Becoming an AI-Ready Security Leader: How CISOs Balance Innovation, Risk, and Resilience in the AI Era by Pearson

5h 41mIntermediate2026-07-31

Authors

Pearson

Course details

AI is reshaping both the threat landscape and the tools defenders use to counter it—and security leaders are expected to guide their organizations through that shift. In this course, cybersecurity and AI specialist Avinash Naduvath shows you how to lead AI adoption in cybersecurity: assessing AI-driven threats, hardening defenses with AI, and governing the risks AI introduces across compliance, vendors, and the AI supply chain. Explore how AI reshapes Zero Trust, security operations, and threat hunting, and see how agentic architectures change the SOC. Build an AI-ready workforce using the 10-20-70 model, an AI persona framework, and champion programs. Finally, plan for resilience—budgeting for AI, communicating impact to the C-suite, and pivoting from "no" to "how" as a security leader. Upon completing this course, you'll have a practical playbook for becoming an AI-ready CISO who can protect the business and unlock AI's value.

Concepts

Introduction

Becoming an AI-Ready Security Leader - Introduction

Introduction to Becoming an AI-Ready Security Leader

Module introduction
Learning objectives
Purpose of the course
Key outcomes
Course structure

Framing the AI Cybersecurity Landscape

Module introduction
Learning objectives
AI expands the threat scope
The AI threat landscape
Key takeaways

Why Should Leadership Care

Learning objectives
Why should leadership care
Key takeaways

Strategic Mindset

Learning objectives
An AI leader needs to
Lead AI adoption with cybersecurity
Key takeaways

Why Do Leaders Need to Care

Module introduction
Learning objectives
Evolution of AI consumption
Leadership imperatives
Key takeaways

Weaponizing AI - AI as a Puppet

Learning objectives
Autonomous attacks Ransomware 3.0
Speed and scale with AI
Enhancing existing attacks Deepfakes, the new face of phishing
Key takeaways

Partners in Crime - AI as a Tool

Learning objectives
AI tools
Key takeaways

AI-Driven Defenses - Protecting with AI

Learning objectives
Defense constructs best benefited from AI
Protecting AI with AI
Key takeaways

The AI Threat Landscape

Module introduction
Learning objectives
Framing AI risks from a business perspective
AI threats A deep dive
Key takeaways

A Holistic AI Security Framework

Learning objectives
AI cybersecurity tenets for leadership to consider
Frameworks to consider
Securing AI systems
AI in cybersecurity
An AI governance principle lens
AI lifecycle lens
Key takeaways

The Zero Trust Imperative - A Risk Lens

Learning objectives
The core of Zero Trust and how AI enhances it
AI-driven identity behavioral identity
Autonomous segmentation
AI-driven application and data protection
AI-driven observability, automation, and orchestration
AI influencing governance
Zero Trust imperatives for AI adoption
Key takeaways

The Compliance Imperative - A Governance Lens

Learning objectives
Financial and legal consequences of noncompliance
Compliance is no longer a static audit
Global AI regulatory matrix
Regional and industry spotlights
Extension to existing GRC
Managing shadow AI consumption
AI security posture management
Operational impact of compliance
The CISO's compliance mandate for AI initiatives
Key takeaways

Vendor Supply Chain Risk

Learning objectives
Visualizing the AI vendor dependency chain
Risk-based categorization of vendors
The black box problem and data lineage imperative
Understanding the three dimensions of vendor risk
The recursive risk
Red teaming your vendors
AI BOM Due diligence
Key takeaways

Insertion of AI into Security Operations

Module introduction
Learning objectives
Typical insertion of AI into cybersecurity
AI in security operations
Bounded autonomy
Considerations for AI insertion into cybersecurity
Key takeaways

Agentic Threat Hunting

Learning objectives
AI-driven threat hunting
Key takeaways

Agentic SOC

Learning objectives
Typical SOC architecture
An agentic SOC architecture
Triage acceleration
Correlation
Detection rule optimization
Key takeaways

A Strategic Framework

Module introduction
Learning objectives
The AI readiness gap
The 10-20-70 principles of AI success
A strategic framework for AI leadership
Key takeaways

AI Skills to Invest In

Learning objectives
The AI persona model
AI literacy for the general workforce
AI literacy for role-specific competencies
AI literacy for the agent architect
AI literacy for soft skills
Key takeaways

Workforce Enablement Strategies

Learning objectives
AI workforce enablement loop
The AI Champions program
The AI sandbox
Measuring AI workforce upliftment initiative ROI
Key takeaways

The Future of the Workforce

Learning objectives
The rise of generalists
Pattern matching vs. judgments
Eliminating idle handover bottleneck
Flattening hierarchies
The hybrid workforce
EPOCH - Human capabilities AI cannot replace
Key takeaways

Navigating Geopolitical Impact of AI Systems

Module introduction
Learning objectives
AI resilience
Geographic reality The latency of sovereignty
Sustainability
Key takeaways

Budgeting Considerations

Learning objectives
The AI budget - From expenses to investment
Budgeting for macro-resilience
Budgeting for agility
Key takeaways

The Polymorphic CISO

Learning objectives
Considerations for a multifaceted CISO
The communication pivot
The three pillars of an AI pitch
Outcome-driven metrics dashboards
Measuring transformation agility
Risk quantification in practice
The CISO-CFO-COO alliance
Key takeaways

The AI-Ready CISO

Learning objectives
Enhance operational resilience and service availability
Enhance unified governance and AI identity
Enhance leadership with agility
From no to how
Enhance confidence Lead through uncertainty
Key takeaways

Summary

Becoming an AI-Ready Security Leader - Summary