Generative Artificial Intelligence Revolution Heats Up in Asia/Pacific, with IDC expecting a 95.4% CAGR in 2027 · EMSNow
SINGAPORE – IDC’s latest Worldwide AI and Generative AI Spending Guide reveals that the Asia/Pacific* region is witnessing an unprecedented surge in Generative AI (GenAI) adoption, including software, services, and hardware for AI-centric** systems with spending projected to soar to $26 billion by 2027, with a compound annual growth rate (CAGR) of 95.4 percent for the period 2022-2027. This surge underscores the region’s pivotal role in driving the next wave of AI innovation and technological advancement.
GenAI is a branch of computer science involving unsupervised and semi-supervised algorithms that enable computers to create new content using previously created content, such as text, audio, video, images, and code, in response to short prompts. IDC believes GenAI will be a trigger technology to transition to a new chapter in the move toward automation for both internal and external parties across generic productivity, business function–specific enhancements, or industry-specific tasks.
“We anticipate that Asia/Pacific will experience a surge in the adoption of Generative AI, with growth rates expected to match those of North America, largely due to enterprises investing heavily in developing data and infrastructure platforms tailored for GenAI applications. We forecast that this investment in GenAI will reach its zenith within the next two years, followed by a period of stabilization. China is projected to maintain its position as the dominant market for GenAI, while Japan and India are set to become the most rapidly expanding markets in the forthcoming years,” Deepika Giri, Head of Research, Big Data & AI, IDC APJ.
Unlocking the vast potential of GenAI, the Asia/Pacific region is poised for a transformative journey across various sectors. With robust digital infrastructure and growing investments in technology, Asia/Pacific emerges as a pivotal player in this dynamic landscape. Strategic investment in hardware, software, and associated services for GenAI is crucial to sustaining and propelling this progress. From software development to customer service, GenAI is revolutionizing industries, ushering in a new era of innovation in Asia/Pacific.
IT spending in GenAI technology progresses through three distinct stages. Initially, during the GenAI Foundation Build phase, attention is directed towards enhancing core infrastructure, investing in IaaS, and bolstering security software. Subsequently, in the Broad Adoption phase, the focus shifts towards the widespread adoption of open-source AI platforms offered as-a-service, playing a fundamental role in digital business control planes. Finally, the Unified AI Services phase sees a surge in spending as organizations rapidly integrate GenAI to gain a competitive edge, diverging from the typical slower growth observed in new technology markets.
“GenAI isn’t a fleeting trend. Its capacity to generate entirely new content, across various mediums, such as images, videos, code, and marketing materials, promises substantial efficiency gains and paves the way for innovative creative opportunities, granting a competitive advantage,” says Vinayaka Venkatesh, Senior Market Analyst, IT Spending Guides, Customer Insights & Analysis, IDC Asia/Pacific. “A significant portion of organizations have either already adopted Generative AI or are in the initial stages of experimenting with models,” Vinayaka Venkatesh ends.
The financial services sector is experiencing rapid growth in Generative AI adoption in Asia. It is projected to reach $4.3 billion by 2027 with a remarkable CAGR of 96.7%. Within this industry, GenAI is being utilized internally to enhance operations efficiency, automate repetitive tasks, and optimize back-office processes such as fraud detection and the creation of intricate documents. Generative AI-powered solutions provide tailored financial services like personalized planning tools and reports, which dynamically adjust to meet customers’ evolving needs. Furthermore, the integration of GenAI yields substantial benefits to profitability by cutting costs, driving revenue generation, and enhancing productivity across various functions such as DevOps, marketing, and legal compliance.
The software and information services industry stands as the second-largest adopter of GenAI, embracing its versatility across sectors such as marketing, data analytics, and software development. Within marketing, GenAI can streamline content creation for websites, blogs, and social media platforms, optimizing marketing strategies and enhancing audience engagement. In data-driven fields like machine learning and analytics, GenAI proves invaluable for generating synthetic data, enriching existing datasets, and improving model performance and resilience. Additionally, in software development, these tools aid developers by automating coding tasks, generating prototypes, and accelerating the software development lifecycle, leading to heightened productivity and efficiency.
As the third-largest adopter of GenAI, governments across the Asia-Pacific region have a substantial opportunity to transform their operations and service delivery. This technology holds the potential to enhance efficiency, transparency, and citizen engagement. Governments are well-placed to spearhead efforts in advancing education and training in GenAI, thereby catalyzing the creation of new job prospects, and stimulating the growth of technology innovation hubs. These hubs will function as focal points for state-of-the-art training, bolstering skill sets, and nurturing the emergence of future AI professionals, including scientists, engineers, technicians, and specialists.
In the rapidly evolving Asia/Pacific retail market, characterized by diverse consumer preferences and advancing digital technologies, retailers are increasingly turning to GenAI to gain a competitive advantage. GenAI enables enhanced personalization, tailoring experiences to individual preferences, while also boosting efficiency by automating tasks like product design and content creation, thereby accelerating time-to-market. Furthermore, retailers leverage GenAI to create dynamic visual content and interactive experiences, fostering heightened customer engagement and loyalty.
IDC’s Worldwide AI and Generative AI Spending Guide measures spending for technologies that analyze, organize, access, and provide advisory services based on a range of unstructured information. The Spending Guide quantifies the AI opportunity by providing data for 38 use cases across 27 industries in nine regions and 32 countries. Data is also available for the related hardware, software, and services categories. The AI and Generative AI Spending Guide is produced to provide the latest market developments through an accurate and quality forecast. During the period between updates, IDC’s AI and Generative AI analyst teams conduct primary and secondary research to support this data product. Research in the period from August 2023 to February 2024 resulted in multiple additions and enhancements to the data. In this release of the AI and GenAI Spending Guide, we distilled leading forecasts such as IDC’s Worldwide Black Book and IDC’s Worldwide ICT Spending Guide, as well as AI and generative AI research led by IDC’s AI Council of senior researchers globally.
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**Taxonomy Note: The IDC Worldwide AI and Generative AI Spending Guide uses a precise definition of what constitutes an AI Application in which the application must have an AI component that is crucial to the application – without this AI component the application will not function. This distinction enables the Spending Guide to focus on those software applications that are strongly AI-centric. In comparison, the IDC Worldwide Semiannual Artificial Intelligence Tracker uses a broad definition of AI Applications that includes applications where the AI component is non-centric, or not fundamental, to the application. This enables the inclusion of vendors that have incorporated AI capabilities into their software, but the applications are not exclusively used for AI functions. In other words, the application will function without the inclusion of the AI component.
