Learners use their own business processes, tools, risks and decisions rather than generic AI examples.
Enterprise course ยท Security, data protection and safe use
Generative AI Security for Enterprise Teams
Help security, IT and business teams understand the real risks created by generative AI and turn them into daily working controls. The course focuses on practical prevention: what can be entered, what must be reviewed, what tools are approved and where AI must never act alone.
The cohort leaves with policies, playbooks, scorecards, checklists or pilot plans matched to the course theme.
Managers can use the outputs for approval, coaching, procurement, governance, automation or operational change.
Who this course is for
Security and IT teams
Teams responsible for preventing data leakage, unsafe automation and tool misuse across the organisation.
Data owners
People who need to classify what can and cannot be used with AI tools.
Operational teams
Business users who need safe, repeatable AI habits without waiting for every task to be reviewed manually.
What learners work on
- Classify business data into safe, restricted and prohibited AI-use categories.
- Review common generative AI risks including prompt injection, overreliance, data leakage and excessive agency.
- Create approved and prohibited AI tool guidance for teams.
- Define human-review rules for AI-generated summaries, recommendations, code and customer-facing content.
- Design a simple reporting path for risky AI behaviour or accidental disclosure.
- Build team-specific AI security playbooks that managers can reinforce.
Course sprint structure
Work through realistic business examples: leaked files, unsafe prompts, false outputs and automation mistakes.
Define what data can be used, which tools are approved and what must stay out of AI systems.
Set review thresholds for decisions, customer communication, code, analysis and regulated work.
Publish practical rules, examples and escalation guidance teams can use immediately.
What the business can use afterwards
The course is designed to finish with working artefacts the organisation can review, approve and reuse. This is the commercial point: the training creates practical business infrastructure.
Reusable business outputs
- Approved AI tool list
- Sensitive data handling rules
- Prompt and output review checklist
- AI incident reporting path
- Team AI security playbook
- Manager reinforcement guide
Actionable business use cases
Control confidential data exposure
Give employees practical rules for what cannot be pasted, uploaded or summarised with AI.
Prevent risky automation
Define when AI can draft, when humans must approve and where autonomous action is prohibited.
Standardise security training
Turn AI security from a one-off warning into role-specific behaviours and manager checks.
Outcome standard: every cohort should leave with something a manager can open, review and use in a live business decision. The course is not just content consumption; it is a structured way to produce adoption assets.
Turn this course into a business sprint
Run it with one department, one leadership group or one cross-functional AI working group. The goal is a usable output pack, not just attendance.