A comprehensive guide to get started with AI and manage data debt
Each time a new technology is hyped, people have a tendency to apply it to every imaginable problem. AI is no exception.
But AI should not be used to solve every problem. There are three things companies that successfully implement AI have in common;
- They manage to find use cases with good AI-problem fit: not all problems should be solved with AI.
- Prioritizing among AI use cases: when the number of use cases with good AI-problem fit is too large, prioritization becomes important.
- They are managing their data debt: data is the food for AI. If data is bad, AI use cases will fail. In addition to financial debt, technical debt and organizational debt, data debt should be added to the agenda to create value through AI. Data debt is the single biggest blocker for AI adoption and is the number one reason why up to 80% of AI projects fail.
This guide will delve into each of the three areas, to ensure success for your AI projects.