AI-generated code still requires software engineers to build, test, debug, deploy, secure, monitor, be on-call, support, handle incidents, and so on. That's very expensive. It is much cheaper to pay a small monthly fee to a SaaS company.
So what happens is a corporation ends up spending a lot of money for a square tool that they have to hammer into a circle hole. They do it because the alternative is worse.
AI coding does not allow you to build anything even mildly complex with no programmers yet. But it does reduced by an order of magnitude the amount of money you need to spend on programming a solution that would work better.
Another thing AI enables is significantly lower switching costs. A friend of mine owned an in person and online retailer that was early to the game, having come online in the late 90s. I remember asking him, sometime around 2010, when his Store had become very difficult to use, why he didn’t switch to a more modern selling platform, and the answer was that it would have taken him years to get his inventory moved from one system to another. Modern AI probably could’ve done almost all of the work for him.
I can’t even imagine what would happen if somebody like Ford wanted to get off of their SAP or Oracle solution. A lot of these products don’t withhold access to your data but they also won’t provide it to you in any format that could be used without a ton of work that until recently would’ve required a large number of man hours
no way. We're not talking a standalone AI created program for a single end-user, but entire integrated e-commerce enterprise system that needs to work at scale and volume. Way harder.
Their initial answer/efforts seem to be a qualified but very qualified "Possibly" (hah).
They talked of pattern matching and recognition being a very strong point, but yeah, the edge cases tripping things up, whether corrupt data or something very obscure.
Somewhat like the study of MRIs and CTs of people who had no cancer diagnosis but would later go on to develop cancer (i.e. they were sick enough that imaging and testing was being ordered but there were no/insufficient markers for a radiologist/oncologist to make the diagnosis, but in short order they did develop those markers). AI was very good at analyzing the data set and with high accuracy saying "this person likely went on to have cancer", but couldn't tell you why or what it found.