The number of jobs affected by AI will vary by industry; through 2019, healthcare, the public sector and education will see continuously growing job demand while manufacturing will be hit the hardest. Starting in 2020, AI-related job creation will cross into positive territory, reaching two million net-new jobs in 2025.

"Many significant innovations in the past have been associated with a transition period of temporary job loss, followed by recovery, then business transformation and AI will likely follow this route," said Svetlana Sicular, research vice president at Gartner. AI will improve the productivity of many jobs, eliminating millions of middle- and low-level positions, but also creating millions more new positions of highly skilled, management and even the entry-level and low-skilled variety.

"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."

IT leaders should not only focus on the projected net increase of jobs. With each investment in AI-enabled technologies, they must take into consideration what jobs will be lost, what jobs will be created, and how it will transform how workers collaborate with others, make decisions and get work done.

"Now is the time to really impact your long-term AI direction," said Ms. Sicular. "For the greatest value, focus on augmenting people with AI. Enrich people's jobs, reimagine old tasks and create new industries. Transform your culture to make it rapidly adaptable to AI-related opportunities or threats."

Gartner identified additional predictions related to AI’s impact on the workplace:

AI has already been applied to highly repeatable tasks where large quantities of observations and decisions can be analyzed for patterns. However, applying AI to less-routine work that is more varied due to lower repeatability will soon start yielding superior benefits.

AI applied to nonroutine work is more likely to assist humans than replace them as combinations of humans and machines will perform more effectively than either human experts or AI-driven machines working alone will.