Businesses are supposed to harness AI's capabilities to maintain a competitive edge

Labor productivity is an important factor in determining the competitiveness and prosperity of an economy. Looking back nearly 40 years, Vietnam's household contracting system (Contract 10) played an important role in boosting agricultural productivity, transforming the country from one struggling with food shortages into one of the world’s leading rice exporters. However, today, labor productivity remains a challenge in managing the economy. According to ASEAN statistics, in 2023, Vietnam's labor productivity was only 7.6% of that of Singapore, 19.5% of Malaysia, 37.9% of Thailand, 45.6% of Indonesia, and 56.9% of the Philippines. It was only higher than Cambodia’s labor productivity by a factor of 1.6 times. This stark disparity highlights one of the biggest challenges Vietnam faces as it strives for continued growth and development.

Resolution 57-NQ/TW, issued by the Politburo on December 22, 2024, outlines a clear vision for advancing science, technology, innovation, and national digital transformation. It emphasizes the importance of fostering scientific research cooperation and technology development with countries at the forefront of science and technology, particularly in digital transformation and fields like AI. In line with this vision, Vietnam’s government has recently signed an agreement with NVIDIA, one of the world’s leading technology corporations, to establish an AI R&D center and an AI Data Center, paying the way for the country to become a leading hub for AI research and development in Asia.

As AI continues to transform work processes across all sectors, its positive impact is becoming increasingly evident. Both individuals and organizations will increasingly look to leverage AI’s capabilities to gain a competitive edge. However, successful AI implementation requires careful planning and a structured approach to avoid common drawbacks and ensure sustainable outcomes. AI spans a wide range of applications, from AI-powered chatbots like ChatGPT to robots and predictive analytics, and it continues evolving. While there is no one-size-fits-all solution, it is possible to identify effective strategies. According to digital technology experts, for the AI industry to grow strongly and sustainably, it is important to implement positive solutions at both the government and enterprise levels.

The role of the government

The government should focus on building AI ecosystems in provinces and cities by fostering the growth of the IT industry and domestic AI companies. This includes promoting partnerships with leading international technology companies such as OpenAI, Google, Meta, Nvidia and Deepseek, while also accelerating AI adoption within the government to more effectively manage economic resources, minimize waste and avoid negative outcomes. In the first phase, the government should prioritize well-managed social resources, including institutions and macro-management environments, to streamline operations. Additionally, there should be an effort to link the AI sector with the semiconductor industry and other key economic sectors.

It is also important to develop digital infrastructure platforms that support strong broadband, data storage capabilities and digital skills, together with nurturing AI human resource capabilities. This should range from basic digital literacy to advanced AI research, ensuring that new skills are integrated into school curricula and professional training programs. Furthermore, promoting an AI innovation culture will help encourage societal acceptance of change, foster new ideas and support widespread AI adoption. Creating such a culture begins with leadership that values democracy, freedom and openness at all levels of government to inspire innovation and creativity. By articulating a clear vision for AI’s role, leaders can promote innovative thinking.

Adopting this culture of innovation will allow for the development of a high-quality, adaptable workforce that is prepared to embrace AI in the future. Moreover, the government must establish AI governance frameworks to manage associated risks and build a responsible ethical framework based on principles such as fairness, accountability and transparency.

The engagement of enterprises

Setting clear objectives is important to the successful implementation of AI. The first step involves identifying problems or opportunities that digital transformation can address. Once these issues are identified, companies can convert them into specific objectives. A purposeful and structured approach ensures that the AI solution remains focused, with clear endpoints for evaluation, and that the implementation of AI models aligns with overall business goals.

Assessing data quality and selecting appropriate AI technology is another key step. Since the effectiveness of AI outcomes is heavily dependent on input data, evaluating the quality and accessibility of this data is necessary. Data quality should be assessed based on several criteria, such as accuracy, completeness, consistency and relevance to the business problem. Furthermore, data should represent real-world situations that the AI model is likely to encounter, preventing biased or limited predictions. It is also important for AI systems to have proper access to this data. Once data quality is confirmed, businesses must determine the AI model structure and methodology that best fits their strategy. In addition to model selection, organizations must also consider the infrastructure and platforms that will support the AI system.

Building an AI-proficient team is important for handling the complexities of AI development, deployment and maintenance. The team should include a range of specialized roles, such as data scientists, hardware engineers and software developers, each with expertise in their respective fields. A well-rounded team not only ensures effective AI implementation but also fosters internal capacity for continuous innovation and adaptation in AI.

Testing and evaluating AI models are important steps to ensure they are accurate, reliable and capable of delivering value in real-world scenarios. Given that the real-world environment is dynamic, with data patterns and business needs to be constantly developed, AI models may experience performance fluctuations. A combination of thorough testing and ongoing evaluation will help ensure that the AI system continues to meet job demands and adapt to changing conditions.

Planning for scalability and continuous improvement is important for the long-term success of AI projects. As data volumes, users or processes increase, the system must be able to handle the growing demand without compromising performance. To plan for scalability, organizations should choose infrastructure and frameworks that support expansion, such as cloud services, distributed computing or modular architecture.

In summary, AI will play a central role in a volatile world that is both cooperative and competitive. AI serves as a powerful tool, a strategic asset, and a key driver of competitive capacity development among economies entering the era of the emerging Industry 5.0. In this context, the economy will develop through close collaboration between humans and machines. By working alongside "robot colleagues," individuals and organizations can focus on creativity and experimentation, maximizing their potential. Building on the foundations of Industry 4.0 and Industry 5.0, this approach will make the country more adaptable, productive, and ultimately enable Vietnam to achieve its full development potential.