Artificial Intelligence (AI) applications offer exciting possibilities for transforming how business is done. Its applications are complex and very new. There is a lot to consider when choosing which AI tools to implement. Here are some key factors to look at when researching what’s best for your company.
Manage your data
Distributors collect a myriad of valuable customer, internal, and vendor information in the process of doing business. AI can generate outputs based on that internal data, whether stored in the cloud or on-premises. If that data isn’t properly managed, your AI-driven business processes might suffer the consequences. In a recent Forbes article on this topic, Simon Jelly points out that only 23% of your collected data will probably be “good” data. Your AI applications are only as effective as the data you input. According to Jelley, there is a lot of data to clean to get to the good stuff.
Classify your data
Jelley suggests that after you have captured the relevant data, you classify it. There are 3 key steps to this:
- Create the sets of definitions, labels, and groups you will use to organize your data.
- Apply that taxonomy to your data.
- Establish a single source of truth (SSOT) location for each category of your data.
Clean your data
Once classified, clean your data to rid it of the ROT (redundant, obsolete, or trivial). Redundant data can give AI the impression that something is more important than it is because it’s repeated. Once AI has clean data, it will help keep it clean.
Optimal results
Remember, only about a quarter of the data you collect will be useful to your AI tools. When considering how to get the most out of your AI applications, look to good data management. Classify and clean your data for optimal results.
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