Demand For AI Talent More From Non-IT Departments: Gartner

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Skills, University teacher, PhD
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  • In March 2019, the number of AI jobs listed by IT went up to 68,959 and listings by other departments reached 156,294
  • Departments recruiting AI talent in high volumes are marketing, sales, customer service, finance, and research and development

Skills, University teacher, PhDThe strongest demand for talent with artificial intelligence (AI) skills comes from other business units and not from the IT department for the past four years as per Gartner. The report added that the number of AI jobs posted by IT was less than half of that from other departments.

As per the report in July 2015, IT departments published 14,900 listings for AI jobs while other business divisions posted 89,895 AI job listings. In March 2019, the number of AI jobs listed by IT went up to 68,959 and listings by other departments reached 156,294.

Asset-centric industries supporting projects

Peter Krensky, research director at Gartner said, “High demand and tight labor markets have made candidates with AI skills highly competitive, but hiring techniques and strategies have not kept up. In the recent Gartner AI and Machine Learning Development Strategies Study, respondents ranked “skills of staff” as the No. 1 challenge or barrier to the adoption of AI and machine learning (ML).”

The report said a significant portion of AI use cases is reported from asset-centric industries supporting projects. These include predictive maintenance, workflow and production optimization, quality control and supply chain optimization. It said that AI talent is often hired directly into these departments to let data scientists and others learn the intricacies of the specific business area and remain close to the deployment and consumption of their work.

Marketing, sales, customer service

Departments recruiting AI talent in high volumes are marketing, sales, customer service, finance, and research and development. They are using AI talent for customer churn modeling, customer profitability analysis, customer segmentation, cross-sell and upsell recommendations, demand planning, and risk management.

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