In a groundbreaking partnership, Thinking Machines Data Science has become OpenAI’s first official Services Partner in the Asia-Pacific (APAC) region. This collaboration is uniquely positioned to help organizations transform AI from theoretical involvement to operational value, combining strategic training, agentic AI app development, and governance with OpenAI’s cutting-edge technology.
Why This Partnership Matters
AI adoption in APAC is increasing rapidly—but many organizations struggle to transition from experimental AI pilots to scalable business solutions. According to an IBM study, while 61% of APAC enterprises have adopted AI, only a fraction report delivering measurable results.
By naming Thinking Machines as its official Services Partner for APAC, OpenAI ensures that their advanced GPT technology is grounded in expertise, strategy, and real operational frameworks. This addresses a critical need: translating AI promise into tangible business outcomes.
Thinking Machines & OpenAI: What’s in It?
The collaboration offers three strategic pillars:
- Executive Enablement: Training programs tailored for C-suite and senior managers to understand and govern AI as a strategic asset, not just a technical feature.
- Transformational Services: Design, integration, and rollout of bespoke Agentic AI applications, leveraging OpenAI APIs to embed AI into workflows with built-in human oversight.
- Thought Leadership & Regional Engagement: Co-publication of white papers, hosting industry roundtables, and scaling in focal countries—starting with Singapore, the Philippines, and Thailand.
The APAC Enterprise Adoption Gap
The starting point for this collaboration is a prevailing challenge: enterprises can pilot AI, but few scale.
Stephanie Sy, founder and CEO of Thinking Machines, highlights three critical enablers that most pilots ignore:
- Leadership Alignment on clear business outcomes.
- Workflow Redesign to embed AI in everyday processes.
- Workforce Capability Building to ensure real adoption.
These insights form the structure of joint Thinking Machines–OpenAI offerings.
Capability Building: Vision, Process, People
Leadership Alignment: Executive sessions help boards define if AI is a strategic growth engine or a managed risk—driving accountability, risk appetite, and ownership across the organization.
Process Redesign: By redesigning workflow so that AI handles routine tasks (e.g., drafting or retrieval) and humans focus on judgment and exceptions, organizations can realize measurable efficiency gains.
Capability Development: Brief, practice-oriented levels of Handle starting – such as that of Thinking Machines – “Second Brain, Real Results” that concentrate on right away mastering the ability to evaluate AI answers, and envision crafting dependable AI. Over 10,000 professionals in APAC have already benefited.
Human-in-Command & the Rise of Agentic AI
Thinking Machines champions a “human-in-command” paradigm: AI handles retrieval, drafting, summarizing; humans maintain decision authority, backed by audit trails and provenance.
They also lead in Agentic AI, where systems go beyond single queries to orchestrate complex workflows—research, form filling, API calls—while preserving transparency and human oversight.
This combination promises speed plus trust—fundamental for enterprise scale.
Governance and Trust as Adoption Accelerators
Governance cannot be afterthought; it must be embedded in workflows.
Thinking Machines emphasizes:
- Visible governance: approved data sources, role-based access, audit logs.
- Reliability: answers come with citations; retrieval restricted to trusted content.
- Policy alignment and compliance, especially in regulated sectors like finance and healthcare.
Success metrics focus on traceability and exception rates—not just policy coverage.
Scaling Regionally, Rooted Locally
APAC is diverse—culturally, linguistically, operationally. Thinking Machines adopts a “build local, scale deliberately” strategy:
- Local-first pilots: Singapore, Philippines, Thailand serve as testbeds.
- Tailored adaptation: AI customized to each locale’s language, processes, and governance.
- Unified frameworks: scalable templates for governance, connectors, and metrics.
This dual model ensures depth and scale.
Executive Fluency: Skills Over Tools
Sy argues that tools matter less than skills. Thinking Machines focuses training on:
- Executive literacy: enabling leaders to define outcomes, guardrails, and scale decisions.
- Workflow design: clarifying handoff between humans and AI.
- Hands-on competency: prompting, verifying, crafting reliable retrieval.
After just one workshop, many professionals report 1–2 hours saved per day—a compelling ROI.
Real-World Impact and Case Studies
A standout example is BEAi—a retrieval-augmented generation system built with the Bank of the Philippine Islands. It supports English, Filipino, and Taglish, links responses to policy pages, and understands supersession for policy compliance. This system was able to translate complex governance documents into more everyday guidance for staff – AI – native in practice.
Conclusion: A Blueprint for AI-Driven Transformation
Through this partnership, Thinking Machines and OpenAI are delivering more than AI tools—they’ve crafted a practical blueprint for enterprise-scale AI adoption in APAC:
- Strategic alignment at executive level
- Workflow redesign for human-AI collaboration
- Governance built into every step
- Skills-first approach for sustainable adoption
- Pilot locally, scale regionally
The goal is clear: transforming AI from buzz to business engine—with human oversight and measurable impact.
FAQs
What is the Thinking Machines-OpenAI partnership?
It’s a collaboration to help APAC businesses scale AI through executive training, custom applications, and governance frameworks, with Thinking Machines as OpenAI’s first Services Partner in the region.
How does Thinking Machines ensure AI governance?
They integrate governance into daily workflows with approved data sources, audit trails, and human decision points, ensuring compliance and trust.
What is human-in-command AI?
It’s an approach where AI handles routine tasks like drafting or retrieval, while humans focus on judgment and exceptions, supported by transparent audit trails.
Which industries will benefit most from this partnership?
Finance, retail, and manufacturing are key focus areas, with tailored solutions for compliance, customer experience, and supply chain optimization.
