The whole picture – evaluating the returns for AI and considerations for success

I have eventually got to reading the CSIRO briefing paper “Evaluating and prioritising artificial intelligence projects” after missing the webinar launching it a couple of weeks ago (and caught up on the YouTube video of the webinar), and the topics particularly resonated with me, and pick up the themes I have been recently being talking about (Data is the first Challenge!, Is new tech a Silver Bullet or just Hype?) and do recommend that you read this paper and short checklist for selecting projects – which also provides some good thoughts on risks and challenges to manage.

A couple of quotes from the paper which I feel are worthwhile repeating.

The Executive summary and AI investment checklist is worth reviewing. Below are the headings, but the list within the document has some other useful prompts to check out as well.

  1. Strategic alignment and problem definition
  2. Investment and resources
  3. Data foundations
  4. Analytically robust evaluation, prioritisation and project selection
  5. Risk management and ethics
  6. Portfolio perspective
  7. Stakeholder engagement and qualitative factors
  8. Systems Integration and implementation
  9. Iterative approach and governance

I will pick up on some of the reasons AI projects fail, namely the interplay with people and systems in future posts, so please follow me on linkedIn to keep in touch.

Full Citation to the briefing paper: Evaluating and prioritising artificial intelligence projects: A guide for better decision making and investment outcomes. Stefan Hajkowicz, Chief Research Consultant, Analytics and Decision Sciences, CSIRO June
2025.

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