I'm working on integrating AI into a product right now: IMO you want to look at what's happening now as more a shift in cost to develop and maintain - which itself is going to create qualitative differences.
I can now have 1-2 developers stand up ML backed services at a level of quality that a few years ago would have required an ML + engineering team to build along with an ongoing tuning burden. Now that the AI is "good enough" out of the box time-to-value has dropped, which also allows for more exploration.
One area I'm seeing a lot of traction at my company and amongst other developers: onboarding flows for complex products. LLMs are really great at taking a small amount of input from or about a user, walking down a decision tree, and creating some initial dummy data relevant to them to more quickly demonstrate value. You might not ever know chatGPT is involved but it doing wonders for quite a few companies' conversion rates.
I can now have 1-2 developers stand up ML backed services at a level of quality that a few years ago would have required an ML + engineering team to build along with an ongoing tuning burden. Now that the AI is "good enough" out of the box time-to-value has dropped, which also allows for more exploration.
One area I'm seeing a lot of traction at my company and amongst other developers: onboarding flows for complex products. LLMs are really great at taking a small amount of input from or about a user, walking down a decision tree, and creating some initial dummy data relevant to them to more quickly demonstrate value. You might not ever know chatGPT is involved but it doing wonders for quite a few companies' conversion rates.