Alibaba Cloud Research Reveals Rapid AI Adoption Across Asia, Yet Challenges Remain
Alibaba Cloud has released a survey report titled “The AI Business Application Readiness and Accessibility Survey,” which indicates high enthusiasm among Asian companies regarding the adoption of Artificial Intelligence (AI). Approximately 90% of respondents expressed optimism regarding the implementation of AI within their organisations.
This optimism is translating into concrete investment plans. Around 95% of surveyed companies intend to increase their investment in AI products. More than half of the respondents plan to raise budgets by over 20% for Infrastructure as a Service (IaaS), Platform as a Service (PaaS), and Model as a Service (MaaS).
As AI becomes a strategic corporate agenda, 58% of respondents plan to increase MaaS spending by more than 20%. Although MaaS is a relatively new concept, the largest investments remain directed towards fundamental AI infrastructure, such as computing, data storage, and networking; 69% of respondents plan to increase IaaS spending by more than 20%, followed by 61% planning similar growth in PaaS investments.
Indonesia recorded the highest level of enthusiasm for AI compared to other surveyed countries. All respondents (100%) expressed optimism regarding AI implementation in their organisations. Indonesia also leads in cloud infrastructure adoption, with 91% of respondents stating that their IT infrastructure is fully or largely running on the cloud. For Indonesian companies, AI is no longer viewed merely as a tool for efficiency; 75% of respondents stated that driving innovation and creating new business opportunities are their primary goals in adopting AI.
Five Key Strategic Objectives for AI Adoption
For the majority of respondents, AI is transitioning from the experimental stage to operational implementation. Approximately 75% of companies in Asia stated that AI has become an integral part of their business operations. Across various layers of the AI ecosystem, about 90% of companies reported they have begun adopting both PaaS and MaaS, while only 1% stated that AI is not a priority for their organisation.
Beyond improving operational efficiency and cost savings (63%), the primary strategic drivers for AI adoption are driving innovation and unlocking new business opportunities (64%), followed by optimising revenue growth potential (48%). Gaining a competitive advantage (45%) and enhancing customer experience (43%) also rank among the top five objectives.
In terms of application, companies are prioritising AI for data analysis and decision-making (66%), customer services such as chatbots (64%), marketing and content creation (58%), product development including coding (55%), and human resources operations (38%).
The Need for Full-Stack Agentic AI Cloud Solutions
The study indicates a high demand for integrated AI and Cloud solutions within a unified technology suite. When selecting AI solution providers, 45% of respondents prefer fully integrated AI + Cloud solutions. Meanwhile, 34% prefer hybrid flexibility with models that can be deployed across various clouds, and only 16% prefer standalone AI models without integrated cloud infrastructure.
Integrated AI + Cloud architectures are often preferred as they allow for centralised management and security of data and models, simplify the implementation process, and provide companies with clearer cost control through pay-as-you-go schemes. Respondents noted that integrated technology helps companies standardise data flows, implement consistent governance and security policies, and accelerate the realisation of benefits from various AI initiatives.
Main Challenges in AI Adoption: Privacy, Cost, and Skill Gaps
Despite increasing enthusiasm and investment, companies still face various challenges in expanding AI implementation. Concerns regarding data privacy and security are the greatest hurdles, with 48% of respondents citing them as the primary barrier to wider AI adoption. The next challenge is high implementation costs (42%), while 37% of respondents identified the lack of internal expertise as a major constraint.
The Need for End-to-End Solutions for Specific Industry Sectors
Across various industries, respondents noted that access to individual AI products is already quite high, with an average of 91% stating that AI solutions are available in their markets. However, companies still see a gap in the availability of end-to-end AI solutions designed to meet the specific needs of various industrial sectors and that can integrate seamlessly with existing systems and workflows.
Research findings show that the need for corporate support focuses on three main areas: AI solutions more tailored to the specific needs and applications of each industry (54%), the availability of more adequate talent and skills (49%), and solutions that are more accessible and affordable (45%). Companies also require more success stories of AI implementation (42%), training provided by solution providers (41%), and stronger support from boards of directors and management (32%) to drive large-scale adoption and secure internal backing.
The Importance of Local Language Support
Language is also a critical factor in expanding AI access. In several markets, such as Japan, South Korea, Indonesia, and Thailand, companies believe that the limited availability of high-quality AI models in local languages remains a barrier to AI development, even though English and Mandarin-language models are becoming increasingly available.