AI Value Canvas
Guide / References

AI Value Canvas guide

References and Further Reading

Review the sources and further reading that support the public guide.

These sources support the methods, governance questions, and further learning in this guide. They are not a checklist of rules: applicability depends on your jurisdiction, sector, and use case.

Foundation, governance, and regulation

  • [Boston Consulting Group. (2024, October 24). *AI Adoption in 2024: 74% of

Companies Struggle to Achieve and Scale Value*.](https://www.bcg.com/press/24october2024-ai-adoption-in-2024-74-of-companies-struggle-to-achieve-and-scale-value) Press release.

  • [Osterwalder, A., & Pigneur, Y. (2010). *Business Model Generation: A

Handbook for Visionaries, Game Changers, and Challengers*. Wiley.](https://www.wiley.com/en-ie/Business+Model+Generation:+A+Handbook+for+Visionaries,+Game+Changers,+and+Challengers-p-9780470876411) The foundational work behind the Business Model Canvas.

  • [International Organization for Standardization & International

Electrotechnical Commission. (2023). ISO/IEC 42001:2023: Information technology — Artificial intelligence — Management system.](https://www.iso.org/standard/42001) A voluntary international management-system standard for AI.

  • [Tabassi, E. (2023). *Artificial Intelligence Risk Management Framework

(AI RMF 1.0)* (NIST AI 100-1). National Institute of Standards and Technology.](https://doi.org/10.6028/NIST.AI.100-1)

  • [Autio, C., et al. (2024). *Artificial Intelligence Risk Management

Framework: Generative Artificial Intelligence Profile* (NIST AI 600-1). National Institute of Standards and Technology.](https://doi.org/10.6028/NIST.AI.600-1)

  • [European Parliament & Council of the European Union. (2024). *Regulation

(EU) 2024/1689 of 13 June 2024 laying down harmonised rules on artificial intelligence (Artificial Intelligence Act)*. Official Journal of the European Union.](https://eur-lex.europa.eu/eli/reg/2024/1689/oj/eng)

  • [Ministry of Science, Technology and Innovation, Malaysia. (2024). *The

National Guidelines on AI Governance & Ethics (AIGE).*](https://mastic.mosti.gov.my/storage/2024/09/THE-NATIONAL-GUIDELINES-ON-AI-GOVERNANCE-ETHICS.pdf) National guidance, not legislation.

  • [Malaysia. (2010). Personal Data Protection Act 2010 (Act

709).](https://www.pdp.gov.my/ppdpv1/en/akta/pdp-act-2010-en/)

  • [Malaysia. (2024). Personal Data Protection (Amendment) Act 2024 (Act

A1727).](https://www.pdp.gov.my/ppdpv1/wp-content/uploads/2024/11/Act-A1727.pdf) Consult the current consolidated law and appropriate professional advice for a particular deployment.

Design, users, and innovation

  • [Lewrick, M., Link, P., & Leifer, L. (2018). *The Design Thinking

Playbook: Mindful Digital Transformation of Teams, Products, Services, Businesses, and Ecosystems*. Wiley.](https://www.wiley.com/en-us/the-design-thinking-playbook-mindful-digital-transformation-of-teams-products-services-businesses-and-ecosystems-p-9781119467472)

  • [Brown, T. (2009). *Change by Design: How Design Thinking Transforms

Organizations and Inspires Innovation*. HarperBusiness.](https://www.harpercollins.com/products/change-by-design-tim-brown)

  • [Dorst, K. (2015). Frame Innovation: Create New Thinking by Design. MIT

Press.](https://mitpress.mit.edu/9780262328852/frame-innovation/)

  • [Christensen, C. M., Hall, T., Dillon, K., & Duncan, D. S. (2016). *Know

Your Customers’ “Jobs to Be Done”*. Harvard Business Review.](https://hbr.org/2016/09/know-your-customers-jobs-to-be-done)

Responsible AI, data, and operations

  • [IEEE Global Initiative on Ethics of Autonomous and Intelligent Systems.

(2019). Ethically Aligned Design: A Vision for Prioritizing Human Well-being with Autonomous and Intelligent Systems (1st ed.).](https://standards.ieee.org/wp-content/uploads/import/documents/other/ead1e.pdf) Voluntary guidance.

  • [Crawford, K. (2021). *Atlas of AI: Power, Politics, and the Planetary

Costs of Artificial Intelligence*. Yale University Press.](https://yalebooks.yale.edu/book/9780300264630/atlas-of-ai/)

  • [Polyzotis, N., Zinkevich, M., Roy, S., Breck, E., & Whang, S. (2019).

Data validation for machine learning. Proceedings of Machine Learning and Systems, 1, 334–347.](https://proceedings.mlsys.org/paper_files/paper/2019/hash/928f1160e52192e3e0017fb63ab65391-Abstract.html)

  • [Sculley, D., Holt, G., Golovin, D., Davydov, E., Phillips, T., Ebner,

D., Chaudhary, V., Young, M., Crespo, J.-F., & Dennison, D. (2015). Hidden technical debt in machine learning systems. Advances in Neural Information Processing Systems, 28.](https://proceedings.neurips.cc/paper_files/paper/5656-hidden-technical-debt-in-machine-learning-systems)

AI strategy and organizational change

  • [McAfee, A., & Brynjolfsson, E. (2017). *Machine, Platform, Crowd:

Harnessing Our Digital Future*. W. W. Norton & Company.](https://wwnorton.com/books/Machine-Platform-Crowd/)

  • [Davenport, T. H., & Ronanki, R. (2018). Artificial intelligence for the

real world. Harvard Business Review.](https://hbr.org/2018/01/artificial-intelligence-for-the-real-world)

Reader next step

Select the sources that are relevant to the decision, jurisdiction, and stage of your Canvas work. Return to the applicable guide section to record how the source changes an assumption, control, or next test; do not treat a reference list as evidence that the work is ready to advance.