Although artificial intelligence and machine learning remain relatively niche technology segments, their usage is rapidly expanding as more businesses attempt to “smarten” their apps and services. Where are companies hiring the most technologists with A.I. and machine learning experience, and which industries are driving demand?
Let’s start by taking a look at the U.S. metro areas with the most A.I.-related job postings, as curated by CompTIA (which relies on Burning Glass, the same nationwide database of job postings that Dice uses). As you might expect, the top cities for A.I. job postings overlap with the nation’s most well-established tech hubs, which makes sense.
Meanwhile, the industries pushing hardest to acquire artificial intelligence talent include professional, scientific and technical services (which represents much of the tech industry), finance and insurance, manufacturing, and information (also representing the “core” tech industry). Finance and insurance companies have shown increasing interest in A.I. as a tool for predicting markets, streamlining customer service, and successfully mining datasets for insights. In manufacturing, meanwhile, A.I. is widely viewed as the key to automation.
As you can see from the chart below, though, the number of A.I.-related jobs within these industries is still relatively small. That could change in coming years as A.I. and machine-learning tools become cheaper and more commoditized, and more businesses (large and small) realize these technologies can mean the difference between success and failure:
At the moment, companies’ top uses for A.I. include predictive sales/lead scoring, CRM/service delivery optimization, chatbots and digital assistants, cybersecurity threat detection, and marketing automation. If teams are going to invest massive amounts of money and talent in building out an A.I. capability, they probably want a relatively quick return on investment, which is probably why utilizing A.I. in a sales and customer-service context is so popular. However, the use-cases will proliferate as A.I. tools become more widespread and easier to use.