Amid the wave of digital transformation, many Vietnamese enterprises have moved beyond basic automation and started integrating AI into their operations. However, a new paradigm is emerging—where systems no longer just assist humans but can analyze, decide, and act independently. This is what we call Agentic Automation.
In a context where Vietnam is experiencing rapid growth while facing pressure on workforce and productivity, Agentic Automation is no longer a distant trend—it is becoming a strategic solution.
Table of Contents
What is Agentic Automation?
Agentic Automation can be understood as an advanced stage of automation, where AI systems are capable of operating autonomously end-to-end, rather than executing isolated tasks.
Instead of waiting for human instructions, AI agents can:
- Analyze data independently
- Make decisions
- Execute appropriate actions
A quick comparison of automation levels:
- Traditional Automation: rule-based (if-this-then-that)
- AI Automation: capable of analysis but still human-guided
- Agentic Automation: fully autonomous, end-to-end execution
Example:
In an e-commerce business, instead of staff manually monitoring inventory, adjusting prices, and running campaigns, an AI agent can:
- Analyze sales data in real time
- Automatically adjust product pricing
- Launch and optimize marketing campaigns
- Continuously improve based on market feedback
Why Agentic Automation is Highly Relevant for Vietnam
Fragmented business structure dominated by SMEs
Most Vietnamese companies are SMEs with limited resources and suboptimal processes. Scaling manually is inefficient. Agentic Automation enables them to scale operations without proportionally increasing headcount.
Rapid growth but shortage of high-quality talent
Vietnam’s economy is growing fast, but skilled talent is not keeping up. AI agents can act as a “capability layer,” helping businesses maintain performance without relying solely on hiring.
A rapidly expanding digital ecosystem
The growth of fintech, e-commerce, logistics, and SaaS is generating massive amounts of data—ideal “fuel” for Agentic Automation, where more data leads to better decision-making.
Increasing digital readiness
Many businesses are already familiar with CRM, ERP, and automation tools, making the transition to Agentic Automation more natural rather than disruptive.
Application Potential Across Industries in Vietnam
As AI adoption accelerates in Vietnam, Agentic Automation is unlocking a new phase—moving from task automation to full operational automation. With AI growing at ~39% annually and around 18% of businesses already adopting AI, the potential is significant.
Financial Services & Banking: Leading the shift toward intelligent automation
The financial sector is among the most ready for Agentic Automation adoption. Currently, around 70% of financial institutions in Vietnam have implemented AI in functions such as customer service, marketing, and IT.
Agentic Automation can elevate these systems to a new level by enabling:
- End-to-end automated credit processing (from data collection to approval)
- Real-time fraud detection with continuous self-learning capabilities
- Personalized financial agents that proactively advise customers
→ This is likely the fastest industry to transition from “AI-assisted” to “AI-operated” models.
Manufacturing & Industry: Toward end-to-end operational optimization
As a regional manufacturing hub, Vietnam is well-positioned to leverage Agentic Automation in:
- Predictive maintenance
- Supply chain optimization
- Real-time production orchestration
Agentic AI can continuously analyze machine data, predict failures, and automatically trigger maintenance workflows, reducing human dependency. More importantly, it enables a shift from isolated automation (at the production line level) to system-wide self-optimization across the entire factory.
E-commerce & Retail: Personalization at scale
With the rapid growth of e-commerce in Vietnam, Agentic Automation can:
- Dynamically manage inventory and pricing based on real-time demand
- Create and optimize marketing campaigns autonomously
- Operate omnichannel customer service agents (chat, email, social media)
The key difference is that agents do not just respond—they proactively recommend actions such as upselling, cross-selling, and retention strategies. This directly drives revenue growth, as already observed by many AI-adopting businesses in Vietnam.
Logistics & Supply Chain: Real-time decision-making at scale
Agentic Automation is particularly suited for complex systems like logistics, where decisions must be made continuously and dynamically:
- Automated route optimization
- Supply chain disruption prediction
- Continuous cost optimization based on real-time data
Multi-agent systems can coordinate across the entire value chain—from warehousing to transportation to last-mile delivery—replacing fragmented systems with a unified, intelligent network.
Education: Personalizing learning experiences
Early implementations in Vietnam have already shown promising results. For example, multi-agent systems used in admission consulting have achieved accuracy rates of up to 92%.
In the future, Agentic Automation can:
- Build fully personalized learning pathways
- Track student progress and automatically adjust content
- Support educational operations (admissions, administration, student services)
→ While still in early stages, this sector holds strong long-term potential.
IT & Business Services: Automating knowledge work
Agentic Automation is especially impactful in knowledge-intensive tasks:
- AI coding agents for software development
- Automated project management and task allocation
- Data analysis and business decision-making
It is projected that up to 70% of office work could be handled by agentic AI within the next decade, highlighting massive potential in service-based industries.
Public Sector: Enhancing governance and service delivery
In the context of national digital transformation, Agentic Automation can:
- Automate administrative processes
- Support policy decision-making through data analysis
- Deliver 24/7 intelligent public services
This helps reduce administrative burden while improving citizen experience and service accessibility.
Challenges of Implementing Agentic Automation in Vietnam
Despite its strong potential, Agentic Automation in Vietnam still faces several practical barriers.
Data infrastructure is not yet ready
Data remains fragmented, unstandardized, and siloed across systems, making it difficult for AI to generate accurate insights and for agents to coordinate effectively.
Talent gap in agentic system design
Beyond AI engineers, there is a shortage of professionals who understand how to design multi-agent systems aligned with real business problems—a relatively new capability in Vietnam.
Concerns over control and governance
Many organizations are hesitant to allow systems to make autonomous decisions, especially in the absence of clear governance frameworks for risk control, accountability, and transparency.
High initial investment costs
From data infrastructure to system integration, implementation requires significant upfront investment—posing challenges, particularly for SMEs.
Organizational mindset not fully ready
Many businesses are still comfortable with traditional operations or basic automation, and are not yet ready to “delegate authority” to autonomous systems.
How Vietnamese Enterprises Should Prepare
To successfully implement Agentic Automation, businesses should not start with technology—but with a strong foundation.
Standardize and centralize data
Data is the backbone of any agentic system. Companies must invest in cleaning, standardizing, and consolidating data into unified platforms such as data warehouses or data lakes. Establishing data governance and quality standards ensures a single source of truth, improving decision accuracy.
Start with small, high-ROI use cases
Instead of large-scale deployment, businesses should begin with clearly measurable use cases, such as customer service automation, order processing optimization, or business analytics support. These quick wins help validate value and build momentum.
Adopt a human-in-the-loop approach
In early stages, combining human oversight with AI execution is critical. Humans supervise, validate, and handle exceptions, while AI handles repetitive and data-intensive tasks. This reduces risk and builds internal trust.
Develop a long-term AI strategy
Agentic Automation is not a short-term project but part of a broader digital transformation journey. Businesses need clear goals, roadmaps, and performance metrics. Fragmented implementation will lead to inefficiencies and limited scalability.
Choose the right technology and partners
The ecosystem of Agentic Automation technologies is evolving rapidly. Selecting the right platforms and experienced partners is crucial to accelerate implementation, avoid common pitfalls, and maximize ROI.
AkaBot – A Strategic Partner for implemeting Agentic Automation
In the journey toward Agentic Automation, AkaBot acts as a practical and scalable stepping stone, enabling businesses to transition gradually rather than making a disruptive leap. Developed by FPT IS, AkaBot combines RPA, IDP, and AI Agents to move beyond rule-based automation and introduce decision-making capabilities into business operations.
Instead of attempting full autonomy from day one, AkaBot follows a hybrid approach: automating structured, repetitive processes while progressively embedding AI agents into more complex, cross-functional workflows. This allows organizations to both achieve immediate efficiency gains and build the foundation for long-term agentic systems.
Recently, AkaBot has further strengthened its position in the Agentic Automation landscape. It has been recognized by G2 and granted a patent in Taiwan (China) for its Machine Learning-based technology that automatically segments and classifies input documents—an essential capability for intelligent, agent-driven workflows.
👉 Rather than waiting for a large-scale transformation, businesses can begin their Agentic Automation journey today—starting with focused use cases, scaling gradually, and building toward fully autonomous operations with AkaBot.
