BUV Cooperates with the HCMC Investment and Trade Promotion Centre to Promote the Application of AI in Manufacturing

On the afternoon of 16 December 2025, the Ho Chi Minh City Investment and Trade Promotion Centre (ITPC), in collaboration with the British University Vietnam (BUV), organised the workshop “AI Applications: Optimising Manufacturing Processes.”

The workshop aimed to create a specialised forum for in-depth exchange, supporting manufacturing enterprises in updating emerging technology trends and identifying appropriate roadmaps for applying artificial intelligence (AI) in the context of digital transformation and the development of smart factories.

The event attracted approximately 250 delegates, including representatives from state management agencies, manufacturing enterprises, technology experts, universities, and media organisations.

AI – A Foundational Technology for Smart Manufacturing

The workshop was held against the backdrop of Ho Chi Minh City expanding its development space and forming a multi-centred megacity, opening up new opportunities for industry, logistics, smart urban development, and innovation. Within the modern manufacturing ecosystem, AI has been identified as a foundational technology, playing a critical role in improving productivity, optimising operations, and enhancing the competitiveness of enterprises.

Speaking at the workshop, Ms. Cao Thi Phi Van, Deputy Director of the Ho Chi Minh City Investment and Trade Promotion Centre (ITPC), emphasised:
“AI is opening up entirely new operating models for manufacturing enterprises, from supply chain management and production planning to energy optimisation and quality control. The application of AI will be the key to helping enterprises improve productivity and competitiveness in the coming period.”

Ms. Cao Thi Phi Van, Deputy Director of the Ho Chi Minh City Investment and Trade Promotion Centre (ITPC), delivering her remarks at the conference

Discussions highlighted that AI is increasingly being applied in production planning and scheduling, predictive maintenance, quality control through computer vision, energy consumption optimisation, and process automation. The smart factory model is becoming an inevitable trend in the global manufacturing industry.

Policy Orientation and Implementation Context

Promoting the application of AI in manufacturing aligns with the Politburo’s Resolution No. 57-NQ/TW on breakthroughs in science, technology, innovation, and national digital transformation, as well as the Government’s action programmes to support enterprises in technological innovation and the development of smart and sustainable manufacturing models.

Participants also agreed that AI deployment must be aligned with each enterprise’s level of readiness, ensuring investment efficiency, avoiding fragmented or unstructured implementation, and paying due attention to human factors and management capabilities.

Practical Perspectives from Industry and Academia

Sharing insights from the education and research perspective, Professor Rick Bennett, Deputy Vice-Chancellor and Vice President of BUV, stated: “For manufacturing enterprises today, the question is no longer whether to apply AI, but how to deploy AI effectively, responsibly, and in a way that matches the resources and readiness of each organisation.”

Professor Rick Bennett, Deputy Vice-Chancellor and Vice President of BUV, at the conference

From a technical standpoint, Associate Professor Ali Al-Dulaimi, Head of the School of Computing & Innovative Technologies at BUV, commented: “AI only delivers real impact when it is implemented according to a roadmap that matches an enterprise’s readiness, starting with specific problems supported by clear data and generating measurable value in the short term.”

According to experts, AI can only create sustainable value when it is deployed in an integrated manner across three pillars—people, processes, and technology—where leadership capability, change management, and workforce training play a decisive role.

Expectations and Future Directions

Within the framework of the Memorandum of Understanding (MoU) signed between ITPC, the Saigon Hi-Tech Park Management Board (SHTP), and BUV, BUV will continue to actively participate and work alongside the City in workshops, training programmes, and knowledge transfer initiatives, with the goal of enhancing the quality of high-tech human resources.

The cooperation focuses on developing and delivering high-tech skills training programmes that meet the practical needs of enterprises in key areas such as artificial intelligence (AI), data, automation, smart manufacturing, and digital transformation. These efforts aim to help build a workforce with strong professional competence, global mindset, and the ability to adapt quickly to technological change.

Expert, Associate Professor Ali Al-Dulaimi, Head of the School of Computing & Innovative Technologies at BUV, delivering his remarks at the conference

Currently, BUV is working closely with Ho Chi Minh City and domestic and international partners—particularly leading universities worldwide—to soon roll out high-quality high-tech skills training programmes in Ho Chi Minh City in particular and Vietnam in general. These programmes are designed in line with international standards and closely aligned with enterprise needs and the City’s long-term development strategy.

Through these collaborative initiatives, BUV reaffirms its commitment to accompanying Ho Chi Minh City in realising its vision of becoming a national hub for economic, financial, and technological development, making practical contributions to improving human resource quality, fostering innovation, and promoting sustainable development.

Through the workshop, ITPC also expects to continue strengthening its role as a bridge connecting enterprises with experts, universities, technology organisations, and domestic and international partners, while supporting businesses in accessing suitable AI solutions to optimise manufacturing processes, enhance competitiveness, and achieve sustainable growth in the new context.