How to select an AI project that delivers business value (and how to quantify it)
AI Summary
AI Hype Summary
- Introduction
- AI is hyped due to its ability to create and deliver value for businesses.
- Project Selection Criteria
- Feasibility
- High feasibility: easy to implement.
- Low feasibility: difficult to implement.
- Value
- High value: significant benefit to the business.
- Low value: minimal benefit.
- Project Categories
- No Brainer: High feasibility, high value.
- Low Hanging Fruit: High feasibility, some value.
- Backlog: Low value, low feasibility.
- Big Bet: High value, low feasibility.
- Value Assessment
- Operational Efficiency
- Number of people involved.
- Percentage of their time spent on tasks.
- Average cost per person.
- Risk
- Types and magnitude of risks.
- Probability of occurrence.
- Time or future risk as an investment in technology.
- Revenue
- Avoid double counting with operational efficiency.
- Identify new revenue opportunities or cost savings.
- Conclusion
- AI delivers value in three key areas:
- Saves time and effort for people.
- Reduces risk.
- Drives new revenue or reduces costs.
- The excitement around AI is due to its potential to significantly increase business value.