Wikipedia gives a good summary of the AI winter of the late eighties and early nineties (the qualification is necessary since there has been more than one). Some aspects of it are clear enough, but here's one I'm still curious about:
"By the early 90s, the earliest successful expert systems, such as XCON, proved too expensive to maintain. They were difficult to update, they could not learn, they were "brittle" (i.e., they could make grotesque mistakes when given unusual inputs), and they fell prey to problems (such as the qualification problem) that had been identified years earlier in research in nonmonotonic logic."
Okay, but all those things were just as true in 1980 as they were in 1990, yet XCON was very profitable in 1980 despite those problems, so why was it not still profitable in 1990? What changed?
The thing that comes to mind that might have changed is the competitive landscape. Conjecture: in 1980, the alternative to XCON was pen, paper and the occasional subproblem set up in VisiCalc. In 1990, the alternative was increasingly sophisticated ERP systems written with conventional technology, and the occasional use of Excel. XCON would still have been useful in 1990 had it been the only game in town, but the conventional alternatives were now good enough that it was no longer necessary to pay for the maintenance of an unconventional program.
Is that the reason, or is there something else I'm missing?