IMAGE: Thinking Machines Data Science
The race to make AI a cornerstone of business strategy in APAC just gained fresh momentum. Thinking Machines Data Science, a Southeast Asia–based AI consultancy, is collaborating with OpenAI to accelerate enterprise AI adoption across the APAC region.
Beyond the typical rhetoric of innovation, this partnership signals something more profound: the transition of AI from proof-of-concept experiments to a resilient layer of enterprise infrastructure across the region.
With the announcement, Thinking Machines becomes OpenAI’s first official services partner in APAC—a distinction that positions the firm as a bridge between global cutting-edge models and the messy realities of local enterprise adoption.
The collaboration focuses on three pillars: ChatGPT Enterprise enablement, agentic AI application development, and executive training programmes. Collectively, these aim to help leaders and organisations move from playing with AI pilots to embedding AI as a core driver of productivity and growth.
From hype to human-centred adoption
According to an IBM CEO study, 61 per cent of enterprises in APAC have already adopted AI. Yet adoption does not always translate into measurable business value. Companies frequently struggle with scaling, executive buy-in and cultural adaptation.
Stephanie Sy, founder and CEO of Thinking Machines, frames the partnership as an answer to this gap: “We’re not just bringing in new technology but helping organisations build the skills, strategies, and support systems they need to take advantage of AI. For us, it’s about reinventing the future of work through human-AI collaboration.”
This human-centric framing is not accidental. Across the region, resistance to AI is rarely technological—it’s organizational. Employees are wary of automation replacing roles, while executives face pressure to show returns on investment. By focusing on executive enablement and leadership programmes, the Thinking Machines-OpenAI partnership appears to be betting that cultural transformation is just as critical as technical transformation.
Singapore as a launchpad
Singapore is again at the heart of this regional push. Since OpenAI established its APAC headquarters in the city-state in 2024, Singapore has emerged as a natural testbed for enterprise AI strategies. With the highest per-capita ChatGPT usage rates globally, it offers fertile ground for adoption.
This initiative aligns neatly with the country’s National AI Strategy, which emphasises the integration of AI into everyday business and government functions. By extending training and services from Singapore into the Philippines and Thailand, Thinking Machines and OpenAI are also signalling that AI’s benefits must scale beyond the region’s traditional tech hubs.
Andy Brown, head of go-to-market for OpenAI in APAC, underscored the practical ambition: “This initiative with Thinking Machines will give leaders the know-how and hands-on support to embed our latest GPT-5 model into their daily operations, helping them move from experimentation to impact.”
Building “AI second brains”
One of the more intriguing concepts emerging from the collaboration is the idea of “AI second brains” for executives. Beyond jargon, this reflects a growing recognition that leaders are drowning in data, decisions and distractions. AI-powered assistants tailored to an executive’s workflows could fundamentally change how leaders prioritise, strategise and act.
Thinking Machines, which has already trained over 10,000 professionals in AI, plans to equip leaders with customized ChatGPT Enterprise deployments and Agentic AI apps. The latter are especially noteworthy. By embedding an organisation’s ‘DNA’ into AI applications via OpenAI APIs, Agentic AI moves beyond generic chatbots into domain-specific tools that reflect a company’s culture, strategy and unique operating environment.
In practical terms, this could mean AI systems that help banks assess credit risk in emerging markets, or AI copilots for manufacturers managing complex supply chains. The emphasis is not on replacing workers, but on augmenting them with AI that is contextually aware and strategically aligned.
Responsible transformation at scale
No conversation about enterprise AI is complete without addressing governance and responsibility.
Both companies have pledged to deliver frameworks for responsible AI adoption, including training on governance and ethics. This matters in APAC where regulatory landscapes vary widely, from Singapore’s proactive stance to more fragmented approaches elsewhere.
Through co-published white papers, executive roundtables and industry forums, the collaboration also aims to generate thought leadership tailored to APAC’s cultural and linguistic diversity. The implication is clear: AI adoption cannot be a copy-paste import of Western models. It must adapt to the unique dynamics of Asian markets.
What this means for APAC’s AI race
For enterprises in APAC, this collaboration is both a challenge and an opportunity. The challenge lies in the steep learning curve: many organisations have dabbled in pilots but lack the frameworks to scale AI responsibly and profitably. The opportunity lies in accessing structured programmes that combine world-class models with local expertise.
Thinking Machines’ track record across sectors—finance, telecommunications and development organisations—suggests it is well positioned to guide this journey. OpenAI’s global leadership in generative models provides the technological backbone. Together, they aim to make AI adoption less about chasing hype and more about building resilient, future-ready systems.
As AI accelerates from experimentation to execution, APAC enterprises are at a crossroads. Those who lean into partnerships like this may not just adopt AI. They may also reinvent the very architecture of their organisations for the decades ahead.
