AI Agents in Vietnam’s Software Industry: Early Signs and Real Limits

Over the past two years, many Vietnamese software companies have added AI features such as chatbots and coding assistants to their services. Some are now starting to build AI agents that can plan steps and act within business systems. This article examines how AI agents in Vietnam’s software industry are developing, what the evidence shows so far, and where the limits lie.

1. What AI integration has meant so far

For most companies, AI integration meant connecting a language model to an existing product. Typical examples are a support chatbot, a tool that searches internal documents, or a code assistant. The model produces an answer or a draft, and a person decides what to do with it.

This work is still in demand, and companies do not simply leave it behind. It needs clean data, stable APIs, and a security review, which are the same foundations that agents depend on. In that sense, integration is the starting point for agents rather than a separate stage.

2. What changes with agents

An AI agent goes one step further. Given a goal, it chooses its own steps, calls other tools, and can finish a task, such as checking an order, updating a record, and sending a confirmation email. This is why many teams treat agents as part of AI workflow development, where the model, the tools, and the approval steps are designed together. Because the system acts instead of only answering, the engineering work changes in a few ways:

• Permissions: the agent should only read and change what the task requires.
• Testing: results need to be checked on realistic cases, not only a few demos.
• Human review: some actions, such as refunds or deletions, should need approval.
• Monitoring: errors, costs, and unusual behavior have to be tracked after launch.

These tasks look more like ordinary software engineering than research, which suggests that companies with strong delivery habits have an advantage.

 

3. Signs of change in Vietnam

Some technology providers offer platforms for designing, deploying, and managing AI agents, while others focus on AI application development and workflow automation. Industry assessments have also recognized providers for their AI application development capabilities. However, product announcements and industry rankings do not necessarily demonstrate real-world adoption or measurable business outcomes.

AI agent providers vary in their delivery models. Some offer proprietary platforms, while others build and integrate agents into clients’ existing applications, data environments, and workflows. The right approach depends on a company’s technical requirements, integration needs, security constraints, and long-term ownership objectives.

Smaller firms mostly work project by project, building agents on top of a client’s own systems. PowerGate Software, founded in Hanoi in 2011 and certified to ISO 9001 and ISO 27001, lists AI agents and workflow automation among its services, next to web and mobile development. The company says it combines a strong product mindset with experts from the UK, Australia and the US, working together with local experts in Vietnam.

4. The limits of the current picture

The picture is still early. Most of the evidence comes from large groups and from the companies’ own materials, and there is little independent data on how many Vietnamese firms run agents in production.

A survey by FPT and Forrester gives some context. It found that AI agents carry out 17 percent of core processes on average, and that this share is expected to reach 39 percent within two years. However, only 23 percent of organizations had achieved enterprise-wide AI integration and scaling, and the main barriers were integration complexity (41 percent) and data readiness (38 percent). The survey covers enterprises across Asia-Pacific, not Vietnam alone, but the same barriers are likely to apply here.

Talent is another limit. Market outlooks describe a shortage of senior AI engineers in Vietnam, so experienced people are not easy to find.

 

5. What this means for businesses

For companies choosing a development partner, the early stage is a reason to ask practical questions instead of relying on labels. Useful checks include:

• examples of agents that run in production, and the type of task they handle
• how the team tests results and deals with wrong or unsafe outputs
• how permissions and human approval are set up
• who monitors the system after launch

Starting with a small pilot also lets both sides check communication and quality before a larger commitment.

AI agents in Vietnam’s software industry are still at an early stage, led by large groups and followed by mid-size studios. The direction is clear, but real progress depends on data, integration, and governance, which many organizations are still building. For buyers and developers alike, the sensible path is to start small, measure results, and expand only when the agent proves reliable.