2. What skills will I gain from AI security and governance training?

You will develop skills in AI risk assessment, data protection, threat identification, governance policy development, vendor evaluation, monitoring, and incident response. You will also learn how to establish organizational controls for responsible AI use.

3. How can AI security and governance skills support business operations?

These skills can help professionals identify security and governance gaps before AI systems create significant business exposure. They can also support stronger policies, clearer responsibilities, better vendor oversight, and more consistent risk management.

4. What AI security threats are covered in the course?

The course covers prompt injection, data poisoning, model manipulation, AI supply chain risks, unauthorized data access, and other AI-related attack vectors. It also introduces security controls and monitoring approaches for reducing these risks.

5. What practical activities are included in the course?

Learners work through business-focused activities such as conducting an AI risk assessment, evaluating an AI vendor, creating a business AI policy, developing an AI security framework, and designing an incident response plan.

AI Security and Governance for Businesses

Category Cybersecurity

Level Experts

Students 17 Already Enrolled

Review

(4.7)

AI security and governance helps businesses manage the risks, responsibilities, and safeguards associated with artificial intelligence. This course introduces structured approaches for protecting AI systems, data, users, and business operations while establishing clear governance practices across modern business environments.

Learners explore AI risk management, data security, attack vectors, security controls, governance policies, compliance considerations, and responsible AI use. The course also examines vendor risks, human oversight, monitoring, incident management, and documentation requirements that support stronger organizational controls.

Through guided business-focused projects, participants learn to conduct AI risk assessments, evaluate AI vendors, develop security frameworks, create acceptable-use policies, and plan incident response. These skills can help organizations adopt AI more confidently while reducing exposure to security, privacy, compliance, and operational risks.

AI security risks, attack vectors, and security controls
Business AI risk assessment and risk registers
Data protection, access controls, and secure AI data handling
AI governance policies, roles, oversight, and documentation
Compliance, privacy, copyright, bias, and responsible AI
AI monitoring, incident management, and vendor evaluation

No formal qualifications are required to enrol. Basic familiarity with business operations, digital tools, or artificial intelligence can be helpful, but the course is designed to introduce key security and governance concepts progressively.

This course is suitable for business leaders, managers, IT professionals, security teams, compliance professionals, risk managers, and employees involved in AI adoption. It is also useful for organizations developing internal AI policies, security controls, or governance frameworks.

1.1 Understanding AI Security
1.2 Understanding AI Governance
1.3 Business AI Risks and Opportunities
1.4 AI Systems and Attack Surfaces
1.5 Responsible AI Principles
1.6 Building an AI Security Mindset

2.1 Identifying Business AI Risks
2.2 Assessing AI System Risks
2.3 Creating AI Risk Registers
2.4 Evaluating Third-Party AI Tools
2.5 Managing AI Risk Controls
2.6 Monitoring Emerging AI Risks

3.1 Understanding AI Data Security
3.2 Protecting Customer and Employee Data
3.3 Managing Confidential Business Information
3.4 Data Access and Permissions
3.5 Secure AI Data Handling
3.6 Data Retention and Deletion

4.1 Understanding AI Attack Vectors
4.2 Prompt Injection Attacks
4.3 Data Poisoning Risks
4.4 Model Manipulation Threats
4.5 AI Supply Chain Risks
4.6 Implementing AI Security Controls

5.1 Developing AI Governance Policies
5.2 Establishing Acceptable AI Use
5.3 Defining AI Roles and Responsibilities
5.4 Creating AI Review Processes
5.5 Managing AI Documentation
5.6 Establishing Human Oversight

6.1 Understanding AI Regulatory Requirements
6.2 Managing Privacy Obligations
6.3 Copyright and Intellectual Property
6.4 AI Transparency and Accountability
6.5 Managing Bias and Fairness
6.6 Maintaining Compliance Records

7.1 Monitoring AI System Activity
7.2 Detecting AI Security Incidents
7.3 Managing AI-Related Breaches
7.4 Investigating AI System Failures
7.5 Conducting AI Security Reviews
7.6 Improving AI Security Controls

8.1 Conducting an AI Risk Assessment
8.2 Developing a Business AI Policy
8.3 Creating an AI Security Framework
8.4 Evaluating an AI Vendor
8.5 Designing an AI Incident Response Plan
8.6 Building an AI Governance Roadmap

The course is suitable for professionals involved in business, technology, cybersecurity, compliance, risk management, or AI adoption. No advanced technical background is required.

AI Security and Governance for Businesses

About AI Security and Governance for Businesses

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