A lot of "AI"/machine learning/etc. examples show impressive results on relatively narrow and well-controlled use cases. A lot of people look at those and extrapolate to much broader and less controlled environments with lots of messy corner cases and assume it's just a bit more incremental work to get there. Whereas, in fact, getting from essentially a demo to mostly just works in messy real world environments can easily be 90% of the work.