Produced in association with ADP (Founding sponsor), IMDA (Gold sponsor), Genesys, Splunk, Asia School of Business (Silver sponsors)
Given current projections for how artificial intelligence (AI) will transform business and society, many senior executives in Asia are bullish about AI as a source of future competitiveness. The second part of our series, “Asia’s AI agenda,” explores how businesses in the Asia-Pacific region are assessing the value of AI, creating strategies for deploying it within their organizations, evaluating the emerging use cases, and overcoming the challenges they are facing along the way. This report, “AI for business,” is based on a survey of 871 senior business and technology leaders across the Asia-Pacific and a series of expert interviews.
The key findings of the report are as follows:
Asia is past the halfway mark. More than half of the survey sample have already deployed AI technologies within their businesses. Of the 13 markets covered by the survey, the highest level of AI penetration is in North Asia—Japan and South Korea. Indonesia and Vietnam are at the most nascent stage, with just a quarter of companies using AI.
Adopting on a case-by-case basis. Less than a third of the “AI adopters” have a centralized strategy for AI. The majority are deploying AI case by case. Measuring the effectiveness of the technology on the same terms as other business projects is important, but with caveats. Machine learning takes place over a period of time and is only as effective as the quality of its training data.
Improving the customer experience is imperative. Delivering an improved customer experience is the number one priority for companies in Asia in terms of their development and deployment of AI, with more than half of survey respondents already having used AI in customer processes and interactions. Improving business decision-making speed and quality, and increased operational efficiency, are also ranked as organizational priorities for AI.
Machine learning is the most common AI tool. Machine learning is the most highly deployed AI tool according to our survey (44%), followed by automated reasoning (34%), natural language processing (33%), and robotic process automation (33%). In the year ahead, image recognition followed by reinforcement learning will be the fastest-growing areas of AI.
Constraints include talent, a lack of data, and high costs. A shortage of internal talent, noted by 58% of survey respondents, ranks as the region’s greatest challenge in deploying AI. Yet filling the gap is not easy, as AI engineers are scarce and in high demand. Moreover, retaining them is not guaranteed. Other top AI challenges reported in the survey include the lack of available data and the high costs of deployment.
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