AI is on every CIO\u2019s mind. It\u2019s 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.\n\nBut for many, there\u2019s a roadblock: where can they find the talent they need to deploy AI in their organizations?\n\nThe 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.\n\nBut enterprises don\u2019t 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.\n\nThese skills and mindset are teachable. But what\u2019s the best way to teach them? And for the many organizations who will need to hire external AI talent, what\u2019s the best way to go about it? AI talent is in demand, so it isn\u2019t cheap.\n\nHere are some tactics that can help:\n\n1. Go to schools\n\nUniversities are a great source for tech talent. College AI courses are booming. For example, enrollment in \u201cIntro to Machine Learning\u201d 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\u2019t forget faculty: many AI professors are moonlighting in business. Yann LeCun runs NYU\u2019s Center for Data Science and is also Facebook\u2019s Director of AI Research.\n\n2. Acquire\n\nM&A-based \u201cacqui-hires\u201d can pick up AI talent in a group deal\u2014but 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.\n\n3. Collaborate\n\nAn 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.\n\n4. Crowdsource\n\nCrowdsourcing isn\u2019t just for startups. In AI, it\u2019s 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\u2019s host specifies. The prize goes to the most effective model. A company can thus present an AI problem and let the crowd solve it.\n\n5. Use MOOCs to upskill\n\nLooking 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\u2019re more than satisfactory. After all, an organization\u2019s domain experts won\u2019t need to be computer programmers. They\u2019ll just have to be \u201ccitizen data scientists,\u201d who understand the basics. Andrew Ng\u2019s deeplearning.ai program on Coursera uses five online courses to explain neural networks and machine learning, is a good option.\n\n6. Hire AI as a service\n\nAI 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.\n\nOf course, talent is just one of the elements that organizations have to get right, if they\u2019re to take advantage of AI. As PwC\u2019s 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.\n\nBut there\u2019s no way to face any of these challenges without the right talent. If you haven\u2019t already, CIOs should start thinking about their AI talent strategies right away.