In the pursuit of innovation and technological advancement, businesses are eagerly hopping aboard the artificial intelligence (AI) bandwagon.
More than half (68%) of businesses have already implemented AI within their organizations in 2017, and that number is expected to grow as companies reap the benefits of automating repetitive tasks, streamlining internal workflows, and improving employee productivity.
But as AI jobs become increasingly popular, we’re also seeing a significant staffing problem for employers looking to fill those roles. Demand is quickly outstripping the AI talent supply, and businesses are discovering how difficult it is to hire the very best of the qualified candidates available.
A Widespread AI Shortage Is Fueling a Small but Expensive Candidate Pool
Businesses recognize AI’s massive potential, but its newfound popularity has made qualified candidates a rare commodity.
Demand for workers with AI skills has grown significantly over the past 3 years, with the number of AI-related job postings up about 119%, according to job-posting site Indeed. Interest is at an all-time high, but employee searches for AI-related positions have plateaued within the last year, suggesting a disinterest on the jobseeker side. In other words, employers increasingly need to fill roles like data scientists and software architects, but there aren’t enough candidates applying for those positions.
Contributing to the skills gap is the indifference toward AI-related fields at the university level. Business degrees remain the most popular college major, while computer science degrees don’t even crack the top five. Despite the lure of a six-figure salary, more than 500,000 computing jobs remain unfulfilled in the United States, and funding for science, technology, engineering, and math (STEM) programs remains in jeopardy under the Trump administration.
The few candidates who are versed in AI hold tremendous negotiating power over the companies clamoring for their attention. Experienced analysts and data engineers can selectively choose where they take their talents, often driving salaries into the high six figures. Although corporations like Apple and Google can afford to shell out big bucks for the best of the best, this can force out organizations with less capital looking to break into the AI marketplace.
Thinking Outside the Box—How Businesses Can Achieve Their AI Goals with Less
Until now, the AI marketplace has excluded organizations that lack the money to go head-to-head with Big Tech. But resource-strapped businesses are identifying new ways to stand out in a competitive job market and uncover valuable talent in places most tech conglomerates aren’t looking.
Despite starting with a disadvantage, corporations big and small can realize their own AI-fueled aspirations by:
- Promoting AI education in high schoolers and even younger. Recruiting for AI is a lot like recruiting for college athletics—businesses have to look as far back as the high school level, or younger, to develop talent for the future. One big advantage younger generations have over today’s workforce is they’re already familiar with AI-powered devices, having grown up with automation and natural language processing machines. Companies can partner with students in school to raise awareness around careers in AI and even offer hands-on internship experience for interested candidates. Although this represents a longer-term initiative, exposing young students to AI now can help fill the talent pipeline with more qualified applicants down the road.
- Training existing employees with similar skill sets. While educating high schoolers on STEM-based career paths is great for future talent pools, it doesn’t address the immediate need for AI talent. To solve for today’s AI demand, companies can retrain their current engineers who are already competent in skills like math and science that are necessary prerequisites for an AI career. Encouraging employees to switch to an AI-focused position will require companies to provide defined career paths with opportunities for employees to climb the corporate ladder.
- Developing an AI-first mentality with easy “wins.” It’s human nature to resist change—for corporations intent on adopting an AI culture, they need to first demonstrate the business value of AI to their own teams. Companies should identify a simple, internal process that can be replaced with an easy-to-implement AI tool to get everybody on board. Something like automating an administrative workflow doesn’t require a PhD but still demonstrates how AI can help employees boost their productivity. Identifying the quick “wins” can also help businesses understand just how much data they are working with so employers can hire the right candidates for future jobs.
The AI talent drought is expected to persist for the immediate future, but a shortage of talent doesn’t mean businesses can’t get started on their own deep-learning projects today. From investing in their future pipeline to leveraging existing employee resources, companies of all sizes don’t have to wait to experience AI’s business impact for themselves.
|Antonis Papatsaras, PhD, takes tech to new levels at SpringCM. He can translate his 15 years’ experience in massive cloud infrastructure, highly available and scalable architectures, very high-volume ingestion, and AI knowledge into smart strategies and projects that put the SpringCM cloud platform in a class by itself. Before he joined SpringCM, Papatsaras was Director of Software Engineering of Autonomy, where he led the re-architecture of numerous products to true software-as-a-service (SaaS) multichannel, multitenant solutions.
Papatsaras was also Director of Software Engineering at Interwoven and Vice President of Software Engineering at Discovery Mining, an SaaS eDiscovery company. He received his PhD in Formal Specification and Design of Safety Critical/Distributed Systems from Teesside University in the United Kingdom. In 2003, he was elected a member of the Institute of Learning and Teaching in Higher Education (ILTHE), and in 2007, he achieved the status of Fellow of the Higher Education Academy. Connect on Twitter: @anton1s