Day 2 | 21st October
- Sharing honest experiences of failed or underperforming AI initiatives, including where expectations didn't match reality and why certain use cases didn't deliver impact
- Identifying the most common reasons AI projects stall or fail, from poor data foundations and unclear ownership to overhyped use cases and lack of internal alignment
- Exploring how to apply these lessons to future initiatives, including how to prioritise the right use cases, set realistic expectations, and build scalable, outcome-driven AI strategies
Check out the incredible speaker line-up to see who will be joining Anders.
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