Thinking Machines Partners with OpenAI to Enhance AI Services in Asia-Pacific

Thinking Machines Data Science has announced its partnership with OpenAI to deliver AI services to businesses in the Asia-Pacific region, becoming the first official OpenAI service partner in the area. This collaboration aims to transform AI usage into measurable outcomes by offering executive training on ChatGPT Enterprise, supporting the development of custom applications, and guiding the integration of AI into daily operations.

Enhancing AI Capabilities in Organizations

According to Stephanie Sy, founder and director of Thinking Machines, the biggest challenge for companies is adopting AI correctly. It is often viewed merely as a technological acquisition rather than a business transformation, leading to pilot projects that fail to scale. Sy emphasizes the importance of having a clear vision, redesigning processes for integration, and investing in workforce skills to achieve success.

Sy believes that leadership should be at the core of AI adoption, with executives setting goals, assessing risks, and clarifying responsibilities to ensure successful AI applications.

Human-AI Collaboration

Thinking Machines emphasizes the concept of “humans in the lead,” where humans focus on judgment and decision-making, while AI handles routine tasks such as retrieval and summarization. This collaboration improves quality and saves time, with studies showing that AI can increase employee productivity by up to 14%.

Through workshops offered by Thinking Machines, professionals can free up one to two hours daily using ChatGPT, enhancing human-machine collaboration.

Reliable AI Governance

Thinking Machines also focuses on the concept of agent AI, which can execute multi-step processes and coordinate various tasks while maintaining the human role in leadership. The organization ensures that systems are traceable, reversible, and compliant with approved policies before wide-scale deployment.

Good governance accelerates AI adoption, as trust is built through the application of controls and transparency.

Cultural and Linguistic Challenges in Asia-Pacific

Given the significant cultural and linguistic diversity in the Asia-Pacific region, companies face unique challenges in adopting AI. Thinking Machines advocates for building models locally first and then expanding thoughtfully, ensuring alignment with local language and policies.

With experience in Singapore, the Philippines, and Thailand, Thinking Machines demonstrates AI’s value with local teams before expanding to other regions.

Conclusion

In collaboration with OpenAI, Thinking Machines aims to turn AI from mere experiments into tangible results across Asia-Pacific. By focusing on building local capabilities, providing appropriate training, and ensuring good governance, companies can achieve long-term value from AI. Vision, processes, and skills remain key to success in this growing field.