AI is on every CIO’s mind. It’s coming down to earth and getting to work. And many corporations are flush with cash from tax reform. They can afford to invest in AI.
But for many, there’s a roadblock: where can they find the talent they need to deploy AI in their organizations?
The fact is, in the short term (and probably in the long term too, if we prepare well), AI is going to create at least as many jobs as it eliminates. Right now, however, the shortage of AI talent is acute.
But enterprises don’t just need computer scientists. They also need AI-savvy functional specialists to work alongside the more technical talent. These subject matter experts, in every field across the enterprise, will need new skills and a new mindset.
These skills and mindset are teachable. But what’s the best way to teach them? And for the many organizations who will need to hire external AI talent, what’s the best way to go about it? AI talent is in demand, so it isn’t cheap.
Here are some tactics that can help:
1. Go to schools
Universities are a great source for tech talent. College AI courses are booming. For example, enrollment in “Intro to Machine Learning” at Carnegie Mellon University (CMU) is up 600 percent in the last five years. You can get a head start on hiring by engaging a recruiter at one of the top college AI programs. Want to extend your reach farther? One example is Piazza, a collaboration platform with a portal for recruiters to target specific students. And don’t forget faculty: many AI professors are moonlighting in business. Yann LeCun runs NYU’s Center for Data Science and is also Facebook’s Director of AI Research.
M&A-based “acqui-hires” can pick up AI talent in a group deal—but the price tag is steep. The typical cost of onboarding each Ph.D. through M&A can run in the millions. Most organizations will need a more cost-effective option.
An increasing number of institutes, labs, and think tanks are eager to work with companies on AI. Canada, for example, has the Vector Institute, devoted to promoting AI research and business in the country, which is a world leader in AI. The Berkeley Artificial Intelligence Research Lab opened last year in conjunction with Huawei and UC Berkeley. IBM and MIT just announced a similar project.
Crowdsourcing isn’t just for startups. In AI, it’s increasingly for knowledge too. For example, on the knowledge site Kaggle (which Google recently acquired), experts compete to produce a prediction model based on parameters that the contest’s host specifies. The prize goes to the most effective model. A company can thus present an AI problem and let the crowd solve it.
5. Use MOOCs to upskill
Looking to get your current team up to speed on AI? Massive open online courses (MOOCs) are an affordable way to train staff on AI topics, and for many employees, they’re more than satisfactory. After all, an organization’s domain experts won’t need to be computer programmers. They’ll just have to be “citizen data scientists,” who understand the basics. Andrew Ng’s deeplearning.ai program on Coursera uses five online courses to explain neural networks and machine learning, is a good option.
6. Hire AI as a service
AI as a service allows companies to access highly qualified talent on a project basis. For example, Element.ai has in-house AI specialists as well as an academic network of more than 20 leading researchers it can tap into. Many established professional service firms also offer AI as service.
Of course, talent is just one of the elements that organizations have to get right, if they’re to take advantage of AI. As PwC’s recent look at what to expect from AI in 2018 found, many enterprises are also going to face AI-driven cyberthreats, pressure for responsible and explainable AI, and a need to break down barriers among internal teams and data cartels.
But there’s no way to face any of these challenges without the right talent. If you haven’t already, CIOs should start thinking about their AI talent strategies right away.
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