As industries invest more and more in projects that use AI software capabilities, IDC expects spending on AI systems to increase to USD 15.06 billion in 2022 with a compound annual growth rate (CAGR) of 50% during the 2018-2022 forecast period.

Swati Chaturvedi, Senior Market Analyst at IDC Asia/Pacific, stated:

Artificial Intelligence is changing the world as we speak. In fact, Asia/Pacific is quickly driving the growth in adoption of artificial intelligence because of its fertile & nascent digital ecosystem. Countries are developing economically with the help of technological advancements, increasing talent pool of millennials and growing number of tech-savvy businesses, to stay in this competitive market

In addition, regional spending on AI systems will be driven by the retail industry where retailers will invest over 70% of this industry spend on solutions such as merchandising, expert shopping advisory & recommendations, automated customer service agents and supply & logistics.

The AI use cases that will face the most investment this year are automated customer service agents (almost $700 million), sales process recommendation and automation (more than $450 million), and intelligent process automation (more than $350 million). Moreover, the fastest growth will be seen in digital twin/advanced digital simulation.

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What is more, hardware will be the largest area of AI systems spending in 2019 with about USD 7 billion going towards server and storage. Software will also be the fastest growing category for regional AI spending with a five-year CAGR of 80%.

Companies will also invest in IT services to develop their AI systems. By the end of the forecast, AI-related services spending will be slightly less than software spending.

China will be responsible for about two thirds of the Asia/Pacific - excluding Japan - (APEJ) regional spending on AI systems in all forecast years, driven by the retail, professional services and government industries. Nevertheless, Asia Pacific (excluding Japan & China) will indicate quick growth in adopting AI-enables solutions and deployment.

On the other hand, AI still faces many challenges from an application development and deployment perspective. The technology is dependent on multi-tiered technology stacks and many different skill sets. This makes its successful implementation to require organizations to enhance their capabilities in different dimensions including data, people, process, and infrastructure.

These organization are suggested to consider cloud-native infrastructure, review data readiness and practice data-driven decision making, according to Jessie Cai, Senior Research Manager at Cognitive Computing/Artificial Intelligence.

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