Enterprise adoption of artificial intelligence (AI) is approaching critical mass. Research firm Gartner reported earlier this year that 37 percent of organizations have deployed AI or plan to do so soon, up from 10 percent in 2015. It won’t be long before more than half of enterprises around the world are deploying AI on some level.
How much organizations benefit from their AI deployments, however, depends in large part on whether they have the skills internally to develop, manage, scale and troubleshoot AI implementations. In all likelihood they don’t, thanks to the shortage of AI talent that is holding back progress on AI projects across multiple industries.
“AI and machine learning are not turnkey solutions, at least not yet,” according to AI research firm Emerj. “You need people on your team with the requisite technical ability to train AI systems … Unfortunately, the number of folks with those skills is relatively few and far apart.”
Indeed, 54 percent of respondents to a Gartner enterprise survey said the biggest obstacle to their AI plans is a shortage of in-house skills. Given this formidable skills gap, it’s little wonder that most AI applications in the enterprise are, as Emerj says, “little more than ‘pilots.’” No one knows what they’re doing!
So how can enterprises eager to launch AI initiatives obtain (and retain) the necessary talent? There are no magic wands or secret AI jobsites, but enterprise decision makers can obtain the right AI talent by following a basic but comprehensive skills acquisition/development strategy.
Obviously, the first step is to define the AI objectives. This helps determine precisely which AI skills are required. So, a company developing a system for machines to visually inspect products and parts would need a computer vision engineer, while an organization building an AI-driven customer service chatbot would need a computational linguistics specialist. This AI skills assessment is an area where the chief information officer should take the lead.
Once it’s clear which AI skills are needed, organizations have four basic sources for talent. Since all have advantages and disadvantages, it’s best to employ a combination if possible.
Hiring from outside and inside
If finding the right AI specialists quickly is your priority, posting a job online or using your network to reach out to candidates are obvious avenues. And if you offer enough money, you’ll definitely draw interest.
The problem with hiring from outside is that it can take longer than expected, especially when there’s a shortage of qualified candidates. On top of this, it’s hard for all but the largest enterprises to compete for AI talent with deep-pocketed tech giants such as Google and Microsoft.
Another common way to quickly acquire both talent and technology is to buy out a startup or smaller organization. This is an attractive option, in that you can assess the work of the AI staff based on the products and services they’ve developed.
Nonetheless, acquisitions always carry inherent risks. Not only can it be difficult to integrate new technologies, it can be even more challenging to integrate cultures. If the AI staff from the acquired company lacks enthusiasm for your enterprise’s mission, they won’t stick around long — not in this job market.
A longer-term option for an organization in need of AI talent is to develop from within. Offer training programs in various AI disciplines and recruit internal candidates, particularly those with backgrounds in programming, data management and statistics. While well-designed AI training programs can deliver a great return on investment, they aren’t overnight solutions.
Also, some organizations may struggle to recruit internal candidates. This may be the byproduct of enterprise leaders failing to effectively communicate their AI vision, or the employees may fear that AI will cost them their jobs.
Finally, some organizations have established industry and academic partnerships to develop AI initiatives and create a pipeline of AI talent. For example, autonomous vehicle manufacturer Argo AI recently announced a 5-year, $15 million research partnership with Carnegie Mellon University. Given that Argo was founded by Carnegie alumni, this deal virtually ensures that the company will have access to potential AI specialists who already are familiar with their company and objectives. Although such partnerships can take time to develop, they can result in AI hiring decisions that have a high probability of success.
The shortage of AI talent creates genuine competitive challenges for organizations that can’t simply open their checkbooks to qualified candidates. Enterprises that want to fully leverage AI first must clearly define their goals and the specific skill sets needed to achieve them. Then they should build and cultivate multiple sources of AI talent. This will increase the chances that an enterprise’s AI initiatives will be successful and sustainable.