuinely need.
- UK Licensed
- Global Standards
- Expert Instructor
- 5 Day Training
- Overview
Course Overview
Most business leaders understand that AI introduces new risks. Far fewer understand what those risks specifically are, how to assess them against established frameworks, or what an adequate organizational response looks like. Adversarial attacks that manipulate model outputs. Data poisoning that corrupts training data before deployment. Model inversion that reconstructs sensitive information from AI outputs. These aren’t theoretical threats; they’re documented attack vectors that real AI systems have been exploited through, and they require a different security response than conventional cybersecurity approaches address.
This AI Security Essentials for Business Leaders program covers AI security risk identification, AI governance framework design, and enterprise AI security strategy across AI-specific threats, regulatory compliance, and organizational incident response. It sits within our corporate training programs portfolio alongside Foreign Corrupt Practices Act compliance and other tech certifications, bringing the same rigorous, leadership-focused approach to AI risk that we apply across our governance and technology programs.
Every governance, risk, and compliance concept in this program is explicitly AI-qualified; this is not a general information security course repackaged with AI terminology. It covers securing AI systems specifically, because that requires a distinct analytical framework that conventional security strategy doesn’t provide.
- Goals
Course Objectives
By the end of this program, attendees will be able to:
- Identify AI security risks across adversarial attacks, data poisoning, model inversion, and AI supply chain vulnerabilities
- Apply the NIST AI risk management framework and ISO/IEC 27001 to assess and prioritize AI-specific security risks
- Design an AI governance framework that addresses transparency, accountability, and regulatory compliance across AI deployments
- Evaluate AI compliance obligations under GDPR, CCPA, and emerging AI-specific regulatory frameworks
- Develop an AI security strategy covering infrastructure protection, third-party AI vendor management, and AI incident response
- Build an AI security-first organizational culture through leadership commitment, awareness programs, and cross-functional collaboration
- Key Points
Who Should Attend?
- Business Executives Overseeing AI Strategy and Deployment
- IT and Cybersecurity Managers Securing AI Systems
- Legal and Compliance Officers Managing AI Regulatory Exposure
- Risk Officers Assessing Enterprise AI Security Risks
- Entrepreneurs and Decision-Makers Deploying AI Solutions
- Senior Leaders Building Organizational AI Governance Capability
- Key Benefits
Key Benefits of the Course
- An AI security program grounded in real AI threat scenarios and enterprise security strategy
- Practical NIST AI risk management framework and artificial intelligence governance skills applicable from the next AI deployment decision
- Stronger AI cybersecurity capability covering adversarial AI, data privacy, and supply chain risk management
- Clear generative AI security and emerging AI threat methodology for organizations deploying large language models
- A recognized credential from our certificate programs portfolio supporting progression toward senior AI governance and security roles
- Outline
Course Outline
Day 1: AI Security Fundamentals and AI-Specific Threat Landscape
- Covers the AI security threat landscape in depth: adversarial attacks that manipulate model inputs to produce incorrect outputs, data poisoning that corrupts training datasets before deployment, and model inversion attacks that reconstruct sensitive information from AI system responses
- Introduces the distinction between conventional cybersecurity and AI security, why securing AI systems requires a different analytical framework, and why general information security strategy doesn't fully address the attack surfaces that AI deployment creates
- Real AI security breach examples show how organizations that understood cybersecurity but not AI security specifically failed to anticipate and prevent attacks that targeted their AI systems rather than their conventional IT infrastructure
Day 2: AI Risk Management and Governance Frameworks
- Covers the NIST AI risk management framework in depth, how the framework's four core functions (Map, Measure, Manage, Govern) apply to AI security risk assessment, and what implementation looks like across different organizational AI deployment contexts
- Introduces artificial intelligence governance framework design transparency requirements, accountability structures, AI decision-making oversight, and the governance policies that align AI security with corporate leadership priorities and board-level risk appetite
- Attendees complete an AI risk assessment exercise for a realistic enterprise AI deployment scenario, developing the risk identification and prioritization discipline that the NIST AI risk management framework requires
Day 3: AI Compliance, Data Privacy, and Securing AI Infrastructure
- Covers AI compliance obligations under GDPR, CCPA, and emerging AI-specific regulatory frameworks; how data protection law applies to AI training data, AI-generated outputs, and the automated decision-making processes that regulators are increasingly scrutinizing
- Introduces AI data privacy protection methodology: data encryption, anonymization techniques, and the access control disciplines that protect sensitive data used in AI systems against both external attack and internal misuse
- Hands-on exercises develop the AI infrastructure security skills that IT and security managers need: authentication requirements, secure coding practices for AI development, and the cloud AI security controls that third-party AI service deployment requires
Day 4: AI Supply Chain Security and Organizational AI Governance
- Covers AI supply chain security: how third-party AI vendors, pre-trained models, and external data sources introduce security risks that organizations often underestimate when deploying AI solutions built on components they don't fully control or understand
- Introduces generative AI security considerations specific to large language model deployment: prompt injection risks, output manipulation, data leakage through model interactions, and the governance controls that responsible generative AI deployment requires
- Attendees develop an AI vendor security assessment framework for a realistic third-party AI deployment scenario, building the supply chain risk management discipline that enterprise AI security strategy requires
Day 5: AI Incident Response, Future Threats, and Leadership Action Planning
- Covers AI incident response planning, how AI-specific security breaches are detected, contained, and investigated differently from conventional cybersecurity incidents, and what business continuity planning looks like for organizations with AI-dependent critical processes
- Introduces emerging artificial intelligence security threats including autonomous AI risks, explainable AI security implications, and the AI-driven cyberattack capabilities that adversaries are developing alongside the defensive AI security tools organizations are deploying to counter them
- Attendees complete a personal AI security leadership action plan covering organizational artificial intelligence governance priorities, security strategy commitments, and the cross-functional collaboration roadmap that building an AI security-first culture requires
- Terms
Training Methodology
This program combines:
- AI security workshops using realistic enterprise AI threat and governance scenarios
- NIST AI risk management framework and compliance exercises with structured peer review
- AI incident response and supply chain security sessions with instructor feedback on strategic approach
- AI security certification preparation aligned to recognized enterprise AI security leadership standards
- Achievements
Certification
Attendees receive a course completion certificate from our Corporate & Industrial Training Center. The program develops practical, leadership-ready AI security capability across threat identification, AI risk management, governance design, regulatory compliance, and AI incident response. In-house training is available for executive teams and organizations building enterprise AI security governance programs. Visit our Training calendar for upcoming dates and contact us now for scheduling options.
- Case Study
Case Study Example
A financial services firm had deployed three AI-powered customer-facing applications without a formal AI governance framework or AI security assessment behind any of them. When a researcher demonstrated that one application was vulnerable to a model inversion attack that could reconstruct customer financial data from model outputs, the organization had no AI incident response protocol, no AI security policy, and no clear ownership of AI security responsibility across IT, compliance, and legal functions. After key executives and IT security staff completed this AI Security Essentials program, the organization established an artificial intelligence governance committee, conducted a formal AI risk assessment across all deployed systems using the NIST AI risk management framework, and introduced AI-specific security controls across its deployment pipeline. Read insights from similar artificial intelligence governance transformation projects in our learning resource library.
- Why Choose
Why Choose This Program?
AI security training that recycles general cybersecurity frameworks without addressing the AI-specific attack vectors, governance requirements, and regulatory obligations that AI deployment creates produces security professionals who are prepared for the wrong threats. This program is built specifically around AI security, the threat landscape, the risk frameworks, and the leadership disciplines that protecting AI systems actually requires. Explore our Foreign Corrupt Practices Act compliance program and other tech certifications across our training portfolio for a complete view of what we offer.
- Connect
Contact Us
Ready to build AI security leadership capability across your executive or security team? Contact us now for upcoming dates and in-house training solutions tailored to your organization.
- FAQs
Fequently Asked Questions
What does the AI Security Essentials for Business Leaders program cover?
Five days across AI security threat identification, NIST AI risk management framework application, artificial intelligence governance design, AI compliance and data privacy, supply chain security, generative AI security, AI incident response, and a personal AI security leadership action plan on Day 5.
How is this different from a general cybersecurity course?
General cybersecurity courses cover information security strategy, network protection, and conventional threat response. This program covers AI security, specifically adversarial attacks, data poisoning, model inversion, AI governance frameworks, and the regulatory compliance obligations that AI deployment creates a distinct discipline that general security training doesn’t address.
Do attendees need a technical background to benefit from this program?
No deep technical background is required. The program is designed for business leaders, executives, and decision-makers who need to understand AI security well enough to make informed governance and investment decisions, not to implement technical security controls themselves.
Does this course cover generative AI security specifically?
Yes. Day 4 covers generative AI security, including prompt injection risks, output manipulation, and data leakage through large language model interactions the AI security considerations that organizations deploying generative AI tools need to understand and govern.
Which organizations benefit most from AI security training?
Financial services, healthcare, and technology organizations with significant AI deployment see the most direct value, though any organization deploying AI systems in customer-facing, regulated, or business-critical applications has a use case for building leadership-level AI security and AI governance capability.
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Course Schedule
Select your preferred date & venue
20 Jan -- 24 Jan
Greece
GBP 4595/Person
7 Apr -- 11 Apr
USA
GBP 4595/Person
30 Jun -- 4 Jul
KSA
GBP 4595/Person
6 Oct -- 10 Oct
Portugal
GBP 4595/Person
20 Jan -- 24 Jan
Greece
GBP 3595/Person
7 Apr -- 11 Apr
USA
GBP 3595/Person
30 Jun -- 4 Jul
KSA
GBP 3595/Person
6 Oct -- 10 Oct
Portugal
GBP 3595/Person
Duration
5 Days