Most companies started their journey from analytics to AI some years ago by jumping on the data science train. In those days data scientist was assumed to be the most sexy job of the 21st century. With the first use cases the appetite for more analytics increased. But there is also a long list of failed projects. Now, we have GenAI and everybody is jumping on the AI train. That is a good point in time, to take a moment to ask what are the lessons learned from the journey so far? And where will we go next?
Join this session, to learn more about:
- Why some data science and AI initiatives succeed while others fail, exploring common pitfalls
- How the role of data science has evolved with the advent of generative AI, including shifts in required skills, tools, and approaches that are reshaping AI-driven strategies
- Actionable steps to advance the AI journey, focusing on aligning AI initiatives with business goals, scaling AI responsibly, and preparing for future advancements in the AI landscape
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