In 2020, artificial intelligence will create 2.3 million jobs and eliminate 1.8 million jobs, according to Gartner.
The number of jobs affected by AI will vary by industry, and 2019 will see a growing demand for jobs in healthcare, the public sector and education, while manufacturing will be hit with job losses. By 2020, AI-related job creation will cross into positive territory, reaching two million net-new jobs in 2025, the analyst's Predicts 2018: AI and the Future of Work report found.
Warnings about AI's impact on the economy are constantly in the news, and University of Oxford researchers have predicted that 35% of UK jobs are at risk of automation over the next two decades. But Gartner's findings suggest that AI could also improve the productivity of many roles.
"Many significant innovations in the past have been associated with a transition period of temporary job loss, followed by recovery ... business transformation and AI will likely follow this route," said Svetlana Sicular, research vice president at Gartner.
"Unfortunately, most calamitous warnings of job losses confuse AI with automation. That overshadows the greatest AI benefit: AI augmentation - a combination of human and artificial intelligence, where both complement each other."
For IT leaders, however, the focus shouldn't simply be on the potential increase in jobs. When considering investment in AI-enabled technologies, they must also consider which jobs will be lost, which will be created and how the technology will transform how employees work on a day-to-day basis. Gartner has previously underlined that CIOs will be responsible for choosing which tasks AI perform, and how it can help human workers.
The analyst firm has also predicted that by 2022, one in five workers engaged in non-routine tasks will rely on AI to perform certain jobs. AI has already been applied to highly repeatable tasks, where large volumes of data can be analysed for patterns. But applying AI to less routine work that is more varied will soon start yielding benefits.
AI applied to non-routine work is more likely to assist humans in the long run than replace them, as combinations of humans and machines will perform more effectively than either human experts or AI-driven machines working alone will.
