Overview: Many large organisations have begun their Artificial Intelligence (AI) journeys, but some have taken unusual directions, while others are adopting a wait-and-see approach. As a general rule, I believe most organisations should identify the most important AI use cases and, using a basic scoring system, prioritise the easy, high-value ones first.
A good option is to hire an AI-focused team to implement the AI program within your business. Hire internal staff with key domain knowledge and pair them with IT experts, preferably those with strong AI skills.
Tip: All Digital Transformation Projects must cover People, Process and Technology in that order of importance.
Thought: The two biggest mistakes I have observed as of July 2025 in clients are a lack of clearly defined benefits of AI projects and poor-quality, insecure data.
FAIRS for:
- Findable,
- Accessible,
- Interoperable,
- Reusable, and
- Secure.
Tip: If your organisation's data is in a good FAIRS state, AI projects are far more likely to succeed.
1. AI Idea Generation: Collate a detailed list of possible ideas. I like to use SharePoint, it's a good idea to open up idea generation to the business or make gamification of idea generation to get a good set of ideas. You'll get lots of overlap, distil it into unique ideas, and bring the team/stakeholders together.
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| Figure 1. AI idea filter funnel |
3. Technological Feasibility: Can technology meet the requirement, and at what cost? A high-level technical design is strongly recommended, as shown in Figure 2.
4. Implement: If the idea holds up to Business impact, and is possible, select the highest value to lowest effort ideas. It is a good idea to start with the simpler ideas to get the ball rolling.



