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On the morning of April 10, the Exclusive AI Talk 2026 event took place, offering a comprehensive yet highly practical view of how AI is reshaping the workplace within enterprises. Moving beyond trend-driven discussions, the sessions went straight to the core challenge many organizations are facing: how to transform AI from a “technological promise” into a “real operational capability. 

The AI race is accelerating 

One of the most notable takeaways is the growing market pressure forcing businesses to act. According to Gartner and The Wall Street Journal, global AI investment is projected to reach approximately $2.5 trillion, while 68% of CEOs plan to continue increasing their AI spending in 2026, signaling that AI is no longer an experimental option, but a strategic priority. 

Beyond expectations, AI is already proving its real-world value at a global scale. Since the launch of ChatGPT in late 2022, AI-related stocks have contributed around 75% of the total gains of the S&P 500, 80% of earnings growth, and 90% of capital expenditure growth. This underscores that AI is not just a technology wave, but a direct driver of operational efficiency and profit margins for businesses. 

In this context, AI is creating a clear compounding effect. Mr. Nguyen Quoc Tuan, CEO of ScaleUP, noted that early adopters will continue to build advantages over time, while frontrunners accelerate further ahead of the rest. This is also why AI is seen as a long-term game—where companies that wait until ROI becomes fully clear before acting risk falling behind. In such cases, the cost of delay is not just missing opportunities, but can even exceed the initial investment required to implement AI early on. 

From fragmented tools to an AI Workspace – a strategic shift for enterprises 

At the event, Mr. Nguyen Quang Minh – Director of the AI Consulting and Innovation Center (AI Lab) at FPT Smart Cloud, FPT Corporation – outlined a typical “evolution” journey in how enterprises adopt AI. It often begins with the fragmented, individual use of public AI tools. This is followed by a phase where organizations deploy standalone AI Agents, functioning as “digital workers” for specific tasks. 

However, real value only begins to scale when enterprises transition to an AI Workspace model where multiple AI Agents can collaborate to solve more complex problems. At a more advanced level, multi-agent and autonomous AI models enable systems not only to execute tasks but also to reason, allocate work, and coordinate with one another toward shared goals. 

This shift is not merely a technological upgrade, but a fundamental transformation in how businesses operate. 

When AI becomes a new “workforce” within the enterprise 

A key insight from the event is that AI is increasingly taking on the characteristics of a “worker” rather than just a tool. It can perform tasks, collaborate, and even make decisions in certain contexts. However, most organizations today still manage AI as an IT system, rather than as part of their organizational structure. This disconnect is a major bottleneck, preventing many well-funded AI initiatives from delivering proportional impact. In other words, companies are “using AI,” but not yet “operating with AI.” 

Experts at the event emphasized that to bridge the gap between investment and outcomes, businesses need a more holistic approach. According to BCG, three pillars determine AI success: algorithms, technical infrastructure, and people–organization–process. Among these, the last is often the biggest constraint. AI does not fail because it lacks intelligence, but because it is deployed in systems that are not ready to absorb it. When data is unrefined, processes are not standardized, and people are unprepared, AI risks becoming an added layer of complexity rather than a driver of efficiency. 

Vietnam’s challenge: Strong potential, but a lack of high-impact use cases 

According to Mr. Nguyen Duc Hanh, CIO of Thien Long Group, the situation in Vietnam clearly reflects this gap. While interest and investment in AI are rapidly increasing, applications that directly impact revenue, cost efficiency, and operational speed remain limited. This highlights a significant gap—but also a major opportunity. Enterprises that move early in building high-impact use cases will gain a clear competitive advantage in the coming years. 

From an implementation perspective, a practical approach highlighted at the event is to start with small but high-impact use cases—where outcomes can be clearly measured. This not only helps mitigate risks but also builds internal confidence to scale AI initiatives further. 

At the same time, clearly defining objectives, selecting the right tools and partners, and ensuring clean, ready-to-use data are critical prerequisites. More importantly, organizations must be willing to adapt their processes to work effectively with AI, rather than holding on to legacy ways of working. Incorporating AI-related KPIs into performance evaluations and preparing dedicated teams for post-deployment operations are no longer optional—they are quickly becoming the new standard. 

From “using AI” to “implementing AI effectively.” 

In closing, a clear message emerged: in a landscape where trillions of dollars are being invested in AI but results remain uneven, the advantage will not belong to those who invest the most, but to those who understand and implement it effectively. 

From this perspective, AI Workspace is not just a technology trend, but a new operating model—one where humans and “digital workers” collaborate to create real business value. 

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DATA SUBJECT RIGHTS POLICY 

(Reference No.: 02-2026/CS/PDP – Version 1.0) 

1. Introduction

FPT Smart Cloud Company Limited (“FPT Smart Cloud”, “we”, “us”, or “our”) is committed to fully respecting and protecting the lawful rights of Personal data subject matters (or Data subjects) in accordance with Vietnamese laws on Personal data protection. 

This page is designed to provide customers, partners, and users with a transparent, comprehensive, and structured overview of: 

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In 2026, Artificial Intelligence (AI) is shifting decisively from the experimentation phase to large-scale deployment, pushing enterprises to quickly develop strategies to turn AI into a true growth capability.

With insights and guidance from leading technology experts at FPT Smart Cloud, FPT Corporation, the white paper “10 Technology Trends in Vietnam 2026” provides in-depth perspectives and a comprehensive view of the technologies shaping the market – from AI infrastructure, next-generation software development, and domain-specific language models to security, governance, and emerging technology waves that will directly impact competitive advantage in the years ahead.

The white paper helps businesses answer the most critical questions:

  • 1. Where should we start?
  • 2. Which trends have the highest practical application potential in Vietnam?
  • 3. What should we prepare to accelerate innovation while effectively managing risks, data, and operational costs?

AI Agents are artificial intelligence systems that can interact with the environment and make decisions to achieve goals in the real world without any human guidance or intervention. This technology are shaping technology trends, with notable milestones such as the Google I/O 2023 event launching Astra or the emergence of GPT-4o.

Large corporations are pouring billions of dollars into AI Agents to take the lead in AI Era. In this article, FPT.AI will clarify how AI Agents are helping businesses improve processes, enhance customer experience and optimize operations.

What are AI Agents (Intelligent Agents)?

AI Agents are artificial intelligence systems that can interact with the environment and make decisions in the real world without any human guidance or intervention.

AI Agents can gather information from their surroundings, design their own workflows, use available tools, coordinate between different systems, and even work with other Agents to achieve goals without requiring user supervision or continuous new instructions.

With the development of Generative AI, Natural language processing, Foundation Models, and Large Language Models (LLMs), AI Agents can now simultaneously process multiple types of multimodal information such as text, voice, video, audio, and code. Advanced agent AI can learn and update their behavior over time, continuously experimenting with new solutions to problems until achieving optimal results. Notably, they can detect their own errors and find ways to correct them as they progress.

AI Agents can exist in the physical world (robots, autonomous drones, or self-driving cars) or operate within computers and software to complete digital tasks. The aspects, components, and interfaces of each agent AI can vary depending on its specific purpose. Encouragingly, even people without deep technical backgrounds can now build and use AI Agents through user-friendly platforms.

what is ai agent
AI Agents are AI models and algorithms that are capable of making decisions without human intervention.

>>> READ NOW: What is Generative AI? Trends in Applying GenAI from 2024 to 2027

What are the key features of an AI Agent platform?

Key features of an AI Agent platform include:

  • Autonomy: AI Agents can operate independently, make decisions, and take actions without continuous human supervision. For example, self-driving cars can adjust speed, change lanes, stop, or adjust routes based on real-time sensor data about road conditions and obstacles, without driver intervention.
  • Reasoning Ability: AI agents use logic and analyze available information to draw conclusions and solve problems. They can identify patterns in data, evaluate evidence, and make decisions based on the current context, similar to human thinking processes.
  • Continuous Learning: AI Agents continuously improve their performance over time by learning from data and adapting to changes in the environment. For instance, customer support chatbots can analyze millions of conversations to gain deeper understanding of common issues and improve the quality of proposed solutions.
  • Environmental Observation: AI agents continuously collect and process information from their surroundings through techniques like computer vision, natural language processing, and sensor data analysis. This ability helps them understand the current context and make appropriate decisions.
  • Action Capability: AI agents can perform specific actions to achieve goals. These actions can be physical (like a robot moving objects) or digital (like sending emails, updating data, or triggering automated processes).
  • Strategic Planning: AI agents can develop detailed plans to achieve goals, including identifying necessary steps, evaluating alternatives, and selecting optimal solutions. This ability requires predicting future outcomes and considering potential obstacles.
  • Proactivity and Reactivity: AI agents proactively anticipate and prepare for future changes. For example, Nest Thermostat learns the homeowner’s heating habits and proactively adjusts temperature before the user returns home, while quickly responding to unusual temperature fluctuations.
  • Collaboration Ability: AI agents can work effectively with humans and other agents to achieve common goals. This collaboration requires clear communication, coordinated actions, and understanding the roles and objectives of other participants in the system.
  • Self-Improvement: Advanced AI agents can self-evaluate and improve their operational performance. They analyze the results of previous actions, adjust strategies based on feedback, and continuously enhance their capabilities through machine learning techniques and optimization.

agent in artificial intelligence
Key Features of AI Agents

>>> READ NOW: 2 Ways to Classify Artificial Intelligence and 7 Common Types of AI

Differences between Agentic AI Chatbots and AI Chatbots

Below is a comparison table highlighting the distinctions between Agentic AI chatbots and AI Chatbots:

Criteria Agentic AI Chatbots Traditional AI Chatbots
Autonomy Operate independently, perform complex tasks without continuous intervention Require continuous guidance from users, only respond when prompted
Memory Maintain long-term memory between sessions, remember user interactions and preferences Limited or no memory storage capability, each session typically starts from scratch
Tool Integration Use function calls to connect with APIs, databases, and external applications Operate in closed environments with no ability to access external tools or data sources
Task Processing Break down complex tasks into subtasks, execute them sequentially to achieve goals Only process simple, individual requests without ability to decompose complex problems
Knowledge Sources Combine existing knowledge with new information from external sources (RAG) Rely solely on pre-trained data, unable to update with new information
Learning Capability Continuously learn from interactions, improving accuracy and relevance over time Do not learn or improve from user interactions, responses always follow fixed patterns
Operation Mode Can perform multiple processing rounds for a single request, creating multi-step workflows Operate on a single-turn basis (receive-process-respond), without multi-step capabilities
Planning Ability Strategically plan and self-adjust when encountering new information or obstacles No long-term planning capability or strategy adjustment
Personalization Provide personalized experiences based on user history, preferences, and context Deliver generalized responses, identical for all users
Response Process Analyze intent, access relevant information, create plan, execute actions, and evaluate results Recognize patterns, search for appropriate responses in existing database, reply
Error Handling Recognize errors, self-correct, and find alternative solutions when problems arise Often fail to recognize errors or lack ability to recover when encountering off-script situations
User Interaction Proactively ask clarifying questions, suggest options, and track progress Passive, only directly respond to what users explicitly ask
Workflow Use threads to store all information, connect with tools, execute function calls when needed Simple processing according to predefined scripts, no workflow extension capability
Practical Applications Complex customer support, data analysis, process automation, personal assistance Primarily for FAQs, basic customer support, simple conversations
Intent Detection Accurately identify users’ underlying intents, even when not explicitly stated Only react to specific keywords or patterns, often missing true intentions
System Integration Easily integrate with multiple systems and applications through APIs Limited integration capabilities, often requiring custom solutions
Development Requirements Can be developed on no-code platforms, without requiring in-depth programming knowledge Typically require programming knowledge to build and maintain

Agentic AI chatbots mark a significant evolution in conversational AI, powered by LLMs but extending well beyond them. Operating on thread-based architecture, they store complete conversation histories, files, and function call results. These advanced chatbots activate via various triggers (scheduled events, database changes, or manual inputs) to analyze requests, interpret intentions, and execute actions autonomously.

Five key innovations drive this technology:

  • RAG integration for context-aware responses with higher accuracy
  • Function calling to interact with external systems
  • Advanced memory systems for continuous learning and adaptation
  • Tool evaluation to assess resources and fill information gaps
  • Subtask generation to break down complex goals independently

Unlike traditional chatbots’ single-turn model (receive-process-respond), agentic chatbots process multiple turns per prompt, queue actions strategically, and dynamically select appropriate tools based on user intent. They can search connected knowledge bases, call external APIs, or generate responses from core training when external tools aren’t needed. Critically, no-code platforms have democratized their development, accelerating adoption across industries by enabling businesses of all sizes to implement sophisticated AI without significant technical investment.

Agentic AI chatbots
Differences between Agentic AI chatbots and AI Chatbots

>>> READ MORE: What is Agentic RAG? Difference between Agentic RAG and RAG

Key Components of AI Agents

AI Agents are composed of multiple components working together as a unified system, similar to how the human body functions with senses, muscles, and brain. Each component in AI Agent Architecture plays a specific role in helping the agent sense, think, and interact with the surrounding world.

agent intelligent
Key components of AI Agents

Sensors

Sensors help AI Agents collect information (percepts) from the surrounding environment to understand the context and current situation. In physical robots, sensors might be cameras for “seeing,” microphones for “hearing,” or thermal sensors for “feeling” temperature. For software agents running on computers, sensors might be web search functions to gather online information, or file reading tools to process data from PDF documents, CSV files, or other formats.

ai agents
Sensors help AI Agents collect information (percepts) from the surrounding environment

>>> EXPLORE MORE: How to build an AI Agent and train it successfully?

Actuators

If sensors are how agents receive information, actuators are how they affect the world. Actuators are components that allow agents to perform specific actions after making decisions. In physical robots, actuators might be wheels for movement, mechanical arms for lifting objects, or speakers for producing sound. For software agents, actuators might be the ability to create new files, send emails, control other applications, or modify data in systems.

ai agent architecture
Actuators are components that allow agents to perform specific actions after making decisions

Brain

Processors, Control Systems, and Decision-Making Mechanisms form the “brain” of the AI Agents, where information is processed and decisions are made. Processors analyze raw data from sensors and convert it into meaningful information. Control systems coordinate the agent’s activities, ensuring all parts work harmoniously. Decision-making mechanisms are the most important part, where the agent “thinks” about processed information, evaluates different action options, and selects the most optimal action based on goals and existing knowledge.

Ai agent free
Processors, Control Systems, and Decision-Making Mechanisms form the “brain” of the AI Agent

>>> EXPLORE: Applications of AI Agents in Personalized Marketing

Learning and Knowledge Base Systems

These are the memory and learning capabilities of AI Agents, allowing them to improve performance over time. Knowledge base systems store information the agent already knows: data about the world, rules of action, and experiences from previous interactions. This might be a database of locations, events, or problems the agent has encountered along with corresponding solutions.

Learning systems allow the agent to learn from experience, recognize patterns, and improve decision-making abilities. An agent with learning capabilities will continuously update its knowledge base, helping it better cope with new situations or changes in the environment.

The complexity level of these components depends on the tasks the AI Agent performs. A smart thermostat might only need simple temperature sensors, a basic control system, and actuators to turn heating systems on/off. In contrast, a self-driving car needs to be equipped with all components at high complexity levels: diverse sensors to observe roads and other vehicles, powerful processors to handle large amounts of real-time data, sophisticated decision-making systems for safe navigation, precise actuators to control the vehicle, and continuous learning systems to improve driving capabilities through each experience.

Ai agent tool
AI Knowledge Management Agents

>>> EXPLORE: What Are Intelligent Agents? The Difference Between AI Agents and Intelligent Agents

How do AI Agents Work?

When receiving a command (goal) from a user (Prompt), AI Agents immediately initiate the goal analysis process, transferring the prompt to the core AI model (typically a Large Language Model) and beginning to plan actions. The Agent will break down complex goals into specific tasks and subtasks, with clear priorities and dependencies. For simple tasks, the Agent may skip the planning stage and directly improve responses through an iterative process.

During implementation, thanks to Sensors, AI agents collect information (transaction data, customer interaction history) from various sources (including external datasets, web searches, APIs, and even other agents). During this collection process, the AI Agent continuously updates its knowledge base, self-adjusts, and corrects errors if necessary.

The Processors of AI Agents use algorithms, Deep Neural Networks, machine learning models, and artificial intelligence to analyze information and calculate necessary actions.

Throughout this process, the agent’s Memory continuously stores information (such as history of decisions made or rules learned). Additionally, AI Agents also use feedback from users, feedback from other Agents, and Human-in-the-loop (HITL) to self-compare, adjust, and improve performance over time, avoiding repetition of the same errors.

Finally, through Actuators, AI Agents perform actions based on their decisions. For robots, actuators might be parts that help them move or manipulate objects. For software agents, this might be sending information or executing commands on systems.

ai agents framework
Technically, an AI agent system consists of four main components, simulating the way humans operate

To illustrate this process, imagine a user planning their vacation. They ask an AI Agent to predict which week of the coming year will have the best weather for surfing in Greece. Since the large language model that underpins the agent is not specialized in weather forecasting, the agent must access an external database that contains daily weather reports in Greece over the past several years.

Even with historical data, the agent cannot yet determine the optimal weather conditions for surfing. Therefore, it must communicate with a surf agent to learn that ideal surfing conditions include high tides, sunny weather, and low or no rainfall.

With the newly gathered information, the agent combines and analyzes the data to identify relevant weather patterns. Based on this, it predicts which week of the coming year in Greece is most likely to have high tides, sunny weather, and low rainfall. The final result is then presented to the user.

Ai agents examples
According to BCG analysis, AI agents are strongly penetrating many business processes, with a compound annual growth rate of up to 45% over the next 5 years

>>> READ NOW: RPA vs AI Agents: Is RPA Still Relevant in the Age of AI?

Common Types of AI Agents

There are 5 primary types of AI Agents: Simple Reflex Agents,  Goal-Based AI Agents, Model-Based Reflex Agents, Utility-Based Agents, Learning Agents. Each suited to specific tasks and applications:

  • Simple Reflex Agents: Simple Reflex Agents operate on the “condition-action” principle and respond to their environment based on simple pre-programmed rules, such as a thermostat that turns on the heating system at exactly 8pm every night. The agent does not retain any memory, does not interact with other agents without information, and cannot react appropriately if faced with unexpected situations.
  • Model-Based Reflex Agents: Model-Based Reflex Agents use their cognitive abilities and memory to create an internal model of the world around them. By storing information in memory, these agents can operate effectively in changing environments but are still constrained by pre-programmed rules. For example, a robot vacuum cleaner can sense obstacles when cleaning a room and adjust its path to avoid collisions. It also remembers areas it has cleaned to avoid unnecessary repetition.
  • Goal-Based AI Agents: Goal-Based Agents are driven by one or more specific goals. They look for appropriate courses of action to achieve the goal and plan ahead before executing them. For example, when a navigation system suggests the fastest route to your destination, it analyzes different paths to find the most optimal one. If the system detects a faster route, it updates and suggests an alternative route.
  • Utility-Based Agents: Utility-Based Agents evaluate the outcomes of decisions in situations with multiple viable paths. They employ utility functions to measure the usefulness that each action might bring. Evaluation criteria typically include progress toward goals, time requirements, or implementation complexity. This evaluation system helps identify the ideal choice: Is the best option the cheapest? The fastest? The most efficient? For example, a navigation system considers factors such as fuel economy, reduced travel time, and toll costs to select and recommend the most favorable route for the user.
  • Learning Agents: Learning Agents learn through concepts and sensors, while utilizing feedback from the environment or users to improve performance over time. New experiences are automatically added to the Learning Agent’s initial knowledge base, helping the agent operate effectively in unfamiliar environments. For example, e-commerce websites use Learning Agents to track user activity and preferences, then recommend suitable products and services. The learning cycle repeats each time new recommendations are made, and user activities are continuously stored for learning purposes, helping Agents improve the accuracy of their suggestions over time.

ai agents
Popular Types of AI Agents

>>> EXPLORE: What is an LLM Agent? How it works, advantages, and disadvantages

What are the outstanding benefits of using AI Agents?

AI Agents for businesses deliver a consistent experience to customers across multiple channels, with the following 4 outstanding benefits:

  • Improve productivity: AI Agents help automate repetitive and time-intensive tasks, freeing up human resources from manual work so that businesses can focus on more strategic, creative and high-value initiatives, fostering innovation. For more complex issues, AI Agents can intelligently escalate cases to human agents. This seamless collaboration ensures smooth operations, even during periods of high demand.
  • Reduce costs: By optimizing processes and minimizing human errors, AI personnel help businesses cut operating costs. Complex tasks are handled efficiently by AI Agents without the need for constant human intervention.
  • Make informed decisions: AI Agents use machine learning (ML) technologies to help managers collect and analyze data (product demand or market trends) in real time, making faster and more accurate decisions.
  • Improve customer experience: AI agents significantly enhance customer satisfaction and loyalty by offering round-the-clock support and personalized interactions. Their prompt and precise responses effectively address customer needs, ensuring a smooth and engaging service experience. Lenovo leveraged AI agents to streamline product configuration and customer service, integrating them into key systems like inventory tracking. By building a knowledge database from purchase data, product details, and customer profiles, AI agents help Lenovo cut setup time from 12 minutes to 2 minutes, boosting sales productivity and customer experience. This led to a 12% improvement in order delivery KPIs (within 17 days) and generated $5.88 million in one year, according to Gartner.

ai agents
Benefits of implementing AI Agents in Business

>>> Read more about: AI Agents at Work – Foundation for Productivity Breakthrough

Is ChatGPT an AI Agent?

ChatGPT is not an AI Agent. It is a large language model (LLM) designed to generate human-like responses based on received input, with some components similar to AI Agents:

  • Simple sensors that receive text input
  • Actuators that generate text, images, or audio
  • Control system based on transformer architecture
  • Knowledge base system from pre-training data and fine-tuning.

However, these elements are not sufficient to make ChatGPT a genuine Agent. The most important difference between AI Agents and ChatGPT is autonomy. ChatGPT cannot set its own goals, make plans, or take independent actions. When you ask ChatGPT to write an email, it can create content but cannot send the email itself or evaluate whether sending an email is the best action in a specific situation.

Additionally, ChatGPT cannot directly interact with external systems or adjust its behavior based on real-time feedback. Updates like plugins, extended frameworks, APIs, and prompt engineering can improve ChatGPT’s functionality, but still don’t create a complete Agent. ChatGPT also lacks the ability to maintain long-term memory between sessions. It doesn’t “remember” you or previous conversations unless specifically programmed to do so in certain applications.

what are ai agents
ChatGPT lacks core features to be considered an AI Agent

>>> READ NOW: What is a Multi Agent System (MAS)?

Practical Applications of AI Agents

Imagine a future workplace where every employee, manager, and leader not only works together, but is also equipped with a team of AI teammates to support them in every task and at every moment of the workday. With these AI teammates, we will become 10x more productive, achieve better results, create higher quality products, and of course, become 10x more creative.

You may be wondering, “When will this future come?” The answer from FPT is: The future is now. Here are four stories that demonstrate how AI is already impacting businesses.

Revolutionizing Insurance Claims Processing

Imagine you go to the hospital for a health check-up, buy medicine, and file an insurance claim. Typically, the insurance company’s document processing will take at least 20 minutes. With integrated AI Agents, insurers can process all documents through rapid assessment tools, risk assessment tools, and fraud detection tools, returning results in just 2 minutes.

This represents an incredible leap in productivity, improving the customer experience and creating new competitive value for the business.

what are ai agents
AI Agents in Finance – Accounting

>>> READ NOW: Blockchain, Deepseek & AI Agents Reshape the AI ​​Race

Transforming the Customer Contact Center

The second story focuses on customer service. Several FPT.AI customers have deployed AI systems for inbound and outbound communications. These systems provide human-like customer support, handling requests, resolving issues, and providing excellent service.

For some customers, AI Agents are now handling 70% of customer requests, completing 95% of received tasks, and achieving a customer satisfaction rating of 4.5/5. Currently, FPT’s customer service AI Agents manage 200 million user interactions per month.

ai agents
How AI Agents Improve Customer Service

ai agents
Advantages of applying AI Agents in customer service

Empowering pharmacists with AI Mentor

At Long Chau, the largest pharmacy chain in Vietnam, more than 14,000 pharmacists work every day to advise customers. To ensure they stay updated with knowledge and work effectively, FPT.AI has developed an AI Mentor that interacts with more than 16,000 pharmacists across 2,000 pharmacies every day.

This AI Mentor identifies strengths and weaknesses, provides insights, and personalizes conversations to help them improve. The results are:

  • Pharmacists’ competencies improved by 15%.
  • Productivity increased by 30%.

Within the first nine months of the year, the pharmacy chain recorded a revenue growth of 62%, reaching VND 18.006 trillion, accounting for 62% of FRT’s total revenue and completing 85% of its 2024 plan. More importantly, we pride ourselves on helping pharmacists become the best versions of themselves while continuously improving.

ai agents
FPT AI Mentor won the “Outstanding Artificial Intelligence Solution” award at AI Awards 2024

>>> READ NOW: Understanding AI Agents in KYC

From a cost center to a profit center

FPT.AI’s AI Innovation Lab works with customers to identify opportunities, deploy pilots, and scale solutions. For example, one of our clients transformed their customer service center from a cost center to a profit center.

Using AI, they detected when customers were happy and immediately suggested appropriate products or services to upsell credit cards, cross-sell overdrafts, activate new customers to sign up, and reactivate existing customers. This approach helped the customer service center contribute about 6% of total revenue.

The four stories above are just a small part of the countless ways AI can transform businesses. AI, as a new competitive factor, is opening up a blue ocean of innovation. Every company and organization will need to reinvent their operations and build a strong foundation to compete in the future, leveraging the advances of AI.

what are ai agents
Applications of AI Agents in practice

>>> EXPLORE: What is Agentic AI? The differences between Generative AI and Agentic AI

Challenges in Deploying AI Agents

AI Agents are still in their early stages of development and face many major challenges. According to Kanjun Qiu, CEO and founder of AI research startup Imbue, the development of AI Agents today can be compared to the race to develop self-driving cars 10 years ago. Although AI Agents can perform many tasks, they are still not reliable enough and cannot operate completely autonomously.

One of the biggest problems that AI Agents face is the limitation of logical thinking. According to Qiu, although AI programming tools can generate code, they often write wrong or cannot test their own code. This requires constant human intervention to perfect the process.
Dr. Fan also commented that at present, we have not achieved an AI Agent that can fully automate daily repetitive tasks. The system still has the ability to “go crazy” and not always follow the exact user request.

AI Agents
Challenges and Considerations When Using AI Agents

Another major limitation is the context window – the ability of AI models to read, understand, and process large amounts of data. Dr. Fan explains that models like ChatGPT can be programmed, but have difficulty processing long and complex code, while humans can easily follow hundreds of lines of code without difficulty.
Companies like Google have had to improve the ability to handle context in their AI models, such as with the Gemini model, to improve performance and accuracy.

For “physical” AI Agents such as robots or virtual characters in games, training them to perform human-like tasks is also a challenge. Currently, training data for these systems is very limited and research is just beginning to explore how to apply generative AI to automation.

>>>> EXPLORE: What is Data Leakage? How to Prevent Data Leakage when implementing Generative AI?

Continue writing the future with AI Agents with FPT.AI

In the digital economy, competition between companies and countries is no longer based solely on core resources, technology and expertise. Organizations, from now on, will need to compete with a new important factor: AI Companions or AI Agents.

It is expected that by the end of 2025, there will be about 100,000 AI Agents accompanying businesses in customer care, operations and production. Each AI Agent will undertake a number of tasks such as programming, training, customer care… Thanks to that, employees are more empowered, businesses increase operational productivity, improve customer experience, and make more accurate decisions based on data analysis.

fpt ai agents
The Future of AI Agents

FPT AI Agents – a platform that allows businesses to develop, build and operate AI Agents in the simplest, most convenient and fastest way. The main advantages of FPT AI Agents include:

  • Easy to operate and use natural language.
  • Flexible integration with enterprise knowledge sources.
  • AI models are optimized for each task and language.

Currently, FPT AI Agents supports 4 languages: English, Vietnamese, Japanese and Indonesian. In particular, AI Agents have the ability to self-learn and improve over time.

fpt ai agents
FPT AI Agents is FPT Smart Cloud’s trump card in the AI ​​era

AI Agents are all operated on FPT AI Factory – an ecosystem established with the mission of empowering every organization and individual to build their own AI solutions, using their data, supplementing their knowledge and adapting to their culture. This differentiation fosters a completely new competitive edge among enterprises and extends to building AI sovereignty among nations.

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FPT AI Agents Deployment Process

With more than 80 cloud services and 20 AI products, FPT AI Factory helps accelerate AI applications by 9 times thanks to the use of the latest generation GPUs, such as H100 and H200, while saving up to 45% in costs. These factories are fully compatible with the NVIDIA AI Enterprise platform and architectural blueprints, ensuring seamless integration and operation.

>>> READ NOW: Why Gen AI Agents are the future prospect of Generative AI?

FAQs about AI Agents

What’s the difference between LLMs and AI Agents?

LLM (Large Language Model) is an AI model trained on a vast amount of data to recognize and generate natural language. It functions as a “language brain,” predicting each next word in a sentence. However, traditional LLMs are limited to their initial training data, lack the ability to interact with the outside world, and cannot update themselves with new information after training.

AI Agent, on the other hand, is a much more complete system that typically uses an LLM as its core intelligence foundation but is supplemented with sensors (gathering information), actuators (performing actions), knowledge bases (storing knowledge), and control systems (making decisions). This structure allows AI Agents to not only understand language but also interact with the surrounding environment.

The decisive difference between LLMs and Agents lies in the AI Agent’s “tool calling” capability. Through this mechanism, an Agent can retrieve updated information from external sources, optimize workflows, automatically break down and solve subtasks, store interactions in long-term memory, and plan for future actions. These capabilities help AI Agents provide more personalized experiences and comprehensive responses, while expanding their practical application across many fields.

AI Agent
Difference among LLM, RAG and AI Agent

>>> EXPLORE: Are AI Agents the next frontier of NLP Chatbots?

Are Reasoning models (like OpenAI o3 and DeepSeek R1) AI agents?

No. Reasoning models like o3 and R1 are LLMs trained to reason through solutions to complex problems. They do this by breaking them down into multiple steps using chain of thought. These LLMs cannot naturally interact with other systems or extend their reasoning beyond architectural limitations.

How do AI Agents integrate with existing systems and workflows?

The most common ways to integrate AI agents are:

  • Connect it to a RAG platform, providing native connections between LLMs and knowledge bases. This allows the agent to use representations of your documents and business data as context for future responses, increasing output accuracy.
  • Through APIs to external services. When you configure function calls in the AI agent platform, the model interacts with API endpoints in the same way a traditional program would, creating all the headers and body of the call.

AI Agents workflow
AI Agents workflow

How does Human-in-the-loop fit into the AI Agent workflow?

Human-in-the-loop frameworks enhance supervision of AI agent systems. Simply put, the agent’s actions pause at predetermined points in the workflow. A notification is sent to the user, who must review decisions, information, and scheduled tasks. Based on this information, the user will approve or change how the AI agent will continue the task.

Will AI agents take our jobs?

This technology will certainly replace jobs and bring changes to the market, although there is no clear vision of when and how this might happen. Workers may be replaced by AI agents in many industries. At the same time, many positions for AI development and maintenance may be created, along with human-in-the-loop positions, to ensure that human decisions control AI actions rather than the other way around.

Do AI agents exacerbate bias and discrimination?

An AI model is only as unbiased as the data it was trained on—so yes, they are biased. Addressing these issues involves changing machine learning processes and creating datasets that represent the full spectrum of the world and human experiences.

ai agents
AI Agents with Human-in-the-loop

Who is responsible when an AI Agents makes a mistake?

A difficult problem in ethics and law, it’s still unclear who should be blamed for accidents and unintended consequences. The developers? Hardware/software owners? Operators? As new laws are created and industry barriers are implemented, we will be able to understand what roles AI agents can—and cannot—assume.

In short, with the ability to be autonomous, operate independently, make decisions based on data and real-world environments, AI Agents are a powerful automation solution that helps businesses optimize processes. The AI ​​Agents market is forecast to reach a size of 30 billion USD by 2033 and maintain a growth rate of about 31% per year.

The explosive potential of this technology in the next decade is huge. Contact FPT.AI now to take advantage of the enormous power of AI colleagues, accelerate innovation, enhance customer experience and scale more efficiently than ever!

Contact FPT.AI now for more information and a free consultation:

Hotline: 1900 638 399
Website: www.fpt.ai
Address: FPT Tower, 10 Pham Van Bach Street, Dich Vong Ward, Cau Giay District, Hanoi

>>> Read more about:

  • 2025 technology trends: The explosive development of AI Agents
  • Generative AI vs Machine Learning: Key Differences
  • 2025 marked a pivotal milestone for FPT.AI, as this “Make in Vietnam” AI platform achieved strong growth in scale and technological capability, while also solidifying its presence on the regional and global AI map.

    From expanding to more than 200 global customers in 15 countries and serving over 20 million end users, to the rapid proliferation of AI Agents, 2025 is the year AI truly transitions from a “visionary concept” into an essential technology embedded in enterprise operations. Let’s revisit some notable highlights of FPT.AI in 2025.

    Proven technological excellence through key products, solutions, and strategic projects

    Developing more than 70 language models deployed in real-world applications, addressing industry-specific challenges, and processing more than 1.111 trillion tokens.

    FPT Smart Cloud GenAI Product Center has researched, trained, and integrated more than 70 large language models into real-world products. These models have processed 169 million requests, utilizing 1.111 trillion tokens to solve complex, industry-specific inquiries.

    10,220 active AI agents in business operations

    An ecosystem of 10,220 AI Agents has been deployed to help enterprises automate customer service, sales, internal operations, and data analytics. Each AI Agent functions as a dedicated “digital workforce,” operating tirelessly 24/7 across multiple channels.

    FPT AI Mentor expands its footprint in the Japanese market

    Mishima Kosan Co., Ltd., a leading Japanese manufacturing enterprise, has partnered with FPT to integrate AI into its corporate training. The FPT AI Mentor solution enables Mishima Kosan to standardize training programs, shorten skill-upgrading cycles, and support employees in a multilingual working environment. This strategic collaboration has significantly strengthened FPT.AI’s presence across more than 15 countries worldwide.

    Currently, over 50,000 employees are trained each month through FPT AI Mentor.

    FPT AI eKYC processed 75 million identity verifications, digitalizing customer onboarding for banks, fintech companies, and insurance firms with high accuracy, speed, and strict compliance with biometric anti-spoofing and security standards.

    FPT AI Read processed more than 12 million documents.

    By processing 12 million documents, FPT AI Read enables enterprises to eliminate manual data entry, rapidly reading and extracting information from contracts, records, invoices, and other business documents with high precision.

    FPT AI Enhance quality-checked (QC) over 70 million customer service calls, enabling enterprises to monitor customer service quality at scale, detect errors, identify improvement opportunities, and ensure compliance with standardized scripts and tone of voice.

    Launch of 03 new products and solutions

    2025 was a particularly productive year for the FPT.AI product development team, marked by the introduction of three new solutions with outstanding capabilities:

    • FPT AI Voice Agents empower enterprises to build AI-powered contact center teams. These Voice Agents are capable of handling up to 50 million calls per month, equivalent to a large-scale call center, operating 24/7 without human resource constraints. As a result, businesses can automate up to 70% of call center workloads, allowing human agents to focus on complex cases, improve customer experience, and reduce operating costs.
    • FPT AI Adjust – AI–powered claims assistant, specializing in the insurance industry. The solution automates insurance claim intake and processing, enabling faster, more accurate case handling while reducing manual workload and improving customer satisfaction.
    • AI Solutions for Smart City, supporting real-time analysis and monitoring of transportation infrastructure construction, traffic conditions, and incident alerts, while delivering in-depth reports and analytics for authorities.

    Vietnamese AI workforce serving the nation’s transformation in the rising era

    FPT AI Agents accompany the Nation into the AI Era In 2025, the “Make in Vietnam” AI workforce played a strategic role in supporting national digital transformation. FPT AI Agents accompanied officials from the General Statistics Office (Ministry of Finance), Ho Chi Minh City Tax Department, Ho Chi Minh City Department of Construction, and Ca Mau Provincial Employment Service Center.

    Also, FPT.AI’s product ecosystem was selected by the Ministry of Science and Technology as a representative portfolio of innovative, digital transformation technologies and officially published on the Ministry’s electronic portal. The FPT.AI ecosystem includes FPT.AI, FPT AI Agents, FPT AI Mentor, FPT AI Knowledge Explore, and FPT AI Engage, was officially recognized by the Ministry of Science and Technology as exemplary science, technology, innovation, and digital transformation solutions

    with strong application potential and strategic significance. The electronic portal curates and rigorously evaluates a ‘Make in Vietnam’ ecosystem, affirming Vietnam’s technological self-reliance and autonomy in a context where science and technology are defined as key drivers of national development. Official information is now available at nq57.mst.gov.vn.

    Prestigious awards and global certifications

    Scored a double win for best AI solutions at AI Awards 2025

    Affirming its position as a leading technology company, FPT Smart Cloud achieved two major wins at AI Awards 2025, including Best AI Solution with FPT AI Agents Platform and Outstanding AI Enterprise.

    FPT.AI honored at ASOCIO Awards

    Surpassing numerous international competitors, FPT.AI became the first AI platform from Vietnam to be recognized by the Asian-Oceanian Computing Industry Organization (ASOCIO) in the “AI Service Provider” category, one of the most prestigious technology awards in the Asia-Pacific region.

    FPT.AI’s talented AI engineers won 4 awards at VLSP 2025

    Their outstanding performance at VLSP 2025 – the largest academic arena for Vietnamese language processing – once again reaffirms the research excellence of the FPT.AI team

    FPT AI eKYC certified to ISO/IEC 30107-3 level 2

    After passing over 400 sophisticated spoofing attack tests, including 3D masks, silicone, video replays, and projection attacks, FPT AI eKYC successfully met the ISO/IEC 30107-3 Level 2 international security standards. Certified by FIME, a globally renowned testing laboratory, the solution achieved an APCER of 0.75% (below the benchmark <2.5%) and a live face recognition rate exceeding 98%.

    These milestones represent key highlights within the digital transformation landscape that FPT.AI continues to advance alongside enterprises and public sectors. The year 2025 proves that AI is no longer a distant future trend, but a core infrastructure for driving growth, operational optimization, and enhancing the customer experience. FPT.AI’s journey will continue with more remarkable breakthroughs ahead.

    Continuing Generative AI, Agentic AI emerges as a promising technology, ushering in a new era of autonomy and independent thinking for artificial intelligence applications. What exactly is Agentic AI, and how does it differ from Generative AI? Let’s explore with FPT.AI in the following article.

    What is Agentic AI?

    As a new branch of artificial intelligence, Agentic AI represents systems equipped with Reinforcement Learning, language self-awareness, and contextual decision-making capabilities. It can analyze, set goals, strategize, make decisions, and even adjust its behavior through trial-and-error mechanisms to ensure goal achievement without continuous human intervention.

    One of Agentic AI’s standout features is its ability to “chain tasks”—breaking down complex missions into smaller, manageable steps that can be efficiently executed. For instance, when tasked with creating a website, an AI agent system can autonomously plan and execute steps such as:

    1. Designing the website structure and layout.
    2. Drafting content for individual pages.
    3. Writing necessary HTML, CSS, and backend code.
    4. Designing graphics and integrating visuals.
    5. Testing responsiveness and fixing any issues.

    Agentic AI
    Agentic AI is a new branch of Artificial Intelligence

    >>> Explore: What Are AI Agents? The Difference Between AI Agents and AI Chatbots

    How Does Agentic AI Work?

    Agentic AI operates through a four-step process to effectively and autonomously solve problems:

    1. Perceive: It gathers and processes data from various sources like sensors, databases, and digital interfaces. This step involves extracting meaningful features, identifying objects, and recognizing relevant entities to build a comprehensive understanding of the surrounding context.
    2. Reason: Large Language Models (LLMs) serve as reasoning engines, understanding tasks, generating solutions, and collaborating with specialized models to perform functions like content creation, image processing, or recommendation systems. Techniques such as Retrieval-Augmented Generation (RAG) are used to access proprietary data sources, enabling precise and contextually relevant results.
    3. Act: By integrating with external tools and software through APIs, Agentic AI quickly executes tasks based on predefined plans. Control measures ensure accurate task completion, such as capping spending limits for customer service agents.
    4. Learn: Through a continuous feedback loop called the Data Flywheel, Agentic AI learns from its interactions. Data is constantly collected and analyzed to refine models, adapt strategies, and enhance decision-making over time, thereby improving operational efficiency.

    What is agentic ai
    Agentic AI operates through a four-step process

    The Difference Between Agentic AI and Generative AI

    Agentic AI surpasses both traditional AI systems and Generative AI (GenAI). Below is a comparison to clarify the differences:

    Feature Traditional AI Generative AI (GenAI) Agentic AI
    Core Capability Automates repetitive tasks with fixed rules. Relies on human programming and oversight. Creates new content like text, images, audio, and code. Operates based on human commands, enhancing creativity and efficiency. Acts autonomously, setting goals, strategizing, making decisions, and executing actions independently.
    Autonomy Lacks autonomy; follows pre-programmed rules. Limited autonomy; depends on human guidance for context and output. High autonomy; makes decisions and acts without continuous human intervention.
    Learning Cannot learn; executes pre-set rules. Learns from large datasets to improve results but requires human prompts to act. Learns from experience, adapts over time, and optimizes actions and goals autonomously.
    Responsiveness Predefined responses, static reactions. More flexible responses based on context but relies on user commands and training data. Proactively adapts strategies and goals based on situational context and objectives.
    Decision-Making Limited, rule-based. Suggests ideas based on prompts. Sets goals and makes contextual decisions independently.

    While both technologies fall under artificial intelligence, they cater to distinct purposes. Agentic AI focuses on autonomous actions and complex task execution without continuous oversight, while GenAI relies on human input to determine the context and goals for creative outputs.

    The core distinction lies in their outputs: GenAI produces creative content, while Agentic AI delivers actionable solutions and decisions. Together, they can form powerful systems that combine creativity with automation, enhancing efficiency across diverse applications.

    Real-World Applications of Agentic AI

    Agentic AI holds vast potential for applications across various industries. Here are some notable examples:

    1. Business Operations: Handles massive datasets, automates supply chain management, optimizes inventory levels, forecasts demand, and manages complex logistics plans in real-time, enhancing efficiency and reducing costs.
    2. Healthcare: Functions as 24/7 health assistants, personalizing treatment plans and offering proactive care by predicting potential health issues through Big Data analysis.
    3. Software Development: Manages the entire software development lifecycle, from designing architecture and coding to debugging and quality assurance, revolutionizing how digital products are built and maintained.
    4. Cybersecurity: Monitors network traffic, detects anomalies, and addresses real-time threats without human oversight, allowing experts to focus on complex challenges.
    5. Human Resources: Automates tasks like candidate screening, interview scheduling, onboarding, and training while providing personalized career development advice.
    6. Scientific Research: Accelerates breakthroughs by automating experiments, analyzing results, and formulating new hypotheses, driving innovation across various scientific fields.
    7. Finance: Revolutionizes portfolio management, market trend analysis, and real-time investment strategies, enabling higher returns for investors.

    Agentic AI
    Practical application of Agentic A

    Why Is Agentic AI a Promising Technology Trend?

    Agentic AI is gaining significant attention in the tech world for the following reasons:

    • High Autonomy: Operates independently, making it invaluable for tasks requiring constant monitoring or rapid decision-making.
    • Problem-Solving Capabilities: Combines machine learning with goal-oriented behavior to provide innovative and efficient solutions.
    • Flexibility and Adaptability: Adjusts strategies dynamically based on new information or environmental changes.
    • Personalization: Delivers tailored solutions by learning from previous interactions, enhancing customer service processes.
    • Scalability: Deployable across various applications and industries after training, enabling rapid and effective transformation.
    • Enhanced Communication: Processes natural language effectively, facilitating seamless human interaction and control.

    Agentic AI
    Autonomy is one of the main reasons why Agentic AI is gaining attention from the tech community

    Challenges in Deploying Agentic AI

    Despite its potential, implementing Agentic AI poses significant challenges:

    1. Security Risks: Independent decision-making can expose systems to vulnerabilities, such as adversarial attacks, requiring robust security measures.
    2. Unintended Behaviors: Autonomy may lead to unforeseen actions, necessitating transparent decision-making frameworks for effective management.
    3. Resource Costs: Large-scale Agentic AI models demand substantial energy and data, raising sustainability concerns.
    4. Ethical and Social Issues: Concerns include job automation, accountability for AI-driven decisions, and biases in training data affecting outcomes in sensitive areas like law enforcement or recruitment.
    5. Human Oversight: Developing safety mechanisms like kill switches to control autonomous systems is complex, raising concerns about alignment with human values.

    In conclusion, Agentic AI offers vast potential for enhancing efficiency and automation across industries. However, balancing AI autonomy with human oversight is crucial to fully realizing its capabilities. For more information on FPT.AI solutions, contact us via email: support@fpt.ai or hotline: 1900 638 399.

    >>> EXPLORE:

    PRIVACY POLICY 

    (Code: 03-2026/CS/PDP Version: 2.0)  

    1. Introduction

    FPT Smart Cloud Company Limited (“FPT Smart Cloud”, “We”, “Us”) is committed to respecting and protecting the privacy and personal data of our customers, partners, and users throughout the process of interacting with, accessing, and using our products, services, platforms, and websites. This Privacy Statement (“Statement”) is designed to provide you with a comprehensive, transparent, and systematic view of how we collect, process, use, store, share, and protect personal data. 

    This Statement also helps you understand your rights regarding personal data in accordance with the law. It is issued and implemented in compliance with current Vietnamese legal regulations, including but not limited to Personal Data Protection Law No. 91/2025/QH15, Decree 356/2025/ND-CP, and related guiding documents, while referencing international data protection practices and standards. 

    2. Scope of Application

    This Privacy Statement applies to all individuals interacting with FPT Smart Cloud, including but not limited to: 

    • Visitors and users of the website; 
    • Customers using products and services; 
    • Business partners; 
    • Individuals contacting, exchanging, or interacting with us. 

    The scope covers all interaction channels, including websites, digital service platforms, applications, and other online communication methods operated or managed by FPT Smart Cloud. 

    3. Personal Data Processing Roles

    Depending on the specific relationship with you and the type of service provided, FPT Smart Cloud may act as: 

    • Personal Data Controller: When we decide the purposes and means of data processing; 
    • Personal Data Processor: When we process data at the request of customers or partners; 
    • Both Controller and Processor of personal data. 

    Specific roles will be determined based on the nature of the service and the agreement between the parties. 

    4. Types of Personal Data Collected

    We may collect and process the following types of personal data: 

    4.1. Data Provided by you includes information you actively provide, such as: 

    • Full name; 
    • Email address; 
    • Phone number; 
    • Organization/Business information; 
    • Content of exchanges, requests, or feedback. 

    4.2. Automatically Collected Data Technical information collected when you access our website or services: 

    • IP address; 
    • Device type, operating system, and browser; 
    • Access behavior data; 
    • Cookies and similar tracking technologies. 

    4.3. Data Arising During Service Use  

    • System logs; 
    • Usage history; 
    • Interaction information with the platform. 

    5. Purposes of Processing Personal Data

    Personal data is processed for specific, legal, and transparent purposes, including: 

    • Providing, operating, maintaining, and improving the quality of products and services; 
    • Establishing, performing, and managing contractual relationships; 
    • Receiving and responding to requests, inquiries, or complaints; 
    • Ensuring system safety, security, and fraud prevention; 
    • Fulfilling legal obligations as required by law; 
    • Analyzing, researching, and enhancing user experience; 
    • Conducting marketing and communication activities (subject to your consent). 

    Note: We commit not to use your personal data to train Artificial Intelligence (AI) models without valid consent or unless the data has been anonymized according to regulations. 

    6. Legal Basis for Processing

    The processing of your personal data is based on one or more of the following: 

    • Your explicit and valid consent; 
    • Contractual performance obligations between you and FPT Smart Cloud; 
    • Legal obligations we must comply with; 
    • Legitimate interests of FPT Smart Cloud, provided they do not affect your legal rights and interests. 

    7. Sharing and Disclosure of Personal Data

    When necessary, your data may be shared with: 

    • Affiliates and member units within the FPT ecosystem; 
    • Partners and service providers supporting operations (e.g., technology infrastructure, technical support); 
    • Competent state authorities as required by law; 
    • Other relevant parties to protect the legal rights and interests of FPT Smart Cloud. 

    We ensure that all data recipients are obligated to maintain confidentiality and only process data for the specified purposes. 

    8. International Data Transfer

    Personal data may be transferred outside the territory of Vietnam if necessary for service provision. In such cases, we commit to: 

    • Fully complying with Vietnamese legal regulations on overseas data transfer; 
    • Performing impact assessments and necessary legal procedures; 
    • Applying appropriate protection measures to ensure data safety; 
    • Fulfilling reporting obligations to competent authorities as required. 

    9. Data Retention Period

    Your personal data will be stored for the period necessary to fulfill the identified processing purposes or as required by applicable law. Upon expiration of the storage period, data will be deleted, anonymized, or destroyed using appropriate technical and organizational measures. 

    10. Personal Data Security

    We apply appropriate technical and organizational security measures to protect personal data from risks such as unauthorized access, loss, disclosure, or alteration. These include: 

    • Access control; 
    • Data encryption; 
    • Intrusion monitoring and detection; 
    • Security awareness training for personnel. 

    11. Handling Personal Data Incidents

    In the event of a personal data incident, FPT Smart Cloud will proactively take measures to control and rectify the situation. We will: 

    • Notify competent authorities as required by law; 
    • Notify the data subject when necessary to minimize risks. 

    12. Your Rights

    You have full rights related to your personal data as prescribed by law, including the right to be informed, access, correction, deletion, restriction or objection to processing, withdrawal of consent, and the right to complain. Detailed procedures are available in our Data Subject Rights Performance Policy published on our website. 

    13. Cookies and Tracking Technologies

    We use cookies to ensure website operation, analyze user behavior, personalize experiences, and support marketing activities (with your consent). Detailed usage is governed by our Cookie Policy. 

    14. Third-Party Links

    Our website may contain links to third-party websites or services. We do not control and are not responsible for the content or data protection policies of these parties. You should consult their privacy policies before providing personal data. 

    15. Contact Information

    For any questions, requests, or complaints regarding personal data processing, please contact: 

    • Data Protection Officer (DPO): Pham The Minh 
    • Company: FPT Smart Cloud Company Limited  
    • Address: No 10 Pham Van Bach Street, Cau Giay ward, Hanoi, Vietnam 
    • Email: support@fpt.ai  
    • Hotline: 1900 638 399  

    16. Statement Updates

    FPT Smart Cloud reserves the right to modify or update this Privacy Statement periodically to ensure compliance with legal regulations and operational practices. Updated versions will be published on the website and take effect from the time of posting. Continued use of our services after an update signifies that you have read, understood, and agreed to the revised content. 

     

    COOKIE POLICY

    1. Introduction

    This Cookie Policy (“Policy”) explains how FPT Smart Cloud Company Limited (“FPT Smart Cloud”, “We”, “Us”) uses cookies and similar technologies when you access and use our websites, platforms, and online services. 

    This Policy should be read in conjunction with our Personal Data Protection Policy. 

    Your continued use of the website after being notified about cookies implies your consent to the use of cookies in accordance with this Policy, unless you choose to opt out or adjust your cookie settings.

    2. What are Cookies?

    Cookies are small data files stored on your device (computer, phone, tablet) when you visit a website. Cookies allow the website to: 

    • Recognize your device; 
    • Remember your preferences and browsing behavior; 
    • Improve performance and user experience. 

    3. Purpose of Using Cookies

    We use cookies for the following purposes: 

    • Ensuring the stable operation of the website; 
    • Remembering user choices and preferences; 
    • Analyzing traffic and usage behavior; 
    • Improving content, performance, and experience; 
    • Supporting marketing activities (subject to your consent); 
    • Ensuring security and detecting fraud. 

    4. Classification of Cookies

    We use the following types of cookies: 

    4.1. Necessary Cookies These are essential for the website to function correctly. They handle: 

    • Page navigation; 
    • User authentication; 
    • System security. These cookies do not require your consent. 

    4.2. Performance and Analytics Cookies 

    These cookies help us: 

    • Understand how users interact with the website; 
    • Collect aggregate information (non-directly identifiable); 
    • Improve system performance. The use of these cookies requires your consent according to legal regulations. 

    4.3. Functional Cookies 

    These cookies allow the website to: 

    • Remember your preferences (language, region); 
    • Personalize the user experience. 

    4.4. Marketing Cookies 

    These cookies are used to: 

    • Display relevant advertising content; 
    • Measure the effectiveness of marketing campaigns; 
    • Limit the frequency of advertisement displays. These cookies are only used with your consent. 

    5. Third-Party Cookies

    In some cases, we may use cookies from third parties, such as: 

    • Analytics providers; 
    • Advertising platforms; 
    • Integrated services (video, maps, social networks). 

    These third parties may collect and process data according to their own policies. We recommend that you consult the privacy policies of the relevant third parties. 

    6. Managing and Setting Cookies

    You have the right to choose whether to accept or decline cookies. You can manage cookies by: 

    Adjusting browser settings: 

    • Deleting cookies; 
    • Blocking cookies; 
    • Setting alerts when a cookie is sent. 

    Using the cookie management tool on the website (if available): 

    • Accepting all; 
    • Declining; 
    • Customizing by cookie type. 

    Note: Declining certain types of cookies may affect your experience using the website. 

    7. Legal Basis

    Our use of cookies complies with: 

    • Personal Data Protection Law No. 91/2025/QH15 and Decree 356/2025/ND-CP guiding the Personal Data Protection Law; 
    • The principles of transparency and data subject consent; 
    • International practices regarding privacy. 

    For non-essential cookies, we will: 

    • Only use them with your valid consent; 
    • Allow you to withdraw your consent at any time. 

    8. Cookie Storage Duration

    Cookies can be stored: 

    • In-session (session cookies): Automatically deleted when you close your browser. 
    • Persistent cookies: Stored for a specific period of time. 

    The specific storage time depends on the purpose of use and system configuration. 

    9. Policy Updates

    We may update this Cookie Policy from time to time to align with: 

    • Changes in legislation; 
    • Technological changes; 
    • Operational needs. 

    The updated version will be published on the website and will take effect from the time of posting. 

    10. Contact

    If you have any questions regarding the use of cookies, please contact: 

    • Data Protection Officer (DPO)  
    • Company: FPT Smart Cloud Company Limited  
    • Address: No 10 Pham Van Bach Street, Cau Giay District, Hanoi, Vietnam  
    • Email: Minhpt@fpt.com  
    • Hotline: 1900638399  

    PERSONAL DATA PROTECTION POLICY 

    (Reference No.: 01-2026/CS/PDP – Version 2.0) 

    1. Introduction

    FPT Smart Cloud Company Limited (“FPT Smart Cloud”, “We”, “Us”) is committed to respecting and protecting the privacy and personal data of individuals and organizations when accessing and using our websites, platforms, and services. 

    This Personal Data Protection Policy (“Policy”) is issued to: 

    • Ensure transparency in personal data processing activities; 
    • Safeguard the lawful rights and interests of Personal data subject matters; 
    • Comply with Vietnamese laws, including the Law on Personal Data Protection No. 91/2025/QH15, Decree No. 356/2025/ND-CP, and relevant implementing regulations; 
    • Align with international data protection standards. 

    By accessing and using our platforms, you acknowledge that you have read, understood, and agreed to this Policy. 

    2. Scope of Application

    This Policy applies to all activities involving the collection and processing of personal data of: 

    • Customers; 
    • Website users; 
    • Partners; 
    • Individuals interacting or having contact with FPT Smart Cloud. 

    This Policy applies across all channels, including but not limited to: 

    • Websites; 
    • Applications; 
    • Digital service platforms; 
    • Other online interaction channels. 

    3. Definitions

    For the purposes of this Policy: 

    • Personal data: Personal data refers to digital data or information in other forms that identifies or assists the identification of a specific individual, including basic personal data and sensitive personal data. Personal data, once de-identified, is no longer considered personal data. 
    • Personal data subject matters (or Data subject): Personal data subject matters refer to persons reflected in the personal data. 
    • Personal data processing: Personal data processing refers to activities impacting personal data, including one or more of the following: collection, analysis, summary, encryption, decryption, modification, deletion, destruction, de-identification, provision, disclosure, transfer of personal data, and other activities impacting personal data.. 
    • Personal data controlling party (or Data Controller): Personal data controlling party refers to an agency, organization, or individual that decides on the purposes and means of personal data processing. 
    • Personal data processing party (or Data Processor): Personal data processing party refers to an agency, organization, or individual processing personal data as requested by the personal data processing party or personal data processing and controlling party under a contract. 
    • Personal data processing and controlling party (or Data Controller and Processor): Personal data processing and controlling party refers to an agency, organization, or individual that decides on the purposes and means of personal data processing and directly processes personal data. 

    Depending on specific circumstances, FPT Smart Cloud may act as a Personal data controlling party, Personal data processing party, or both Personal data processing and controlling party. 

    4. Categories of Personaldatacollected 

    4.1. Data provided by you 

    Including but not limited to: 

    • Full name; 
    • Email address; 
    • Phone number; 
    • Company information; 
    • Content of communications and requests. 

    4.2. Automatically collected data 

    When you access our website: 

    • IP address; 
    • Device and browser type; 
    • Cookie data; 
    • Browsing behavior information. 

    4.3. Data generated during service use 

    • System logs; 
    • Usage history; 
    • Platform interaction data. 

    5. Purposes ofdataprocessing 

    Personal data is processed for the following purposes: 

    • Providing, operating, and improving services; 
    • Establishing, performing, and managing contractual relationships; 
    • Receiving and handling requests and feedback; 
    • Ensuring safety and information security; 
    • Complying with legal obligations; 
    • Conducting analysis and research to enhance service quality; 
    • Carrying out marketing and communication activities with consent. 

    FPT Smart Cloud commits not to use customer personal data to train artificial intelligence (AI) models without explicit consent or full anonymization. 

    6. Legalbasis forprocessing 

    We process personal data based on: 

    • Consent of the Personal data subject matter; 
    • Contractual obligations; 
    • Legal obligations under applicable laws; 
    • Legitimate interests of FPT Smart Cloud, provided such interests do not override the lawful rights and interests of the Personal data subject matter. 

    7. Datasharing anddisclosure 

    Personal data may be shared in the following cases: 

    • With affiliated companies and subsidiaries; 
    • With partners and service providers (e.g., cloud infrastructure providers, technical support); 
    • Upon request by competent state authorities; 
    • When necessary to protect the lawful rights and interests of FPT Smart Cloud. 

    Recipients of data are obligated to maintain confidentiality and process data only for agreed purposes. 

    8. Cross-borderdatatransfer 

    As a principle, FPT Smart Cloud stores data within Vietnam. In cases where cross-border data transfer is required: 

    • We comply with Vietnamese legal regulations on data transfer; 
    • We conduct a Data Transfer Impact Assessment and submit the required dossier to the Department of Cybersecurity and High-Tech Crime Prevention (A05) under the Ministry of Public Security; 
    • We apply appropriate safeguards to ensure data security. 

    9. Dataretentionperiod 

    Personal data is retained for as long as necessary to fulfill the processing purposes or as required by law. 

    After the retention period, data will be: 

    • Deleted; 
    • Anonymized; or 
    • Securely destroyed in accordance with internal procedures. 

    10. Rights ofPersonal data subject matters

    Personal data subject matters have rights under applicable laws, including: 

    • The right to be informed and to give consent; 
    • The right to access and correct data; 
    • The right to withdraw consent; 
    • The right to request deletion of data; 
    • The right to restrict or object to processing; 
    • The right to lodge complaints or initiate legal action. 

    To exercise these rights, Personal data subject matters may contact us using the details provided in Section 13. 

    FPT Smart Cloud will handle such requests within the timeframes required by applicable law. 

    11. Personaldatasecurity 

    We implement appropriate technical and organizational measures to protect personal data, including: 

    • Access control mechanisms; 
    • Data encryption; 
    • System monitoring; 
    • Prevention of unauthorized access; 
    • Staff training on information security. 

    12. Personaldatabreach handling 

    In the event of a personal data incident, FPT Smart Cloud will: 

    • Promptly detect and assess the incident; 
    • Apply necessary remedial measures; 
    • Notify competent authorities within 72 hours (or as required by law); 
    • Notify affected Personal data subject matters when necessary. 

    13. Contactinformation

    For any requests or inquiries regarding personal data, please contact: 

    Data Protection Officer (DPO) 
    FPT Smart Cloud Company Limited 

    Address: No. 10 Pham Van Bach Street, Cau Giay Ward, Hanoi, Vietnam 

    Email: Minhpt@fpt.com 

    Phone: 0913571357 

    Hotline: 1900638399 

    14. Implementation Provisions

    This Policy may be amended or supplemented from time to time to ensure compliance with legal requirements and operational practices. 

    This Policy takes effect from the date it is officially published on the FPT Smart Cloud website. 

    SECURITY OR PRIVACY VULNERABILITY REPORTING 

    If you believe you have discovered a security vulnerability or a privacy-related issue within FPT Smart Cloud’s products or services, we look forward to receiving your feedback to help build a safer cloud computing environment. 

    I. Reporting Methods

    FPT Smart Cloud welcomes reports from security researchers, partners, and customers. To ensure information is processed quickly, please send an email to the following addresses: 

    • Technical Security Issues: support@fpt.ai
    • Privacy & Personal Data Issues: minhpt@fpt.com (Send directly to the Data Protection Officer). 

    Your report should include the following information: 

    • The affected product/service and software version. 
    • A detailed description of the observed behavior versus the expected behavior. 
    • Specific steps to reproduce the error (include illustrative videos if available). 
    • Safety Note: Please encrypt sensitive information before sending it to protect the data during transmission. 

    II. Receipt and Processing Procedure

    To protect our systems and customer data, FPT Smart Cloud applies the Coordinated Vulnerability Disclosure (CVD) process according to ISO/IEC 29147 standards: 

    • Acknowledgment: We will send a confirmation response acknowledging receipt of your report within 24-48 business hours. 
    • Investigation & Remediation: FPT Smart Cloud will not disclose or publicly discuss security issues until the investigation is complete and necessary updates have been widely released. 
    • Public Disclosure: We use Security Advisories to provide information about fixes and to recognize the contributions of the reporting individuals or organizations. 

    III. Security Advisories & Compliance 

    FPT Smart Cloud’s Security Advisories are designed to help customers maintain system safety and meet standards such as PCI DSS v4.0.1 and ISO 27001. 

    • Technical Advisories: Updates on configuration changes, patches, or potential risks that are not categorized as software vulnerabilities but affect overall information security. 
    • Recommendations: Customers should regularly monitor Technical Security Advisories and update their systems periodically to ensure data availability and integrity. 

    FPT Smart Cloud is committed to maintaining the confidentiality of the reporter’s information and handling all vulnerabilities with the highest sense of responsibility. 

    Artificial Intelligence (AI) is reshaping our world at a rapid pace. From optimizing business processes to supporting critical decisions, AI offers infinite potential, fostering a synergy between AI and humans. However, alongside its immense benefits, AI also poses significant challenges, especially concerning ethics. The question is no longer “How will AI develop?” but rather “How should AI develop responsibly?”. 

    This is where AI ethics becomes a timely and urgent topic, not only for technology developers but also for regulators, businesses, and society as a whole. Let’s explore what AI ethics is with FPT.AI! 

    What is AI Ethics? 

    AI ethics is a set of principles, values, and guidelines that aim to ensure the transparent, fair, and responsible development, deployment, and use of artificial intelligence. According to UNESCO, AI ethics doesn’t just focus on what the technology can do, but also revolves around the questions of “What should AI do?” and “How should we use AI to benefit humanity, rather than cause harm?”. 

    what-is-AI-ethics

    Why is AI Ethics Important?  

    AI is no longer merely supporting technology. It’s a powerful tool capable of making decisions. According to Deputy Minister of Science and Technology, Mr. Bui The Duy, AI is completely different from any other technologies that humans have found before. While old technological products only follow existing instructions, AI can create its own directions, beyond the control of developers. 

    Furthermore, AI has now become an indispensable partner for humans. A global study involving approximately 32,000 workers from 47 countries by The University of Melbourne showed that over 58% of employees actively use AI in their work, with one-third of them using AI weekly or daily. . 

    AI-va-tuong-lai-cua-cong-viec
    Ảnh được thiết kế bởi Yevgenia Nayberg

    Therefore, without ethical oversight, sometimes wrong decisions made by AI can have far-reaching impacts on individuals or even a nation. An algorithm could reject a job application simply because their resume came from a rural area, implicitly assuming they are “less promising.” A facial recognition system could misidentify people of color due to a lack of diverse data. A chatbot could learn discriminatory language from social media users if left unchecked. 

    These examples highlight that if AI lacks ethics, the consequences will not be limited to technical errors but will also lead to social, legal, and humanitarian consequences. 

    Core Values Shaping AI for the Future 

    core-values-of-ai-ethics

    In the journey of artificial intelligence development, what’s important is not just how far technology advances, but which direction we are leading it. To ensure AI serves the common good, for people, society, and this planet, UNESCO has outlined four core values that act as guiding principles, including: 

    • Respecting human rights and human dignity: Ensuring the respect, protection, and promotion of human rights, fundamental freedoms, and the dignity of each individual. 
    • Building peaceful, just, and interconnected societies: Encouraging the development of societies where everyone can live in harmony, fairness, and connection. 
    • Promoting diversity and inclusion: AI must be designed to serve everyone, excluding no one, fostering diversity and creating equal opportunities. 
    • Protecting the environment and developing thriving ecosystems: AI technology needs to be environmentally responsible, contributing to the protection of the planet and natural ecosystems. 

    These values are crucial compasses for guiding AI development in a positive, sustainable direction. 

    Core Principles in AI Ethics

    With the goal of “living safely” with AI, philosopher Luciano Floridi has distilled 5 core principles, becoming reliable beacons on the journey alongside AI: 

    • Beneficence: AI should be developed and applied to improve the lives of humans and our planet. The ultimate goal is to create “AI for Social Good” (AI4SG), where AI is used to enhance societal well-being. 
    • Nonmaleficence: The principle of “do no harm” is paramount, especially when AI has the potential to affect human existence. This includes avoiding harm to privacy, autonomy, and employment opportunities. 
    • Autonomy: Human ability to act freely and independently must be preserved and promoted, while machine autonomy needs to be limited. 
    • Justice: AI must be developed, designed, and deployed in a way that promotes justice, fairness, equality, and related values. This requires addressing issues like algorithmic bias and ensuring equitable access. 
    • Explicability: To promote other principles, we need to understand the “how” and “why” behind AI systems and products. Accountability and transparency are key. 

    What Should Businesses Do? 

    For businesses, investing in AI technology cannot be separated from building an ethical foundation. According to Coursera, many global corporations like IBM, Google, and Microsoft have established internal ethics committees, built codes of conduct, and verification processes to ensure their AI products adhere to ethical standards from the outset. 

    Some specific actions regarding AI ethics that businesses can take include: 

    • Training personnel on AI ethics, data, and privacy. 
    • Integrating ethical risk assessment into the product development process. 
    • Consulting independent experts to review critical algorithms. 
    • Being transparent about how data is collected, processed, and used. 
    • Establishing internal ethics councils to verify products before launch. 

    Not Just One Person’s Responsibility 

    AI ethics is not solely a matter for the tech industry; it’s a shared responsibility of society as a whole: 

    • Nations and government agencies need to create flexible, appropriate, and practical legal frameworks that keep pace with technological development while still safeguarding human rights. 
    • Universities and research institutes need to integrate ethics topics into AI and data science curricula. 
    • AI users also need to enhance their understanding to use AI intelligently and responsibly. 

    Towards a Sustainable Technological Future 

    AI ethics is not a barrier to innovation, but a solid foundation for the development of artificial intelligence. By prioritizing these core values, we are building a future where AI is not only exceptionally intelligent but also deeply humane, serving and enhancing human life. 

    As AI becomes increasingly integrated into decision-making systems, AI ethics is no longer an option – it’s a prerequisite for building a just, transparent, and humane digital society. 

    🤝 Build ethical AI today, create lasting trust tomorrow. 

    Sources

    UNESCO. (n.d.). Recommendation on the Ethics of Artificial Intelligence. https://www.unesco.org/en/artificial-intelligence/recommendation-ethics 

    Coursera. (2023, July 26). What is AI ethics? Definition and examples. https://www.coursera.org/articles/ai-ethics 

    IBM. (n.d.). AI ethics. IBM. https://www.ibm.com/think/topics/ai-ethics 

    University of Texas at Austin. (n.d.). AI ethics. Ethics Unwrapped. https://ethicsunwrapped.utexas.edu/glossary/ai-ethics thics Unwrapped. https://ethicsunwrapped.utexas.edu/glossary/ai-ethics