AI · LEADERSHIP
Executive AI Security Awareness Course
Understand how AI systems connect to company data, business applications and decision-making. Evaluate the benefits, security risks and regulatory exposure before approving AI use across customer service, sales, finance, HR and procurement.
English lessons and narration are available. Course-content translations are not yet available. Complete the lessons, practical decisions and assessments to earn a named course-completion certificate.
Explore the course topics ↓
After this course, learners will…
What learners can do
- Explain where company information goes and what an AI system can retrieve, disclose or change.
- Identify material AI risks and the EU or US legal questions that require review before deployment.
- Approve proportionate controls, challenge unsupported assurances and direct an evidence-based response.
Benefits for your company
- Connect AI investment to measurable business value, defined authority and accountable ownership.
- Reduce exposure from sensitive data, customer promises, people decisions, fraud and excessive access.
- Keep auditable approval, incident, continuity and supplier-exit decisions as AI use expands.
The risks executives need to recognise
- Confidential or personal information exposed through prompts, connectors and saved conversations.
- Confident errors, fabricated references and unauthorised customer commitments.
- Malicious instructions embedded in documents or messages the assistant reads.
- Agents acting beyond approval, repeating transactions or retaining excessive access.
- AI-assisted impersonation, payment fraud and unsafe employee shortcuts.
- Supplier dependence, insecure extensions, unapproved fallback AI services and service failure.
Where AI changes business risk
- Sales and customer service: CRM access, quotes, support replies and contractual promises.
- Finance and procurement: supplier checks, payment instructions, contracts and independent approvals.
- HR: interview preparation, applicant ranking, staff information and meaningful review.
- Management and collaboration: meeting records, shared assistants, board papers and evidence.
- IT and operations: permissions, integrations, private AI, change control and continuity.
EU and US regulation: assess the actual use
Learn which questions the business must resolve before a deployment or material change, and what evidence to request from legal, privacy, HR and security owners.
- EU AI Act: provider and deployer roles, prohibited and high-risk uses, AI literacy and transparency.
- GDPR: purpose, lawful basis, minimisation, retention, transfers and consequential automated decisions.
- US exposure: FTC consumer-protection rules, employment discrimination and privacy; NYC hiring, California and Colorado examples.
- Separate binding duties and commencement dates from proposed policy, voluntary NIST guidance and internal rules.
Legal coverage reviewed on 13 November 2026; applicability depends on the intended use. Course completion does not establish compliance or authorise every AI deployment.
INSIDE THE COURSE
AI systems, business exposure and the decisions leaders must own.
8 chapters · 24 lessons3 hExercises take additional time.
24 case-led lessons in eight chapters, with business records, interactive diagrams and decisions with explained feedback. Follow one company from pilot approval through an incident and recovery. No paid AI account is required.
01AI capability, business value and accountability
0.3 h
- Distinguish models, applications, assistants and actions
- Measure value after checking and operating costs
- Define tasks, sources and acceptance criteria
02AI systems, deployment choices and data flows
0.3 h
- Compare personal chat, business workspaces, APIs and self-hosting
- Evaluate OpenAI and Claude data-handling arrangements
- Assess DeepSeek and Kimi by service, operator and terms
03Confidential data, unreliable answers and connected systems
0.3 h
- Control sensitive documents, recordings and retained copies
- Detect unsupported claims, invented references and false promises
- Restrict drive, email, CRM and service-desk connections
04Agent authority, shadow AI and executive impersonation
0.3 h
- Constrain actions, approvals, retries and stop controls
- Give staff usable rules and a reporting route
- Protect payment changes against voice and identity deception
05Supplier, infrastructure and operational risk
0.4 h
- Compare hosted and on-premises costs and responsibilities
- Test access, external fallback AI services, extensions and recovery
- Review contracts, licences, retention and a workable exit
06AI in customer, sales and workforce decisions
0.4 h
- Reassess the pilot when models, permissions or uses change
- Protect customer commitments and rights in reused content
- Distinguish HR assistance from consequential applicant ranking
07EU and US legal exposure, incidents and resilience
0.6 h
- Apply EU AI Act, GDPR and US federal/state applicability checks
- Contain an AI incident and assign reporting decisions
- Maintain service, reconcile work and verify recovery
08Board oversight and defensible adoption decisions
0.4 h
- Coordinate restricted workstreams around one evidence record
- Challenge savings claims and expansion proposals
- Lead the pilot, incident and recovery capstone
AI tools and working environments
Compare OpenAI, Anthropic/Claude, DeepSeek, Kimi and on-premises options by capability, operator, data flows, contract and operating responsibility. Understand the model, application, retrieval connection and agent as different parts of the same business system.
AI
Practical AI use, with human judgement.
This course includes role-specific ways to use approved AI assistance, relevant AI threats and failure cases, and checks for evidence, data handling and human approval. Optional prompts use fictional information; an AI account is not required.
AI examples are practical learning activities. They do not add statutory training requirements or replace your organisation’s policies, qualified advice or accountable decisions.