Opinion | A.I. Slopware Is Everywhere Now. Nobody Is Using It.

The number of mobile apps available on Apple’s App Store was up 30 percent last year, according to one estimate. But downloads were up only 3 percent.

It isn’t just apps. Software in general — everything made of code — is suddenly available in huge, heaping quantities. Thanks to artificial intelligence, you can now, in plain language, tell a computer to write code, and it will often do an excellent job. These capabilities get better nearly every week.

But when was the last time you ended up marveling at a new app or game on your phone? Whither the applications like Slack that take industries by storm, or games like Candy Crush that dominate our subway commutes? Is it just all app slop from here on? Did A.I. kill the “killer app”?

That would be a natural conclusion to draw, but I think that we’re headed for a very different kind of digital revolution. We shouldn’t expect a spate of A.I.-made software to replace all our existing tools. After all, people don’t like to switch to new software unless they must. A.I.’s real strength may be to make many new things that play a more moderate, specific role: reducing sources of small friction that otherwise stack up in our lives.

Most big corporate efforts to use A.I. to increase productivity fail — perhaps as many as 95 percent, according to an M.I.T. study published last year. A boss sits a team down — let’s say it’s a financial services firm, or a consulting firm — and asks them to use A.I. to improve the sales process or track relationships, and after a lot of trial and error, it doesn’t work out. This finding is quite awkward, given the projected multibillion-dollar valuations of A.I. companies, but nothing I’ve learned from talking to dozens of people in the industry disproves it. People are hopeful that a bold A.I.-powered future is right around the corner. They are tantalized. They often use A.I. tools all the time individually. But companies’ internal efforts don’t work.

I don’t blame the coders for this, or even the bosses. I blame the big A.I. companies, who are in such a hurry that they often release new versions of their models and tools without manuals or even clear YouTube tutorials. When projects fail, the implication is that humans just need to stop everything else they’re doing and prompt the models harder.