The programme is modular and can be adapted to the organisation’s needs.
Market-ready AI training for leaders, business owners, management teams, administrators, executives and teams: executive AI strategy, board oversight, responsible AI governance, secure deployment, AI agents and business transformation. Participants leave with a clear portfolio of use cases, ROI/risk priorities, operating-model decisions, security guardrails and a practical 90-day action plan.
The programme is suitable for both technical and non-technical participants. Examples and exercises can be adapted to the audience’s level and organisational context.
No advanced technical prerequisite is required for the Executive Briefing or strategic awareness sessions.
This training aims to help leaders, managers, IT teams, cybersecurity teams, risk and compliance professionals, and business teams understand, secure and responsibly deploy AI, Generative AI and agentic workflows.
By the end of the selected programme or option, participants will be able to:
The programme is structured as a modular training portfolio. Each option can be delivered separately or combined into a full learning pathway.
This full programme covers AI fundamentals, cybersecurity essentials, secure AI systems, governance, compliance, security operations and a secure-AI roadmap.
Key topics: AI concepts, types and capabilities; the AI ecosystem; models, tools and platforms; Generative AI and LLM opportunities and risks; impact of AI on business and society.Hands-on workshop: prompt engineering lab to explore LLM capabilities, limits, safety and bias.
Key topics: modern cyber-threat landscape, AI-powered attacks, AI-enabled defence, security principles for AI systems, Zero Trust, identity and access patterns for AI applications. Discussion will include introductions to Open Worldwide Application Security Project’s(OWASP) top 10 vulnerabilities for LLMs and MITRE ATLAS (Adversarial Threat Landscape for Artificial-Intelligence Systems) framework.
Hands-on workshop: threat-scenario analysis to map AI-enabled attack chains, exposed assets, risks and mitigations.
Key topics: data security, privacy and governance for AI; ML pipelines and MLOps environments; adversarial attacks; model vulnerabilities; poisoning; data leakage; bias and model-integrity risks.Hands-on workshop: secure an ML pipeline from data intake to model serving and test it against adversarial inputs.
Content will address security of SaaS platforms and On-prem environments as separate topics of focus:1. SaaS: securing API boundaries, data in transit, prompt and response logging, third party data residency, and trusting the provider's model controls,2. On prem: owning the full stack, including model weights at rest, inference infrastructure, model supply chain, and host and GPU hardening, with a correspondingly different protection approach, governance posture and incident playbook.
Key topics: AI risk-management framework, governance design, EU AI Act, GDPR, NIS2, Cyber Resilience Act, Data Act, ISO/IEC 42001, ethical AI, responsible use, third-party and supply-chain risk.Hands-on workshop: build an AI risk-assessment and compliance checklist for a selected use case.
Key topics: AI for cybersecurity operations, SOC, threat intelligence, security orchestration, automation and response with AI copilots, incident detection and response in AI environments, long-term secure-AI roadmap.Hands-on workshop: incident-response simulation using AI tools to detect, investigate and respond to simulated incidents.
OTHER AVAILABLE OPTIONS:
A compact sprint for teams that need to design, test and improve secure AI solutions quickly.
Day 1: Design and Build Secure AI SolutionsKey topics: from business use case to secure AI solution, secure architecture patterns, tools, frameworks and platforms for trustworthy AI, validation of models, data flows and controls.Hands-on workshop: design a secure AI solution architecture for a selected use case and compliance context.
Day 2: Implement, Test and OptimiseKey topics: implementing and integrating AI applications, security testing and red-teaming for AI, monitoring, logging, observability, continuous improvement and secure scaling.Hands-on workshop: test, monitor and harden the solution; practise secure deployment and incident handling.
Expected outputs: secure-solution architecture, test and monitoring plan, improvement backlog.
A practical training option focused on securing AI agents, prompts, tools, memory, RAG and workflows.
Key modules include:
A high-level session for executives, board members and C-level leaders.
The briefing covers AI and cybersecurity trends, strategic opportunities and risks, regulatory outlook, governance decisions, secure AI adoption choices, risk appetite, use-case prioritisation, ownership, budget, execution model and tailored recommendations.
The training combines theory, practical examples, demonstrations, case studies and hands-on workshops.
Assessment is continuous and practical.
Participants may receive a certificate of attendance after completion of the selected training option.
Depending on the selected option, participants receive a document kit.
9-12H and 13-17H
Monthly
The training can be delivered in person, online or in hybrid format.
This training portfolio helps organisations build a secure AI advantage by accelerating responsible AI adoption, strengthening governance, reducing cyber and operational risks, and improving the practical skills of teams.
Participants leave with concrete and reusable tools, including a secure AI blueprint, secure prompt template, tool permission matrix, risk checklist, incident playbook, release gates and secure-AI roadmap.
The programme is action-oriented: each module connects AI and cybersecurity concepts to practical decisions, applicable controls and outputs that teams can use immediately.