The best place to start with AI is the intersection of three things: a task that wastes real time, a low risk if it goes wrong, and an outcome you can measure. Plenty of teams start with the most exciting idea instead - and stall. A simple grid keeps you honest.
The prioritisation grid
Score each candidate task from 1 to 5 on:
- Pain - how much time or money it wastes today
- Feasibility - how ready the data and tools are
- Risk - how costly a mistake would be (lower is better to start)
- Measurability - how clearly you can prove the result
Your first project is the one that scores high on pain, feasibility and measurability, and low on risk. Save the high-risk, high-reward ideas for later, once you have credibility.
Good first candidates in most organisations
- Drafting routine documents and communications
- Summarising long reports or meeting notes
- First-line customer or internal support
- Cleaning and analysing recurring data
These are the same low-friction wins behind the best way to start using AI.
Avoid starting here
Do not begin with regulated, safety-critical or reputation-sensitive processes. A visible early failure sets the whole programme back - the opposite of the momentum you want, and one of the biggest AI mistakes businesses make.
The bottom line
Start where pain is high and risk is low, prove it, then expand. Learning to prioritise AI opportunities this way is a core skill in the Strategic Application of AI in Business course at London School of Business UK. Enquire today.