The big conversation I wish was happening more among the organizations currently exploring gen AI is how to make the change stick and scale. At the end of the day, when you look at many of the companies right now, they're in exploration mode, which is correct, since this is new. They're throwing out some proofs of concept (POCs) to find the value, and what it will take to achieve. The big question revolves around the end intervention. What change will be needed in the organization to unlock the benefits? What do humans need to do differently to accept, adopt, and scale gen AI? I see more effort needed on that front in many organizations.
Similarly, on the technology side, one piece is about proving what the technology can do. And for those who really want to adopt and scale, another piece involves putting those foundations in place. Do you have the machine learning operations (MLOps) needed to productionize many, many, many models at scale? Do you have the data foundation necessary to really fuel the models and unlock the opportunities at that scale? I think those are the two conversations I would love to see taking place more across Europe.
