At HSC Ho Chi Minh, ‘Global AI Landscape: Opportunities & Lessons for Vietnam’ Debates Data Sovereignty And The Path From Pilot Projects To Production
On August 15, the HSC Conference returned to Ho Chi Minh City, gathering senior voices from enterprise capital, enterprise expertise, and software program engineering to debate synthetic intelligence adoption, knowledge sovereignty, and the way forward for agentic enterprise programs.
Among the occasion’s most anticipated classes was “Global AI Landscape: Opportunities & Lessons for Vietnam,” moderated by Harpreet Singh Maan, Chief Executive Officer at TEIZA, that includes Laura Nguyen, Partner at GenAI Fund; Harry Vu, Senior Vice President and Chief Operating Officer at SotaTek; Charlie Hu, Co-founder of OpenMax; and Trung Vu, Founder and Chief Executive Officer at Revve AI.
Rather than treating Vietnam’s AI ascent as an inevitable by-product of its deep engineering expertise pool, the panelists dissected the sensible obstacles separating technical potential from scalable deployment. They examined the place the nation’s famend developer base and coverage momentum have created real aggressive benefits, and the place fragmented enterprise knowledge, local-first product mindsets, and unquantified pilot initiatives stall adoption earlier than reaching manufacturing.
The dialog weighed the strategic rigidity between leveraging worldwide basis fashions and cultivating sovereign, open-weight options attuned to Vietnamese language and governance necessities, whereas contemplating what it should take for AI brokers to evolve from experimental chatbots into safe, bankable programs able to working inside institutional compliance frameworks.
What adopted was a candid reckoning with the sensible realities of constructing, deploying, and trusting AI inside an rising market context—starting with an sincere evaluation of the place Vietnam presently stands.
Strengths and Weaknesses of the Ecosystem
Laura launched a framework of individuals, course of, and product to guage Vietnam’s readiness. She famous that Vietnamese AI expertise is often described as one of the best in ASEAN, supported by robust entrepreneurial vitality and proactive authorities insurance policies. However, the panel agreed that the nation nonetheless lags in product improvement and international scalability. Trung, himself a Y Combinator alumnus, noticed that too many startups lack a “global-first mindset,” remaining centered on native markets reasonably than worldwide growth. The capacity to construct quickly is properly established; launching world-class merchandise stays the important problem.
The Enterprise Implementation Gap
Harry confronted a widespread false impression amongst companies: that AI is basically plug-and-play. He careworn that deploying a mannequin is often the ultimate step after cleaning fragmented knowledge, standardizing constructions, and establishing human-in-the-loop workflows. “If your knowledge is ugly, is fragmented… earlier than making use of AI, you may have lots of issues to do,” he defined. Charlie drew a pointy distinction between private prototypes and enterprise-grade options, noting that enormous organizations prioritize governance, knowledge privateness, and regulatory compliance over marginal efficiency positive aspects. “If you don’t have the correct authorized checks and safety checks, they’re not going to go together with your answer in any respect,” he said.
Sovereignty and the Model Debate
The dialogue acquired a geopolitical dimension as panelists debated Vietnam’s reliance on worldwide basis fashions. Charlie cautioned towards unconditional belief in American frontier labs, describing closed fashions as “basically nonetheless a black field.” The moderator warned of “digital colonization,” the place sustained dependence on international infrastructure may finally compromise nationwide negotiating energy. Trung proposed a practical center path: reasonably than having particular person tech giants construct separate fashions, Vietnam ought to pool assets to develop an open-weight mannequin tailored to native language and tradition. Laura framed the strategic dilemma via an educational lens of belief—functionality, benevolence, and transparency—suggesting that policymakers and entrepreneurs might rightly attain completely different conclusions.
Barriers to Scalable Adoption
Despite widespread enthusiasm, enterprises battle to advance past pilot initiatives. Laura argued that the basic impediment is quantifiable return on funding. Boards of administrators require monetary justification, not imprecise guarantees of productiveness enchancment. “At the tip of the day, how a lot cash is it bringing again to me or the group?” she requested. Trung added that enterprise workflows include unstated cultural guidelines that resist simple automation, whereas Charlie famous that many present options merely fail the rigorous safety and reliability checklists that enterprise leaders require.
Closing the session, panelists expressed measured optimism concerning the subsequent three to 5 years. Harry advocated for a unified nationwide language mannequin initiative, whereas Charlie affirmed his firm’s robust dedication to Vietnam’s digitally savvy market. Trung urged future founders to suppose globally from inception. The dialog finally portrayed Vietnam as possessing each the expertise and ambition to carve out a particular AI trajectory—offered the ecosystem efficiently closes the hole between technical functionality and enterprise-ready execution.
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