AI+ Security Compliance Practitioner™

The AI+ Security Compliance Practitioner™ is an advanced certification that merges the fundamental principles of cybersecurity compliance with the transformative power of artificial intelligence (AI). Building on the CISSP framework, this certification focuses on how AI can enhance compliance processes, improve risk management, and ensure robust security measures in alignment with regulatory standards. This certification validates knowledge of core principles of cyber security compliance, and assesses understanding of how AI can enhance security posture. This certification structure integrates comprehensive cybersecurity compliance principles with advanced AI applications, validating candidate competency in ensuring compliance and enhancing security through AI technologies.

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Level
beginner

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Duration
50 MCQs, 90 minutes

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Format
Self-Paced Online

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Certification
AI CERTs®

Self-Paced Online

USD $ N/A

Instructor-Led Online

At a Glance: Course + Exam Overview

Our training approach is human‑centred and outcomes‑driven. We focus on what learners can apply confidently.

Program Name

AI+ Security Compliance Practitioner™

Prerequisites

Basic cybersecurity knowledge: Understanding of security principles and organizational controls
Compliance process familiarity: Awareness of standards, policies, audits, and risk management
Introductory AI knowledge: Understanding of AI and generative AI concepts
Evidence review experience: Ability to assess processes and security documentation
Communication and analytical skills: Interpret requirements and explain findings clearly

Exam Format

90 minutes

Certification Modules

Module 1: Foundations of AI-Enabled Security Compliance

1.1 Fundamentals of Security Compliance
1.2 Fundamentals of AI for Compliance Professionals
1.3 Applications of AI Across the Compliance Lifecycle
1.4 Case Study: Manual Compliance Process Causing Audit Delays
1.5 Use Case: AI Compliance Assistant for a Growing Organization

Module 2: Using AI to Interpret Security Standards and Requirements

2.1 Understanding Security Frameworks and Standards
2.2 AI-Assisted Requirement Interpretation
2.3 AI-Enabled Control Mapping
2.4 Case Study: Multiple Framework Compliance at a Technology Company
2.5 Use Case: AI-Based Cross-Framework Control Mapping

Module 3: AI-Assisted Security Risk and Compliance Gap Assessment

3.1 Security Risk Assessment Fundamentals
3.2 Using AI for Security Risk Identification
3.3 AI-Driven Compliance Gap Assessment
3.4 Case Study: Compliance Gaps Following a Security Assessment
3.5 Use Case: AI-Assisted Security Risk Register

Module 4: AI for Security Policy and Procedure Management

4.1 Security Governance Documentation
4.2 Using AI to Create and Improve Security Policies
4.3 AI for Policy Compliance Monitoring
4.4 Case Study: Outdated Information Security Policies
4.5 Use Case: AI Policy Review Assistant

Module 5: AI for Control Implementation and Evidence Management

5.1 Security Control Implementation
5.2 AI-Assisted Control Design and Documentation
5.3 AI-Enabled Evidence Management
5.4 Case Study: Incomplete Evidence During a Compliance Audit
5.5 Use Case: AI-Based Compliance Evidence Reviewer

Module 6: AI for Third-Party Security Compliance

6.1 Third-Party Security Risk
6.2 AI-Assisted Vendor Security Assessment
6.3 AI for Continuous Third-Party Monitoring
6.4 Case Study: Critical Cloud Vendor with Security Deficiencies
6.5 Use Case: AI Vendor Security Review Assistant

Module 7: AI for Compliance Monitoring, Incident Management, and Auditing

7.1 AI-Enabled Compliance Monitoring
7.2 AI for Security Incident Compliance
7.3 AI-Assisted Security Auditing
7.4 Case Study: Repeated Control Failures Before an Audit
7.5 Use Case: AI Security Compliance Monitoring Dashboard

Module 8: AI-Powered Security Compliance Program and Capstone

8.1 Establishing an AI-Enabled Compliance Program
8.2 Governance of AI Used for Compliance
8.3 AI Agents for Compliance Automation
8.4 Case Study: Organization-Wide AI Compliance Transformation
8.5 Use Case: AI-Powered Security Compliance Control Tower
8.6 Capstone Hands-on: Build an End-to-End AI-Powered Security Compliance Program

Optional Module: AI Agents Security Compliance

1.1 What Are AI Agents?
1.2 Key Capabilities of AI Agents in Cyber Security Compliance
1.3 Applications and Trends for AI Agents in Security Compliance
1.4 How Does an AI Agent Work?
1.5 Core Characteristics of AI Agents
1.6 Types of AI Agents

Industry Opportunities

Cybersecurity Compliance Analyst

Ensure AI systems comply with cybersecurity regulations, industry standards, and organizational security policies.

GRC Specialist

Manage governance, risk, and compliance programs while supporting secure and responsible AI implementation.

Security Compliance Officer

Develop and enforce security compliance policies to protect AI systems and meet regulatory requirements.

Risk Management Specialist

Identify, assess, and mitigate security and compliance risks associated with AI technologies and enterprise systems.

IT Security Analyst

Monitor security controls, assess vulnerabilities, and support compliance initiatives across IT and AI environments.

Security Auditor

Conduct security audits, evaluate compliance frameworks, and recommend improvements to strengthen organizational security.

AI Security Governance Specialist

Establish governance frameworks that promote secure, ethical, and compliant adoption of AI across the organization.

Compliance Manager

Lead compliance programs, oversee regulatory adherence, and ensure effective implementation of AI security and governance practices.

Frequently Asked Questions

What practical learning opportunities are provided in this certification?

Learners develop practical skills through projects and case studies focused on AI-powered compliance and security solutions.

What skills will learners develop through this certification?

Learners will gain knowledge of cybersecurity compliance, AI-driven risk management, asset security, IAM, security operations, and AI security trends.

What background knowledge is recommended before starting this course?

Learners should have basic knowledge of cybersecurity, networking, programming, and AI/ML fundamentals.

What learning methods are available for this certification?

Learners can choose between instructor-led training or a self-paced learning format based on their preferences.

What assessment method is used for certification completion?

Certification completion requires passing an online proctored exam with 50 questions and a 70% passing score.

Core AI Tools Covered

Checkmarx

Snyk

Nmap

Wireshark

Burp Suite

Nessus

Splunk

IBM QRadar

Palo Alto Cortex XSOAR

Microsoft Sentinel