Published on October 29, 2023, 9:54 pm

Asia/Pacific (excluding Japan) is projected to increase spending on AI systems from $17.6 billion in 2022 to $32 billion by 2025, reflecting businesses' recognition of the benefits of AI. Singapore, Australia, and Japan lead in AI usage, followed closely by Malaysia, Thailand, Vietnam, Indonesia, South Korea, and Hong Kong. The banking industry is expected to invest the most in AI solutions, particularly in risk mitigation and fraud analysis. Professional services are also investing heavily in AI to enhance customer service and streamline tasks. However, there remains a gap between companies that heavily invest in AI and those that do not. Challenges to widespread adoption include concerns over the changing business landscape, data quality, data governance, ethical considerations, and a lack of relevant use cases. The COVID-19 pandemic has accelerated the integration of AI through remote working and increased interconnectedness of customer experience systems. Successful integration requires support from senior leaders, resource allocation towards AI projects, and involvement from those who will apply the models. Leadership involvement is crucial for successful adoption, and establishing a Center of Excellence (CoE) can facilitate scaling AI adoption more effectively. Organizations must prioritize aligning use cases with real business challenges and understanding the significance of data for successful implementation.

Asia/Pacific (excluding Japan) is set to witness a significant increase in spending on AI systems according to IDC, with the investment projected to rise from US$17.6 billion in 2022 to approximately US$32 billion by 2025. This surge in investment reflects businesses’ recognition of the potential benefits that artificial intelligence (AI) can bring, such as improved customer insights, increased employee efficiency, and faster decision-making processes.

Dr Chris Marshall, associate vice president responsible for data, analytics, and AI at IDC Asia/Pacific, emphasizes the varying levels of AI adoption and maturity across different countries. Singapore, Australia, and Japan lead in terms of AI usage, closely followed by Malaysia, Thailand, Vietnam, Indonesia, South Korea, and Hong Kong.

IDC predicts that the banking industry will continue to invest the most in AI solutions over the next five years. Within the banking sector, risk mitigation through augmented threat intelligence and fraud analysis applications takes precedence. Meanwhile, state/local government ranks second in terms of AI investment expenditure due to a focus on public safety and emergency response systems.

Another rapidly growing industry in terms of AI investment is professional services. With a projected compound annual growth rate (CAGR) of 26.6% over the next five years, professional services companies aim to enhance customer service by employing augmented customer service agents capable of resolving customer issues more effectively. Furthermore, these organizations are keen on leveraging smart business innovation and automation to streamline complex and repetitive tasks while facilitating organizational decision-making.

Dr Marshall highlights a widening gap between companies that heavily invest in AI (the top 40%) and those that are not as active in this area (the other 60%). As successful implementation yields value for businesses investing more heavily in AI technologies while prompting additional investments into it.

Despite the great potential AI holds for organizations across various sectors within Asia/Pacific region there are hurdles inhibiting widespread adoption. FutureCIO’s July 2022 roundtable in Singapore identifies concerns over the changing business landscape as one of these obstacles. Other issues that impede AI adoption include data quality, data governance, and ethical considerations.

Dr Marshall points out the limited availability of relevant use cases on the market as a hurdle to AI adoption. Smaller companies often imitate larger firms that have the resources to experiment and adopt AI technologies but may not necessarily focus on relevant use cases. This lack of relevance undermines their potential for success in this area.

Regarding the impact of the pandemic on AI adoption, Dr Marshall acknowledges that remote or hybrid working has become more prevalent due to the COVID-19 crisis, revolutionizing how businesses operate. Additionally, customer experience and transaction-based systems are becoming increasingly interconnected. As organizations transition into digital transformations, large amounts of data are generated which can be leveraged by AI systems effectively.

Success in integrating AI can serve as a catalyst for further investment and development within organizations. According to Dr Marshall, successful integration involves three stages: generating idea support from senior leaders, allocating resources towards AI projects, and involving individuals who will ultimately apply the models. Organizations need to understand how incorporating AI adds value before initiating their journey.

Singapore’s parks represent one example where digitalization technology has made significant headway in managing park facilities. Through utilizing data analytics, IoT integrations, and AI algorithms, Singapore successfully optimizes processes related to managing its parks.

Dr Renée Richardson Gosline from MIT emphasizes that hurdles such as human bias offer valuable opportunities for “good friction” within the AI journey. She argues that executives aiming to enhance customer experiences must embrace good friction to interrupt automaticity when applying black box-like AI systems.

Drawing upon Dr Marshall’s insights from IDC Asia/Pacific’s research findings, it is apparent that leadership involvement is crucial when considering adopting new technologies like AI; understanding where it aligns with specific business problems is fundamental to success. Establishing a Center of Excellence (CoE) can facilitate scaling AI adoption more effectively. Furthermore, organizations must acknowledge the significance of data for AI implementation as it forms the backbone of successful AI programs.

As Asia/Pacific continues to invest in AI technologies, enterprises should prioritize aligning their use cases with real business challenges. Additionally, examining successful use cases and designing an effective roadmap can guide organizations towards achieving optimal results through AI adoption.

To listen to Dr Chris Marshall’s perspectives on AI adoption in Asia/Pacific and his recommendations for getting the most out of AI, access the PodChats for FutureCIO episode through this link.

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