WGU E026 AI for IT Automation and Security Complete PA Master Study
Guide | Comprehensive Rubric Breakdown, Enterprise Networking, GNS3, AI
Automation & Cybersecurity | 2026 Updated.
Proposed Table of Contents (≈100 pages)
Chapter Topic Approx. Pages
1 Introduction to WGU E026 & PA Overview 6
2 Understanding Every Rubric Requirement 8
3 Enterprise Network Design Fundamentals 8
4 AI in IT Automation 10
5 AI for Cybersecurity 10
6 GNS3 Installation & Lab Setup 8
7 Building the Enterprise Topology 12
8 Router, Switch & Firewall Configuration Concepts 12
9 Testing, Validation & Troubleshooting 8
10 Documentation & Professional Writing 6
11 AI Ethics, Governance & Risk 6
12 Final Submission Checklist & Study Review 8
Chapter 1
Introduction to WGU E026
AI for IT Automation and Security
Purpose of This Guide
This handbook is designed to help students understand the concepts, technologies, and workflow
commonly involved in completing the Performance Assessment (PA) for WGU E026. It explains
the underlying networking, automation, AI, and cybersecurity principles and provides planning
guidance so you can build, document, and justify your own project.
Important: This guide is an instructional resource. You should adapt the ideas and examples to
your own implementation and document your own evidence for the assessment.
,Course Overview
E026 introduces the application of artificial intelligence to enterprise IT operations and security.
Rather than focusing only on theoretical AI, the course emphasizes how AI can assist with
operational tasks such as monitoring, anomaly detection, configuration validation, and incident
response within a networked environment.
Typical learning outcomes include:
Understanding enterprise network architecture.
Explaining AI-assisted automation concepts.
Recognizing common cybersecurity controls.
Designing a secure and scalable network.
Planning validation and testing.
Communicating technical decisions effectively.
Why AI Matters in IT Operations
Modern organizations manage thousands of devices, cloud services, user accounts, and
applications. Manual administration alone often cannot keep pace with the volume of events
generated each day.
AI techniques can assist by:
Identifying unusual activity in large volumes of logs.
Prioritizing alerts based on risk.
Detecting configuration drift.
Supporting predictive maintenance.
Assisting administrators with routine analysis while leaving final decisions to human
operators.
The Role of the Network Engineer
A network engineer working with AI-enabled environments may be responsible for:
Designing resilient network architectures.
Implementing segmentation and secure connectivity.
Planning monitoring and logging.
Integrating automation workflows.
, Verifying that systems operate as intended.
Documenting technical decisions for stakeholders.
Strong documentation is often as important as the technical implementation because it
demonstrates the reasoning behind the design.
Performance Assessment Mindset
Think of the PA as demonstrating a professional engineering process:
1. Identify the problem.
2. Gather requirements.
3. Design a solution.
4. Explain why the design is appropriate.
5. Implement or model the design.
6. Validate the outcome.
7. Reflect on risks and future improvements.
Each stage should be supported by clear explanations and evidence from your own work.
Common Technologies
Depending on your chosen implementation, you may encounter concepts or tools such as:
Enterprise routers and switches.
Firewalls.
Virtual LANs (VLANs).
Routing protocols.
VPN technologies.
Intrusion Detection/Prevention Systems (IDS/IPS).
Security Information and Event Management (SIEM).
GNS3 for network simulation.
AI-assisted analytics platforms.
Understanding what each component does—and why it belongs in the architecture—is more
important than using every possible technology.
, AI Concepts Relevant to E026
Some foundational AI concepts include:
Machine Learning: Models identify patterns from historical data.
Anomaly Detection: Systems flag behavior that differs significantly from established
baselines.
Classification: Events are categorized (for example, benign or suspicious).
Risk Scoring: Alerts are prioritized based on estimated impact and likelihood.
Automation: Routine actions are executed according to predefined rules, with
appropriate human oversight.
Security Principles
Regardless of the specific technology stack, enterprise designs generally reflect several core
principles:
Least privilege.
Defense in depth.
Network segmentation.
Secure remote access.
Encryption in transit.
Centralized logging.
Continuous monitoring.
Regular backups.
Change management.
Documentation Best Practices
Professional technical documentation should:
Use consistent terminology.
Clearly explain design choices.
Separate facts from assumptions.
Include diagrams where appropriate.
Reference authoritative sources.
Organize information with headings, tables, and figures.
Guide | Comprehensive Rubric Breakdown, Enterprise Networking, GNS3, AI
Automation & Cybersecurity | 2026 Updated.
Proposed Table of Contents (≈100 pages)
Chapter Topic Approx. Pages
1 Introduction to WGU E026 & PA Overview 6
2 Understanding Every Rubric Requirement 8
3 Enterprise Network Design Fundamentals 8
4 AI in IT Automation 10
5 AI for Cybersecurity 10
6 GNS3 Installation & Lab Setup 8
7 Building the Enterprise Topology 12
8 Router, Switch & Firewall Configuration Concepts 12
9 Testing, Validation & Troubleshooting 8
10 Documentation & Professional Writing 6
11 AI Ethics, Governance & Risk 6
12 Final Submission Checklist & Study Review 8
Chapter 1
Introduction to WGU E026
AI for IT Automation and Security
Purpose of This Guide
This handbook is designed to help students understand the concepts, technologies, and workflow
commonly involved in completing the Performance Assessment (PA) for WGU E026. It explains
the underlying networking, automation, AI, and cybersecurity principles and provides planning
guidance so you can build, document, and justify your own project.
Important: This guide is an instructional resource. You should adapt the ideas and examples to
your own implementation and document your own evidence for the assessment.
,Course Overview
E026 introduces the application of artificial intelligence to enterprise IT operations and security.
Rather than focusing only on theoretical AI, the course emphasizes how AI can assist with
operational tasks such as monitoring, anomaly detection, configuration validation, and incident
response within a networked environment.
Typical learning outcomes include:
Understanding enterprise network architecture.
Explaining AI-assisted automation concepts.
Recognizing common cybersecurity controls.
Designing a secure and scalable network.
Planning validation and testing.
Communicating technical decisions effectively.
Why AI Matters in IT Operations
Modern organizations manage thousands of devices, cloud services, user accounts, and
applications. Manual administration alone often cannot keep pace with the volume of events
generated each day.
AI techniques can assist by:
Identifying unusual activity in large volumes of logs.
Prioritizing alerts based on risk.
Detecting configuration drift.
Supporting predictive maintenance.
Assisting administrators with routine analysis while leaving final decisions to human
operators.
The Role of the Network Engineer
A network engineer working with AI-enabled environments may be responsible for:
Designing resilient network architectures.
Implementing segmentation and secure connectivity.
Planning monitoring and logging.
Integrating automation workflows.
, Verifying that systems operate as intended.
Documenting technical decisions for stakeholders.
Strong documentation is often as important as the technical implementation because it
demonstrates the reasoning behind the design.
Performance Assessment Mindset
Think of the PA as demonstrating a professional engineering process:
1. Identify the problem.
2. Gather requirements.
3. Design a solution.
4. Explain why the design is appropriate.
5. Implement or model the design.
6. Validate the outcome.
7. Reflect on risks and future improvements.
Each stage should be supported by clear explanations and evidence from your own work.
Common Technologies
Depending on your chosen implementation, you may encounter concepts or tools such as:
Enterprise routers and switches.
Firewalls.
Virtual LANs (VLANs).
Routing protocols.
VPN technologies.
Intrusion Detection/Prevention Systems (IDS/IPS).
Security Information and Event Management (SIEM).
GNS3 for network simulation.
AI-assisted analytics platforms.
Understanding what each component does—and why it belongs in the architecture—is more
important than using every possible technology.
, AI Concepts Relevant to E026
Some foundational AI concepts include:
Machine Learning: Models identify patterns from historical data.
Anomaly Detection: Systems flag behavior that differs significantly from established
baselines.
Classification: Events are categorized (for example, benign or suspicious).
Risk Scoring: Alerts are prioritized based on estimated impact and likelihood.
Automation: Routine actions are executed according to predefined rules, with
appropriate human oversight.
Security Principles
Regardless of the specific technology stack, enterprise designs generally reflect several core
principles:
Least privilege.
Defense in depth.
Network segmentation.
Secure remote access.
Encryption in transit.
Centralized logging.
Continuous monitoring.
Regular backups.
Change management.
Documentation Best Practices
Professional technical documentation should:
Use consistent terminology.
Clearly explain design choices.
Separate facts from assumptions.
Include diagrams where appropriate.
Reference authoritative sources.
Organize information with headings, tables, and figures.
