Free Practice Questions for EXIN BCS Artificial Intelligence Foundation Certification
- Guide checked for updates:
- 18 Sep 2026
- Question bank created:
- 7 Jul 2026
- Question bank last updated:
- 11 Aug 2026
Study with 316 exam-style practice questions designed to help you prepare for the EXIN BCS Artificial Intelligence Foundation.
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Exam Details
Key information about EXIN BCS Artificial Intelligence Foundation
- Multiple choice
No
No
65%
1 and 2 (Remembering, Understanding)
Knowledge of AI terminology, for instance through the EXIN BCS Artificial Intelligence Essentials exam or a BCS Artificial Intelligence Award exam, is strongly recommended.
Individuals with an interest in exploring the functions and abilities of AI, and how these can be used in an organization. Relevant roles include developers, project managers, product managers, chief information officers, chief finance officers, change practitioners, business consultants, and leaders of people.
Multiple-choice questions
40
60
No
Exam Topics & Skills Assessed
Skills measured (from the official study guide)
1: An introduction to AI and historical development
1.1: Identify the key definitions of key AI terms
1.2: Describe key milestones in the development of AI
1.3: Describe different types of AI
1.4: Explain the impact of AI on society
1.5: Describe sustainability measures to help reduce the environmental impact of AI
2: Ethical and legal considerations
2.1: Describe ethical concerns, including bias and privacy, in AI
2.2: Describe the importance of guiding principles in ethical AI development
2.3: Explain strategies for addressing ethical challenges in AI projects
2.4: Explain the role of regulation in AI
2.5: Explain the process of risk management in AI
3: Enablers of AI
3.1: List common examples of AI
3.2: Describe the role of robotics in AI
3.3: Describe machine learning
3.4: Identify common machine learning concepts
3.5: Describe supervised and unsupervised learning
4: Finding and using data in AI
4.1: Describe key data terms
4.2: Describe the characteristics of data quality and why it is important in AI
4.3: Explain the risks associated with handling data in AI and how to minimize them
4.4: Describe the purpose and use of big data
4.5: Explain data visualization techniques and tools
4.6: Describe key generative AI terms
4.7: Describe the purpose and use of generative AI including large language models (LLMs)
4.8: Describe how data is used to train AI in the machine learning process
5: Using AI in your organization
5.1: Identify opportunities for AI in your organization
5.2: List the contents and structure of a business case
5.3: Identify and categorize stakeholders relevant to an AI project
5.4: Describe project management approaches
5.5: Identify the risks, costs and benefits associated with a proposed solution
5.6: Describe the ongoing governance activities required when implementing AI
6: Future planning and impact – human plus machine
6.1: Describe the roles and career opportunities presented by AI
6.2: Identify AI uses in the real world
6.3: Explain AI’s impact on society, and the future of AI
6.4: Describe consciousness and its impact on ethical AI
Techniques & products