>> Second, many AI projects fail because the organization lacks the necessary data to adequately train an effective AI model. > This is interesting, and reinfo

>> Second, many AI projects fail because the organization lacks the necessary data to adequately train an effective AI model. > This is interesting, and reinforces the trend towards hoarding data assets. Companies completely misunderstand where the data is suppose to come from and attempt to hoard user data. The issue with LLMs is that the problems they are currently best suited for require data generated by the company. Manuals, decision trees, guides, tutorials, expert knowledge in general and companies aren't producing that material, because it's expensive. Also if that data existed, then maybe they wouldn't need an LLM. Tons of LLM implementations are poor attempts to cover up issues with internal processes, lack of tooling and lack of documentation (without which the LLM can't function). I'd say 80% has failed, so far.