In the race to seize the competitive advantage that artificial intelligence (AI) can offer, many businesses have focused on the decades-old assumption that as long as the technology is good, they’ll undoubtedly be successful. While technology is important, prioritizing it at the expense of talent can often become a pitfall for organizations. If you want to build an armoire, you need a craftsman, not just the latest, most expensive hammers. Behind every successful AI project lies a foundation of AI skills — people who understand the importance of the trifecta of business priorities, sector context and technology.
With this in mind, here are three reasons why your AI strategy needs to start with AI talent sooner rather than later.
1. Talent will always matter more than technology.
Getting your hands on the latest and shiniest AI tech may make you feel proactive, but it won’t help you unless you have the talent to make it work for your business.
I’m not saying that the choice of technology doesn’t matter — it absolutely does. However, a talented team will always make the best use of a technology. Take, for example, the lunar landings and the great space race. When we were competing to be the first to the moon, what was considered state-of-the-art technology really had about as much computing power as a modern calculator.
In the grand scheme of things, what the NASA team of engineers and scientists achieved back then is still considered an incredibly impressive achievement today. What got Neil Armstrong and Buzz Aldrin to the moon was not the calculator-level technology, but the fact they had the talent to engage with the technology and get the most out of it. Even with limited technology, the best talent will achieve great things.
The converse, however, is not always true. There are many examples we could draw on to illustrate that merely throwing technology at the problem won’t solve it. Any good solution needs context. Just look at the Compas program, which was twice as likely to mistakenly label black defendants as possible second-offenders than white defendants in a U.S. court. The Northpointe software had taken in a pool of data to make its decision, but it hadn’t accounted for potential bias in the dataset to begin with -- that required context. Instead, they created a tool that was not only useless but racist.
2. AI talent is going, going, gone.
AI talent is in scarce supply. It is a sellers’ market out there and people with the skills to effectively implement an AI solution are going to the highest bidder. McKinsey predicted that this year, the U.S. alone could face a 50–60% gap between supply and demand for deep analytic talent — a key requirement for anyone looking to implement an AI project in their business.
It’s no secret that the search is on. Companies are finding that hardware alone isn’t sufficient to compete in future markets, so we’re seeing major players like Samsung setting up AI hubs in academic hotspots like Cambridge, just as Google settled into London’s Golden Triangle. This is all in the hope they can get their hands on top talent before their competitors do. These digital natives have set up shop with clear routes in for AI talent.
3. You need to find the right AI talent for your business.
For some organizations, hiring talent in this way just isn't possible. There will be companies that are looking to use AI to their advantage but are thinking to themselves: “We are not in the business of building internal analytics teams,” or “It is not at our core and we cannot offer the career paths needed to attract the caliber of talent we are after.”
But the opportunity cannot be ignored. You should still look to form partnerships with people who have data science expertise, otherwise, you risk getting left behind. When you find them, you must ensure they understand the business domain as well as your technology needs. This will enable the creation of custom AI that will squeeze as much value as possible from the platform you have invested in.
Naturally, an industry has evolved to meet this need and there are plenty of AI service providers and AI packaged apps that can reduce your dependency on in-house AI talent. If that’s you, the recent Gartner guide provides some excellent advice on how to find those best suited to your needs.
Just make sure you choose an approach that will lead you to people who are experienced, who can then go on and choose the right tools for the job.
After all, you could have the best, most expensive tools on the market, but if you want to build that armoire, you need skill behind those tools — you still need an experienced craftsman.
Written for Forbes by Matt Jones, Lead Analytics Strategist at Tessella.