It seems that nowadays everyone is becoming an “AI expert” because they have done some prompt engineering or played around with AI tools that help them create music. Everyone now considers themselves to be an AI developer. However, not too long ago, the world of AI users and AI developers and engineers were very different. How do you structure an AI team? For organizations that increasingly depend on AI, who is really on the AI team? A recent AI Today podcast explored this topic of the evolving AI team. Before LLMs became all the rage, the world of AI users and AI developers and engineers really were very different. Just a few years ago if you wanted to do anything with AI, you needed highly-skilled, well-paid, and hard-to-find individuals. These so-called “unicorns” that companies were trying to look for. Companies couldn’t hire data scientists fast enough and the search for this talent was fierce. Companies needed these highly skilled data scientists, machine learning engineers, data engineers, and these other well paid and hard to find individuals. They’re hard to find because you can’t just go to a few week code academy or read some things online and become a data scientist or become a machine learning engineer. It took a lot of time to get those skills. But now with generative AI, really almost anybody can generate stuff with AI. And generative AI has really, truly shifted the landscape of who is able to create these AI outputs. However, it’s important to note that while anyone can now create and interact with AI, that doesn’t mean everyone is an AI Developer.
Full opinion : For Organizations That Depend On AI, It Is Important To Figure Out Who Will Be On Their AI Team.
