Gartner: Less than half of AI jobs over the past 4 years were in IT

Over the past four years, the strongest demand for candidates with AI skills hasn’t come from IT departments, but from other business units within organizations. That’s according to a Gartner report that found that the number of AI jobs posted by IT was less than half of that from other departments, indicating that hiring strategies haven’t kept pace with demand in the AI labor market.

In total, in July 2015, IT departments published 14,900 listings for AI jobs compared with the 89,895 AI job listings published by other business divisions. In March 2019, the number of AI jobs listed by IT jumped 363% to 68,959, but listings by other departments far surpassed it with 156,294 (up 74% from 2015).

Departments recruiting AI talent in high volumes included marketing, sales, customer service, finance, and research and development, which tapped new recruits for things like customer churn modeling, customer profitability analysis, customer segmentation, cross-sell and upsell recommendations, demand planning, and risk management. Asset-centric industries reported a significant portion of AI use cases for projects such as predictive maintenance, workflow, production optimization, quality control, and supply chain optimization.

“In the recent Gartner AI and Machine Learning Development Strategies Study, respondents ranked ‘skills of staff’ as the number one challenge or barrier to the adoption of AI and machine learning,” said Gartner analyst and director Peter Krensky in a statement. “Given the complexity, novelty, multidisciplinary nature and potentially profound impact of AI, CIOs are well-placed to help HR in the hiring of AI talent in all business units. Together, CIOs and HR leaders should rethink what skills are truly necessary for an AI-focused employee to have on day one and explore candidate criteria adjacent to hiring specifications. CIOs should also think creatively about IT’s role in governing and supporting diverse AI initiatives and the evolving teams driving this activity.”

The AI talent gap is well-documented.

A recent study conducted by analysts at International Data Corporation (IDC) found that of the organizations already using AI, only 25% have developed an “enterprise-wide” AI strategy as a result of cost overruns, a lack of qualified workers, biased data, and skills shortages. Separately, a December 2017 report by Tencent Research Institute indicated that there were about 300,000 AI practitioners and researchers worldwide, but millions of roles available for people with these qualifications.

Still, despite a few bumps in the road, there’s no question that AI is an unstoppable force — particularly in the enterprise.

Gartner reported in January 2019 that AI implementation grew a whopping 270% in the past four years, and 37% in the past year alone. That’s up from 10% in 2015, which isn’t too surprising considering that by some estimates, the enterprise AI market will be worth $6.14 billion by 2022. According to the McKinsey Global Institute, the subsequent labor market shifts will result in a 1.2% increase in gross domestic product growth (GDP) for the next 10 years and help capture an additional 20% to 25% in net economic benefits — $13 trillion globally — in the next 12 years.

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