Where I work, there's a somewhat haphazardly divided org structure, where my team has some responsibility to answer the executives demands for "use AI to help o

Where I work, there's a somewhat haphazardly divided org structure, where my team has some responsibility to answer the executives demands for "use AI to help our core business". So we applied off-the-shelf models to extract structured context from mostly unstructured text - effectively a data engineering job - and thereby support analytics and create more dashboards for the execs to mull over. Another team, with a similar role in a different part of the org has jumped (feet first) into optimizing large language models to turn them into agents, without consulting the business about whether they need such things. RAG, LoRA and all this optimization is well and good, but this engineering focus has found no actual application, expect wasting several million bucks hiring staff to do something nobody wants.