Implementing AI in Vietnamese Enterprises: Opportunities, Challenges, and the Right Path Forward

Artificial Intelligence (AI) has become a buzzword in the modern business world, often seen as a “magic wand” that can help companies accelerate digital transformation, optimize operations, and make smarter decisions. But the real question is: Is AI truly a must-have miracle tool for every business?

1. The Current State of AI Adoption in Vietnam

According to a 2024 VCCI report, only about 12% of Vietnamese enterprises are currently applying AI in their operations, mostly within finance, e-commerce, and manufacturing sectors. However, just 37% of those reported clear improvements in productivity or revenue as a result.

Research from the Ministry of Information and Communications (MIC) and Boston Consulting Group also revealed that nearly 70% of businesses are either experimenting with AI or still lack a defined AI strategy. The primary barriers include poor data standardization, weak infrastructure, and a shortage of AI-skilled talent.

2. Levels of Technology Adoption in Vietnamese Enterprises

To better understand the journey toward AI, we can categorize enterprises into different stages of technology adoption:

• Level 1: Manual operations, paper-based processes.
• Level 2: Use of basic tools like Word and Excel.
• Level 3: Implementation of management software such as ERP or CRM.
• Level 4: Semi-automated workflows integrated with software systems.
• Level 5: Well-developed process automation.
• Level 6: AI applied in data analytics and decision support.
• Level 7: AI Automation and AI Agents interacting directly with employees and customers.

Most Vietnamese enterprises remain at Levels 3–4, and only about 5–7% have reached Level 6 or beyond.

3. Key Challenges in Implementing AI

Adopting AI isn’t just about installing software or integrating ChatGPT. The biggest obstacles usually come from:

• Mindset: Many business leaders still view AI as expensive or unnecessary for small-scale operations.
• People: A lack of data and AI expertise within the organization.
• Cost-Benefit Balance: High upfront investment with unclear short-term ROI.
• Technology Limitations: AI is not omnipotent — poor data leads to poor outcomes.

4. AI Implementation – Not Everything Needs AI

While AI is powerful, applying it indiscriminately can backfire. The core principle is automation thinking — understanding the problem, defining goals, and selecting suitable tools. Sometimes, simpler solutions like RPA (Robotic Process Automation) or Power Automate are sufficient to drive real efficiency.

💡 Tip: Start by identifying real pain points, build a solid digital foundation and data system, then gradually introduce AI into analytics and decision-making stages.

5. Conclusion

AI should not be viewed as an end goal but as a means to achieve automation and intelligent decision-making. To truly harness the “magic wand,” businesses must first establish strong foundations and take a step-by-step approach. Sometimes, the right spell matters more than the wand itself.

This article is intended for business leaders and managers who seek a realistic and practical perspective on implementing AI effectively.