A survey report entitled “The AI Business Application Readiness and Accessibility Survey” commissioned by Alibaba Cloud, a leading global provider of AI infrastructure and the intelligence backbone of Alibaba Group, announced near-universal enthusiasm for AI among Asian enterprises.
The momentum is particularly evident in Malaysia, where 92% of organisations expressed confidence in AI adoption, including 60% already exploring or implementing AI initiatives. Notably, Malaysia emerged as the only market in the study where 100% of respondents indicated plans to increase AI investments, underscoring the country’s strong commitment to AI-driven business transformation. This commitment is reflected in spending plans, with 97% intending to increase investment in AI infrastructure (IaaS), alongside more than 90% planning further investment in AI platforms (PaaS) and model services (MaaS).
Top Five Strategic Objectives of AI Adoption
AI is already moving from the pilot stage to production for a significant share of respondents. Around 75% Asian companies say AI has become indispensable to their business operations. Across the stack, approximately 90% of companies report they have started adopting AI development tools (PaaS) and models (MaaS). Notably, only 1% of all respondents say AI is not a priority.
Moving beyond simply achieving cost savings and efficiency (63%), the top strategic objectives reported for AI adoption include driving innovation and new business opportunities (64%), followed by unlocking revenue growth potential (48%). Gaining competitive advantage (45%) and improving customer experience (43%) are also among the top five objectives.
Functionally, enterprises are prioritising data analysis and decision-making (66%), customer service tools such as chatbots (64%), marketing and content creation (58%), product development including coding (55%), and HR operations (38%).
In Malaysia, customer service has emerged as one of the leading AI use cases, with 72% of organisations identifying AI-powered customer service applications, such as chatbots, as a key use case. Improving customer experience also ranks higher locally, with 53% citing it as a key objective for AI adoption.
The Need for A Full-Stack Agentic Cloud
The study underscores strong demand for integrated AI and Cloud solutions delivered via a single, coherent stack. When selecting AI solution providers, 45% of respondents prefer fully integrated AI + Cloud offerings, compared with 34% who favour hybrid flexibility with models deployable across multiple clouds, and only 16% who prefer standalone AI models without bundled cloud infrastructure.
Integrated AI + Cloud architectures often appeal because they centralise management and security for data and models, simplify deployment, and give enterprises clearer control over cost via pay-as-you-go models. Respondents highlight that integrated stacks help them standardise data pipelines, apply consistent governance and security policies, and accelerate time-to-value for AI initiatives.
Barriers: Privacy, Cost and Skills Gaps
Despite strong enthusiasm and investment, organisations face material barriers to scaling AI. Respondents rate data privacy and security concerns as the top challenge, cited by 48% as a leading obstacle to broader adoption. High implementation costs followed (42%), while 37% point to a lack of internal expertise as a major constraint.
Regulatory and ethical concerns are another significant friction point, mentioned by 31% of respondents overall, with this figure rising sharply in more regulated sectors such as financial services, education and the public sector. Additional barriers include integration challenges (28%), the limited accessibility of suitable solutions (23%), an unclear return on investment (22%), a lack of obvious business cases (19%) and resistance from management-level executives (18%).
Demand for Sector-Specific, End-to-End Solutions
Across industries, respondents report high levels of accessibility to individual AI products — on average, 91% say AI solutions are available in their markets. However, they identify a gap when it comes to comprehensive, end-to-end solutions that address sector-specific scenarios and integrate seamlessly into existing systems and workflows.
The research found that support needs cluster around three themes: more customised AI solutions tailored to industry use cases (54%), better availability of talent and skills (49%), and more accessible, affordable offerings (45%). Enterprises also call for successful case studies (42%), vendor-provided training (41%) and stronger board and management endorsement (32%) to unlock large-scale deployments and secure internal sponsorship.
Importance of Local Language Support
Language also emerges as a critical success factor for AI accessibility. In markets such as Japan, South Korea, Indonesia and Thailand, enterprises report that the scarcity of high-quality local-language models is holding back development, even as English- and Chinese-language models proliferate.
Survey data show that only around half of respondents select English as their primary language for AI solutions, with the rest choosing Bahasa, Japanese, Korean, Thai and other local languages. Products that natively support multiple Asian languages are therefore winning market share, with Alibaba Cloud’s Qwen models cited as especially popular in Japan and South Korea due to their strong performance in local languages and support for over 200 languages and dialects in Qwen’s latest generation. As a multilingual market, Malaysia also stands to benefit from AI models that support multiple languages, enabling organisations to better serve diverse customers and workforces. As a multilingual market, Malaysia also stands to benefit from AI models that support multiple languages, enabling organisations to better serve diverse customers and workforces.
Alibaba Cloud’s Role as Full-Stack AI Partner
The report positions these findings within Alibaba Cloud’s broader AI + Cloud strategy and investment roadmap. Alibaba Group announced plans to invest at least RMB380 billion (approximately USD53 billion) over three years to expand cloud computing and AI infrastructure, an amount that exceeds its AI and cloud spending over the previous decade. The company offers full-stack capabilities from foundational infrastructure to platforms and self-developed models, including the Qwen language family and Wan image and video generation models.
Implications for Global Business Leaders
For international enterprises evaluating AI strategies in Asia and beyond, the study offers three key signals.
AI demand is moving quickly from curiosity to commitment, with budgets, roadmaps and early production use cases already in place across a wide range of industries.
Successful adoption will depend on trusted, integrated AI + Cloud partners that can deliver secure, sector-specific, end-to-end solutions while helping clients navigate privacy, regulatory and talent challenges.
Open, multi-lingual ecosystems — combining strong local language support with robust governance, tools and training — will be critical to unlocking AI’s full value for a range of workforces and customer bases.
Dr. Feifei Li, Chief Technology Officer and President of International Business, Alibaba Cloud Intelligence Group
The research findings reinforce Alibaba Cloud’s belief that AI, delivered on top of scalable, secure cloud infrastructure and models, will be the defining technology platform for the next decade. As we enter the agentic AI era, our focus is shifting from producing efficient tokens to enabling actionable outcomes. By building a comprehensive agentic cloud, we provide the critical infrastructure — such as runtime sandboxes and orchestration — that empowers enterprises to seamlessly build the agent-native products of tomorrow.
