"The use of smart machines by enterprises can be transformative and disruptive. Smart machines will profoundly change the way work is done and how value is created. From dynamic pricing models and fraud detection, to predictive policing and robotics, smart machines have broad applicability in all industries," said Susan Tan, Research Vice President at Gartner, in a press release.
Technologies under smart machines include cognitive computing, artificial intelligence (AI), intelligent automation, machine learning, and deep learning. Gartner said these technologies will be adopted at different speeds and timings, with majority of smart technologies to be dominantly adopted between the 2020 and 2025 timeframe.
"For service providers, smart machines represent opportunities to help enterprises assess, select, implement, change and adapt talent, and for IT and business processes, the opportunity to successfully adopt smart machines for business benefits," added Tan.
In line, the opportunity for consulting and system integration (C&SI) services will expand from advising enterprises to help them sort through the hype to helping them with strategic design, training of the smart machines, deployment and integration to expansion and ongoing refinement.
As such, Gartner said spending on smart machine C&SI services is expected to grow from US$451 million this year to nearly US$29 billion in 2021.
"Over time, the increased C&SI opportunity created by the growing number of companies implementing more complex smart machine programmes is expected to be counter-balanced by the reduction in costs of adoption, as every subsequent adoption of the same smart machine solution will be less expensive and faster," said Tan.
Gartner said investments on smart machines will span more than a decade, which indicates the longevity of the smart machine C&SI service market.
"In the long term (about 10 years), smart machines will be an integral set of tools in the toolkit of C&SI service providers and infused into all next-generation services offerings," Tan concluded.
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