IDC: Global spending on generative AI will reach $143 billion in 2027

A recent IDC research report predicts that global enterprise spending on generative artificial intelligence services, software, and infrastructure will grow dramatically over the next four years, expected to start in 2023 From US$1.6 billion to US$14.3 billion in 2027

From 2023 to 2027, global generative AI spending is expected to grow at a compound annual growth rate (CAGR) of 73.3%. IDC said this figure is more than twice the growth rate of overall AI spending and almost 13 times the compound annual growth rate of global IT spending over the same period.

IDC also predicts that by the end of 2027, generative AI spending will account for 28.1% of total AI spending, with generative AI infrastructure being the largest investment area in the construction phase during this period, including hardware, infrastructure As a Service (IaaS) and System Infrastructure Software (SIS).

IDC believes that by the end of the forecast period, spending on generative AI services will gradually exceed spending on infrastructure, with a compound annual growth rate of 76.8% over the next five years. In addition, the company predicts that the generative AI software field will grow the fastest during the forecast period from 2023 to 2027, with a compound annual growth rate of 96.4% for platforms and models, while the application development and deployment (AD&D) and application software fields will grow at a compound annual growth rate of 96.4%. The annual growth rate is 82.7%.

Ritu Jyoti, vice president of IDC’s AI business, said at a press conference releasing the research report, “Generative AI is not just a fleeting trend or pure hype; A transformative technology with far-reaching impact and commercial impact. With ethical and responsible implementation, generative AI will reshape industries and change the way we work, play and interact with the world."

Enterprises are currently trying adopt generative AI, but IDC expects they will start actively building targeted business use cases for wider adoption, including extending AI applications to edge networks.

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