Artificial intelligence (AI) has now become a crucial instrument for business transformation in Asia. Behind the adoption of this technology lies a cost metric that determines operational effectiveness: the price per 'token'—the basic unit systems use to process information.
Recent trends show a shift in interest among business leaders in Asia, particularly in India and Southeast Asia, toward Chinese AI models such as Qwen, DeepSeek, and MiniMax. These companies are able to offer prices up to several times cheaper than major US players like OpenAI, Google, or Anthropic. This cost efficiency is made possible by leaner model architecture designs, competitive infrastructure costs, and government subsidies.
For sectors with high data transaction volumes, such as customer service, e-commerce, and software development, these low prices serve as a major attraction to reduce operational costs. However, industry experts warn that low pricing is not the sole parameter for success. AI model effectiveness must be measured by 'cost per successful outcome', given performance differences in processing local languages and complex reasoning accuracy levels.
In addition to quality issues, Asian companies face regulatory and data security challenges. Although open-source models from China allow for local data management—which is theoretically more secure—concerns regarding geopolitical tensions remain a variable seriously considered by business decision-makers.
Given these complexities, the future of the AI industry in Asia is predicted to move toward a multi-model ecosystem. Companies will likely adopt a hybrid approach: using premium Western models for critical, advanced reasoning tasks, while relying on Chinese AI models for high-volume routine tasks to achieve maximum efficiency. Ultimately, successful AI adoption will no longer be determined by the technology provider's identity, but by the value added and financial gain generated for the business.
