Case Study: How to Translate Business Problems into correct AI Questions
In recent years, the term Artificial Intelligence has often been the focus of attention outside of technology-oriented organizations. Although most companies claim to use artificial intelligence technologies on a daily basis, in reality the implementation of these methods into the business process is mostly still in its infancy phase. The cause lies “lost in translation moment” between business problems/needs and AI related question and solution. We will present real cases (pharmacy, banking, tourism) how we defined a business problem and “translated” it to data scientists in AI terms to select the right AI technique to solve the problem cleanly and efficiently. Furthermore, some proven methods for evaluating the performance of AI models and validating the Use Case and ROI of the solution “on-the-job” will be presented for each case. All presented cases embedded analytics solutions in the business and overcame implementation difficulties.
- Business Problems
- How to address correct AI Questions
- How to achieve Value after all