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Why You Shouldn't Specialize in AI/ML Development

Despite the hype surrounding generative AI, specializing in AI/ML programming could be risky. Here's why.

Knowledge workers with expertise in artificial intelligence and machine learning are in high demand — a fact that is unsurprising, given the current hype surrounding AI.

But that doesn't necessarily mean that software developers will benefit on the career front by pivoting toward AI. On the contrary, now may be a horrible time for developers to specialize in AI/ML programming. Here's why.

Why Are AI/ML Developers in Demand?

The main reason why companies are eager to hire developers and other engineers with expertise in AI/ML is simple enough: A new breed of powerful AI tools, heralded by ChatGPT, has emerged, and companies are keen to get in on the action. Organizations want employees who can build next-generation AI solutions tailored to their needs.

But that's only part of the story. There has long been demand for AI/ML specialists, and a shortage of qualified engineers to fill these roles. That trend stretches back to well before the rise of ChatGPT and other generative AI technologies.

So, demand for developers and other professionals with AI/ML expertise is not new, although it has been accelerated by the generative AI craze.

The Risks of an AI/ML Development Career

Given the long-standing demand for AI/ML specialists, it might seem like an obvious career strategy for developers to learn AI/ML solutions. You might think that mastering software like TensorFlow and PyTorch, to name just a couple examples of popular open source AI/ML tools, would be a ticket to a high-paying programming job.

In reality, though, specializing in AI/ML could be risky, for several reasons.

One is that the surge of interest in AI/ML at the moment will most likely turn out to be a fad. Although there will almost certainly always be some companies eager to hire AI/ML specialists, it seems unlikely that high rates of demand for professionals in this field will last indefinitely. Specializing in AI/ML might help you get a job today, but it's less clear that that will be the case three or five or seven years from now, when there will probably be more people with AI/ML development skills and fewer companies seeking to hire them.

A second reason why AI/ML developers might not always be in high demand is that so far, a relatively small number of companies have been at the forefront of innovation in the AI ecosystem, and most of those companies have a limited number of openings for AI/ML specialists. OpenAI, the company behind ChatGPT and the biggest name in the AI world at the moment, has only a few hundred employees. The large tech companies, like Amazon and Microsoft, certainly have AI/ML development teams, but AI is not yet central to their businesses or product lines, and it's not clear that it will become so — so they have limited need for AI/ML developers.

The takeaway here is that the total number of job openings for AI/ML developers over the next few years is likely to be in the low tens of thousands, not the hundreds of thousands. Companies may say they are interested in AI, but relatively few are hiring AI/ML developers in large numbers.

Finally, there is a pretty good chance that AI solutions will become available via an AI-as-a-service model, which will reduce the need for most companies to hire their own AI/ML developers. What I mean here is that rather than building its own AI/ML applications and services in-house, the typical company will purchase a ready-made solution from a vendor like OpenAI.

This has already happened with earlier generations of AI technology — you can obtain on-demand image recognition technology through a cloud service like Rekognition, for instance — and there is no reason to think it won't happen with generative AI, too. Few companies are going to build their own versions of ChatGPT if they can instead use APIs to interact with ChatGPT, a ready-made generative AI technology.

To be sure, companies that embrace AI-as-a-service may need a handful of AI/ML developers on staff to manage their use of the technology. But they are not going to be hiring large teams of AI/ML specialists because they won't be building their own AI engines.

When It Does Make Sense to Learn AI/ML

On balance, I'm not saying that no one anywhere should specialize in AI/ML development right now. If you actually have a genuine passion for AI/ML programming, then by all means, chase your dream.

But don't jump on the AI/ML bandwagon just because it's a trendy field right now. You're likely to find that AI/ML programming jobs are harder to find than the hype would suggest, and that demand for these roles will start to peter out once generative AI loses its shine and the tech industry moves onto the next big thing.

About the author

Christopher Tozzi headshotChristopher Tozzi is a technology analyst with subject matter expertise in cloud computing, application development, open source software, virtualization, containers and more. He also lectures at a major university in the Albany, New York, area. His book, “For Fun and Profit: A History of the Free and Open Source Software Revolution,” was published by MIT Press.
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