GenAI Security in Practice
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Course Details
Many organizations now use GenAI in writing, research, document review, support, analysis, and workflow automation. The security issue is no longer only whether a tool is approved. The real question is how GenAI is being used inside workflows, what information is passing through it, what systems it touches, and where human review is still required.
1Course Description
This Intermediate-level course focuses on practical GenAI security controls. It moves beyond basic awareness into workflow-level threat thinking, prompt injection, manipulation, data leakage, knowledge-enabled AI risks, agentic workflow controls, monitoring, detection, and response.
The course is intended for learners who need to translate GenAI security concerns into practical controls. It helps learners understand where exposure appears in everyday work, how controls should be designed, and why safer GenAI use depends on user behavior, workflow design, tool configuration, and ongoing refinement.
Learners develop a more systematic approach to GenAI security in practice.
2What This Course Helps You Do
This course helps learners turn GenAI security concerns into usable controls. The bottom-line value is operational risk reduction: safer workflows, stronger data-handling discipline, better response planning, clearer escalation, and more reliable use of AI in contexts where information, customers, records, or decisions may be affected.
For teams, it supports more consistent GenAI use. For managers and control owners, it provides a practical bridge between AI policy, security expectations, and day-to-day work.
3What You Will Learn
By completing this course, learners will be able to:
- Assess GenAI threats at workflow level rather than only at individual tool level
- Understand how prompt injection, manipulation, and instruction override can affect AI-supported work
- Identify data leakage pathways across inputs, uploads, outputs, shared documents, and connected tools
- Recognize security risks in knowledge-enabled AI use cases
- Understand why agentic workflows require stronger controls, monitoring, and handoff discipline
- Design practical controls for safer GenAI-enabled workflows
- Apply role-based safe-use rules in everyday operational settings
- Develop review routines for outputs that may affect customers, decisions, records, or internal processes
- Improve detection and escalation for suspicious or unsafe GenAI behavior
- Create response notes for incidents involving leakage, manipulation, or misuse
- Refine controls as tools, workflows, and user behavior change
- Support more systematic GenAI risk management inside organizations
4Who This Course Is For
This course is for operations teams, IT-adjacent managers, AI policy owners, security stakeholders, governance teams, knowledge-work leaders, and professionals responsible for safer GenAI use in real workflows.
It is suitable for learners who already understand basic AI and security awareness and now need stronger practical control design.
5Why This Course Matters
GenAI security failures often happen through ordinary work patterns: copied documents, weak prompts, poorly reviewed outputs, connected tools, shared knowledge bases, or automated steps that nobody monitors closely enough. These risks increase as organizations move from isolated use to repeated workflows.
This course matters because safer GenAI adoption requires practical controls inside the work itself, not only broad policy statements. Learners need to understand how to reduce exposure where AI is actually being used.
6Module Overview
This course is structured to move learners through the main concepts, risks, decisions, and practical application areas needed for the course topic.
The course includes the following modules:
- Module 1: Threat Thinking for GenAI Workflows
- Module 2: Prompt Injection and Manipulation
- Module 3: Data Leakage Pathways and Sensitive Information Handling
- Module 4: Control Design Patterns for Safe GenAI Usage
- Module 5: Controls for Knowledge-Enabled AI and Agentic Workflows
- Module 6: Detection, Monitoring, and Response
7Practical Outputs You Can Produce
AISDI™ courses are work-product-driven. This means learners are encouraged to turn course ideas into usable outputs such as notes, prompt sets, checklists, decision aids, plans, templates, review routines, and role-specific artifacts. The examples below are indicative only. Learners can use ALMA™ to adapt outputs to their own role, industry, organization, workflow, current priorities, and practical constraints.
Examples of practical outputs from this course may include:
- GenAI workflow risk map
- Prompt-injection warning checklist
- Data leakage pathway review notes
- Safe-use control checklist
- Knowledge-enabled AI risk review questions
- Agentic workflow control notes
- Output review and human-checkpoint routine
- Incident-response prompt set
- Team training outline for safer GenAI use
- Control refinement plan for changing AI workflows
8Learning Components and Format
This course is delivered through AISDI™’s AI-integrated learning environment and is designed for structured, self-paced, practical learning.
The learning experience includes:
- Modular online course content that can be completed on demand
- Structured explanations written for the course level and target audience
- Intermediate practical control guidance for GenAI-enabled work
- ALMA™-guided activities that help learners test, apply, and extend course ideas
- Scenario-based examples and practical reflection prompts where relevant
- Context-aware prompts that help learners connect the course to their own work
- Work-product-driven learning that supports usable outputs, not only course completion
- Knowledge checks and learning activities that reinforce understanding
- A final verification process for validated completion
9How AISDI™ Learning Works
AISDI™ courses are active, AI-interactive learning experiences. Each course combines instructional content, practical examples, visual material, and the Agentic Learning Multi-Dynamic Assistant™ (ALMA™) as part of the course experience.
The aim is practical capability, not passive course completion. Learners get the most value when they work through the course content, use ALMA™ to clarify and extend their understanding, complete the guided activities, and connect course concepts to their own role, workflow, organization, or personal context.
Visuals and graphics support the learning experience, but the main value comes from active engagement with the material and the embedded ALMA™ interaction layer. This helps learners move from awareness toward usable outputs, better judgment, and more confident application.
10ALMA™ in This Course
ALMA™ operates inside the AISDI™ course experience as the learner-facing AI interaction layer. In this course, learners can use ALMA™ to ask questions, clarify difficult concepts, test their understanding, and translate course ideas into their own working context.
The key value is contextualization. Learners can work with ALMA™ to explore how the course applies to their own job role, industry, organization, team, responsibilities, challenges, tools, and current level of AI maturity. Instead of leaving learners to interpret general course content on their own, ALMA™ helps them connect the material to practical decisions, workflows, outputs, and next steps relevant to their circumstances.
In GenAI Security in Practice (In Development), ALMA™ can help learners review planned AI workflows, identify leakage pathways, draft safe-use controls, create role-specific checklists, test escalation logic, and adapt control ideas to the learner’s own tools, team, and organization.
11Course Language and ALMA™ Language Support
The course content is authored in English. Learners can interact with ALMA™ in more than 100 languages for clarification, examples, explanation, and contextual discussion, subject to the capabilities and limitations of AI-generated multilingual interaction. The official course content, completion process, and certificate remain based on the English course version.
12Knowledge Checks and Learning Activities
The course includes structured learning activities, knowledge checks, and applied prompts that help learners test understanding, reinforce key ideas, and connect course content to practical use. These activities support preparation for the final completion verification process.
13Time Commitment
Approximately 8 to 10 Hours of structured, self-paced learning, plus time for ALMA Activities™ and applied work-product development.
14Validated Completion Certificate
Learners who successfully complete the course and final verification process receive a Validated Certificate of Completion showing the course title, completion status, and relevant AISDI™ certificate alignment.
Certificate alignment: AI∇⋮ Professional™
15What This Is Not
This course is not a generic AI-awareness course, a vendor security configuration manual, or a deep engineering course in model security. It is a practical AISDI™ course focused on safer GenAI workflows, operational controls, and usable risk-reduction outputs.
Access Options
This course is included in the Intermediate subscription tier and may also be available through selected course passes, bundles, learning paths, or business access options.
Individual learners can explore subscription access. Teams, businesses, training providers, partners, and organizations can enquire about structured access options, including course passes, custom bundles, learning paths, cohort access, or enterprise deployment.
At a Glance
- Included In:Intermediate Subscription
- Certificate Alignment:∇⋮ Professional™
- Primary Skills Clusters:AI Security Misuse Cybersecurity and Safe Use
- Role / Audience:Manager
- Function / Use Context:Security
- Industry Context:Cross Industry
- Topic / Capability Focus:AI Security
- Duration:8 to 10 Hours
- Status:In Development