AI can deliver real benefits in complex, highly regulated operational environments , but it also introduces a distinct and evolving class of risk. Assuring AI is fundamentally different from assuring conventional software, and organisations face a fundamental question: how can AI be trusted to operate safely, reliably, and responsibly?
This one‑day course is designed for participants navigating the adoption, oversight, or assurance of AI. It explores the assurance challenges unique to AI and applies a whole‑system view of AI‑modulated systems (technology, data, people, processes, and governance). It also addresses long‑term impacts on human performance, organisational capability, and safety culture. The course combines practical insight, exploration of cross‑sector standards relevant to AI assurance, and interactive discussion based around a fictional example system used throughout the day.
Course details:
Dates: 7th July 2026 / 2nd September 2026
Time: 10.00 – 16.30 (BST)
Delivery: online
Price (per attendee): £900 + VAT
The course will cover:
- AI fundamentals: foundation models (including LLMs) vs bespoke AI, AI/ML basics, data types, and learning approaches
- The reality of AI in practice: where it performs well today, and the limitations organisations must plan around
- Standards and regulation: emerging cross‑sector standards and sector‑specific considerations
- Core assurance challenges: specification, testing limits, plausible error behaviours, cyber security, and what “AI error” means in practice
- Assurance approaches: systems thinking, hazard and task analysis, functional allocation, human‑in‑the‑loop and human‑over‑the‑loop strategies, and structured assurance techniques and methodologies
- Safety culture: how AI can influence trust, challenge, skills, decision‑making, and organisational resilience over time
Register your interest
Register your interest in this course or contact us with any questions, we’ll be in touch with next steps.
Learning outcomes
By the end of this course, you will have a better understanding of:
- Why AI assurance requires different ways of thinking compared to traditional software assurance
- The current state of AI adoption across hight integrity and regulated environments, its opportunities and risks
- The key standards and regulatory landscape shaping AI deployment and oversight
- Practical approaches to mitigating assurance gaps as AI is introduced into systems
- The human oversight, governance, and organisational capabilities required to manage AI safely
- The long-term safety culture and capability implications of adopting AI that organisations need to actively plan for
Who should attend?
If you are working in a highly regulated or safety‑critical environment (such as nuclear, rail, aviation, medical, industrial systems), this course will be of interest to you.
It is particularly relevant for:
- Safety, risk, and assurance professionals
- Engineers and technical leads involved in system design, integration, operations, or maintenance
- Engineering, operational, and programme managers responsible for AI adoption decisions
- Human factors / operational performance professionals supporting oversight and safe operations
- Compliance, governance, and quality stakeholders supporting assurance expectations
Sector‑specific and tailored courses
Upon request, this course can be tailored for organisations seeking a delivery aligned to their regulatory, operational, or organisational context.
We can offer:
- Tailored emphasis aligned to your industry, regulatory framework, or assurance maturity
- Adapted examples and exercises using your operational context and assurance challenges
- Additional depth on topics such as:
- human oversight models and competence requirements
- monitoring/safeguarding approaches and managing
- AI systems change over time safety culture considerations and long‑term organisational capability risks
Instructor
Dr Nick Chozos
Executive Principal Consultant, AI and Human Factors Lead at Adelard, NCC Group
Nick has over 20 years of experience of working in the assurance of complex systems across nuclear, medical devices, finance, and other critical infrastructure sectors. Nick was one of the authors of our recent report on AI assurance that Adelard produced on behalf of the UK Nuclear regulator.
Why Adelard?
Adelard, part of NCC Group, brings over 35 years of experience in systems assurance engineering to help organisations develop dependable, high-integrity systems. We contribute and develop strategic policy, methodology and research results for a range of clients in safety regulated sectors and government, with a particular focus on the risks and assurance of complex sociotechnical systems, including emerging technologies such as AI and machine learning.