Alibaba Cloud has released a survey report titled \u201cThe AI Business\nApplication Readiness and Accessibility Survey,\u201d which indicates high\nenthusiasm among Asian companies regarding the adoption of Artificial\nIntelligence (AI). Approximately 90% of respondents expressed optimism\nregarding the implementation of AI within their organisations.<\/p>\n
This optimism is translating into concrete investment plans. Around\n95% of surveyed companies intend to increase their investment in AI\nproducts. More than half of the respondents plan to raise budgets by\nover 20% for Infrastructure as a Service (IaaS), Platform as a Service\n(PaaS), and Model as a Service (MaaS).<\/p>\n
As AI becomes a strategic corporate agenda, 58% of respondents plan\nto increase MaaS spending by more than 20%. Although MaaS is a\nrelatively new concept, the largest investments remain directed towards\nfundamental AI infrastructure, such as computing, data storage, and\nnetworking; 69% of respondents plan to increase IaaS spending by more\nthan 20%, followed by 61% planning similar growth in PaaS\ninvestments.<\/p>\n
Indonesia recorded the highest level of enthusiasm for AI compared to\nother surveyed countries. All respondents (100%) expressed optimism\nregarding AI implementation in their organisations. Indonesia also leads\nin cloud infrastructure adoption, with 91% of respondents stating that\ntheir IT infrastructure is fully or largely running on the cloud. For\nIndonesian companies, AI is no longer viewed merely as a tool for\nefficiency; 75% of respondents stated that driving innovation and\ncreating new business opportunities are their primary goals in adopting\nAI.<\/p>\n
Five Key Strategic Objectives for AI Adoption<\/strong><\/p>\n For the majority of respondents, AI is transitioning from the\nexperimental stage to operational implementation. Approximately 75% of\ncompanies in Asia stated that AI has become an integral part of their\nbusiness operations. Across various layers of the AI ecosystem, about\n90% of companies reported they have begun adopting both PaaS and MaaS,\nwhile only 1% stated that AI is not a priority for their\norganisation.<\/p>\n Beyond improving operational efficiency and cost savings (63%), the\nprimary strategic drivers for AI adoption are driving innovation and\nunlocking new business opportunities (64%), followed by optimising\nrevenue growth potential (48%). Gaining a competitive advantage (45%)\nand enhancing customer experience (43%) also rank among the top five\nobjectives.<\/p>\n In terms of application, companies are prioritising AI for data\nanalysis and decision-making (66%), customer services such as chatbots\n(64%), marketing and content creation (58%), product development\nincluding coding (55%), and human resources operations (38%).<\/p>\n The Need for Full-Stack Agentic AI Cloud\nSolutions<\/strong><\/p>\n The study indicates a high demand for integrated AI and Cloud\nsolutions within a unified technology suite. When selecting AI solution\nproviders, 45% of respondents prefer fully integrated AI + Cloud\nsolutions. Meanwhile, 34% prefer hybrid flexibility with models that can\nbe deployed across various clouds, and only 16% prefer standalone AI\nmodels without integrated cloud infrastructure.<\/p>\n Integrated AI + Cloud architectures are often preferred as they allow\nfor centralised management and security of data and models, simplify the\nimplementation process, and provide companies with clearer cost control\nthrough pay-as-you-go schemes. Respondents noted that integrated\ntechnology helps companies standardise data flows, implement consistent\ngovernance and security policies, and accelerate the realisation of\nbenefits from various AI initiatives.<\/p>\n Main Challenges in AI Adoption: Privacy, Cost, and Skill\nGaps<\/strong><\/p>\n Despite increasing enthusiasm and investment, companies still face\nvarious challenges in expanding AI implementation. Concerns regarding\ndata privacy and security are the greatest hurdles, with 48% of\nrespondents citing them as the primary barrier to wider AI adoption. The\nnext challenge is high implementation costs (42%), while 37% of\nrespondents identified the lack of internal expertise as a major\nconstraint.<\/p>\n The Need for End-to-End Solutions for Specific Industry\nSectors<\/strong><\/p>\n Across various industries, respondents noted that access to\nindividual AI products is already quite high, with an average of 91%\nstating that AI solutions are available in their markets. However,\ncompanies still see a gap in the availability of end-to-end AI solutions\ndesigned to meet the specific needs of various industrial sectors and\nthat can integrate seamlessly with existing systems and workflows.<\/p>\n Research findings show that the need for corporate support focuses on\nthree main areas: AI solutions more tailored to the specific needs and\napplications of each industry (54%), the availability of more adequate\ntalent and skills (49%), and solutions that are more accessible and\naffordable (45%). Companies also require more success stories of AI\nimplementation (42%), training provided by solution providers (41%), and\nstronger support from boards of directors and management (32%) to drive\nlarge-scale adoption and secure internal backing.<\/p>\n The Importance of Local Language Support<\/strong><\/p>\n Language is also a critical factor in expanding AI access. In several\nmarkets, such as Japan, South Korea, Indonesia, and Thailand, companies\nbelieve that the limited availability of high-quality AI models in local\nlanguages remains a barrier to AI development, even though English and\nMandarin-language models are becoming increasingly available.<\/p>",
"url": "https:\/\/jawawa.id\/newsitem\/alibaba-cloud-research-reveals-rapid-ai-adoption-across-asia-yet-challenges-remain-1785588663",
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