9 Application AI in the enterprise operating all business processes

In the context of competition is increasingly fierce, the business organizations are to find out information about the application AI in the enterprise no longer see this trend was far-fetched, which is a practical solutions to enhance the operational capacity, innovation business model.

This trend is evidenced clearly by the data. According to the report The State of AI Index 2025 Stanford's TWO, with up to 78% of organizations globally have application AI to work at least in a division in the year 2024, a significant increase compared with the level of 55% by the year 2023 (hai.stanford.edu). In Vietnam, the study of the Vietnam News found 18% of enterprises have deployed AI, higher than 13% on the previous year, reflecting the speed of the rapid growth of this technology in the domestic market (vietnamnews.vn).

This shows that, app, artificial intelligence is no longer your own advantage, the technology giant, which is becoming a “lever” to help businesses in many scales to optimize costs, improve customer experience, expand business opportunities. This article Lac Viet Computing will help the business better understand: the concept of AI in business operations, the application-specific benefits – challenges at the same time route suggestions deployment in accordance to harness the real value from AI.

1. Concept & the application form AI in business

1.1 definition “AI in business”

Artificial intelligence (AI) in business can understand is the use of the system, algorithms help machines have the ability to learn from data, analysis and decisions, or suggestions, instead of just following command fixed. Say a way to visualize AI is like a “smart employee” can handle large volumes of information quickly, many times people, making suggestions based on what has been learned.

Some concepts AI frequently:

• Machine Learning (machine Learning): computers learn from data to identify patterns and predict. For example, AI systems analyze purchase history to predict customer can buy any product to the next.
• Deep Learning (deep Learning): advanced Form of Machine Learning, simulation activity of the brain. This is the foundation of image recognition, voice or language translation automatically.
• Generative AI (AI creation): technology help to create new content such as text, images, or video. For example, create business reports from raw data or poster design marketing.
• Chatbots, virtual assistants: tools AI communicate with customers or employees via natural language, can support 24/7.

Can distinguish AI in business into three main groups:

• AI automation: Replace the task repeats, which helps reduce cost and time.
• AI-assisted decision-making: analyzing big data to make predictions, which in turn helps leaders have a more accurate determination.
• AI change new products/services: application of AI to create new value, for example product recommendations personalized for each customer or product development smart.

1.2 degree of applied & stages of development AI in business

Not any business also apply AI at the same level. Usually will go through 4 stages:

1. Test (Pilot): Business, choose a small department to test the application AI, for example, deploy chatbot in customer care.
2. Deployed in parts: When you see the effect, AI are deployed for many departments, such as incorporating AI in the analysis of financial data.
3. Integrated into grand strategy: AI does not just support tool, which become part of the strategic long-term growth.
4. Innovation business model: Business development, product/new service based on AI, create competitive advantage and sustainable.

In Vietnam, according to Vietnam News, the majority of new business only at the stage of using AI for the basic tasks, such as process automation, or chatbot. The advanced application, such as big data analytics, or AI creative still in the process of testing, due to limited resources, skills development (vietnamnews.vn).

2. 9 apps AI in the enterprise operating all business processes

2.1. App AI analysis of data in business

App AI in business in the last analysis, business metrics commonly used in large corporations. The AI technology, popular in the analysis of business data, including machine learning (machine learning) and deep learning (deep learning). Machine learning uses algorithms to learn from data, thereby making the prediction or identification of samples. Deep learning, a branch of machine learning, uses neural networks to analyze more complex data such as images or language.

AI technologies bring many benefits in the analysis of business data. AI can analyze historical data to predict future trends, help in business plan preparation effective strategy. Through the analysis of customer data, market, AI help business adjust and optimize the business strategy to achieve the best results.

A typical example of the application AI in successful business thanks to the application AI in data analysis is Amazon. Amazon uses AI to analyze the shopping behavior of the customers, which proposed the suitable product and personalize the shopping experience. This helps not only to increase revenue but also improve the satisfaction of customers.

2.2. App AI virtual assistant answered 24/7 information internal business

App AI in business to provide information timely and accurate, increasing experience satisfaction for employees. Virtual assistant AI helps employees to access internal information quickly and accurately without losing much time search.

Virtual assistant AI works based on machine learning algorithms and processing natural language, which allows to understand, respond to the requirements of employees in a smart way. The virtual assistant this can be integrated with the system of internal documents of the business, helping to lookup and answer information from documents such as rules, regulations, procedures, employee handbook, forms, instant.

Instead of having employees need to filter the results from the system documentation, when the application AI in business virtual assistant AI will synthesize, summarize information, make sure to find the right and the full 100% of the information needed. In addition, the virtual assistant has the ability to solve information in any context, addressing information, 24/7, any time.

For example, virtual assistant LV ChatBot AI is integrated into the system documents internal of the company, help employees access information quickly, thereby increasing work performance and minimize wasted time. Thanks to that,the business has advanced, efficient management and operation, ensure the operation goes smoothly and more efficiently.

2.3. Application virtual assistant AI in operations business accounting

Application AI in accounting optimal operation management, financial accounting, say no to data entry manually, minimize errors and financial management a way more active. Accounting software integration assistant AI brings many outstanding features, help optimize financial management:

• Automate data entry, invoice entry: application recognition technology, optical character (OCR) and artificial intelligence systems have the ability to read, dissection, automatic processing, data entry, invoice information input correctly, eliminate errors, save time entering data manually.
• Accounting assistant: Support to answer any queries in real time right in functions, statistical reports, helping leadership decisions quickly and minimize the time the report.
• Analyze and monitor financial indicators: Assistant AI has the ability to analyze and track the financial indicators, warning fluctuations instant help businesses manage risks in an active way.
• Automation scheduling, and reminders to limit the debt – payment: the System automatically send a reminder email on the account, the debt payments due, helps to increase the experience with customers and suppliers.
• Financial forecast accuracy: application of AI in the enterprise to analyze historical data and predict trends, the software helps business financial planning more accurate.
• Virtual assistant AI: Support 24/7, to answer any questions about the policy and modes of finance and accounting. Integrated platform ChatGPT and Gemini, this virtual assistant can provide information questions & answers quickly.

Lac Viet successful development software, LV-DX Accounting application of artificial intelligence help automate the process of data entry, minimize errors, improve efficiency, financial management. Thanks to the ability to analyze and instant alerts of AI assistant, LV-DX Accounting integrated AI support risk management a proactive financial planning more accurate.

2.4. App AI in lookup – signed in the business process

App AI in the enterprise with business lookup – signed in the operating procedures help optimize the active search for information, the sign, make a decision. AI are integrated of the same model RAG in the system of document management, the register number, to help answer any queries in real time right in the workspace. This feature helps leaders quickly grasped the situation, business decision immediately, reducing wait time employee accountability report.

See details: X5 performance with software digitization process application intelligence AI lookup, approved

When there are documents that need approval, instead of having to manually filter the information from the search results, traditional, virtual assistant AI has the ability to research, summarize information and answers to users right on the documentation.

2.5. Process automation (Workflow Automation, RPA)

In many businesses, employees often take a lot of time for the work repeated as data entry for invoice reconciliation, or synthesis report. AI combined with technology, RPA (Robotic Process Automation) can handle the task of this in an automatic way, many times faster than humans.

For example, A logistics company can use AI to automatically read to extract information from lading, rather because employees have to enter manually. This helps reduce the rate of errors due to human, at a minimum, at the same time save hundreds of hours of work per month.

Real value for business:

• Reduce staffing costs in the stitch administration.
• Increased processing speed tasks, shorten the time customer feedback.
• Enhance accuracy, reduce risks skewed data.

2.6. Chatbots, virtual assistants in customer care

As reported by Gartner, by 2025, approximately 80% of trades customer service will be handled at least in part by AI (Gartner). Chatbots, virtual assistants to help businesses serve customers 24/7, responding quickly to the frequently asked questions, at the same time reduce the pressure for staff of customer care.

For example, Banks can deploy chatbot on the website or mobile application to assist customers to check balances, lookup, transaction history, or interpretation of the loan procedure. Thus, employees only need to focus on the more complex problems instead of handling the requirements simple.

Real value for business:

• Enhance customer experience thanks to quick service, continuous.
• Reduce operating costs total station customer care.
• Collects data of the user behavior, thereby improving the product/service.

2.7. Personalize customer experience

In the competitive environment today, serving every customer by a “general formula” is no longer effective. AI help businesses analyze data, shopping behavior, transaction history, habits interact to give suggestions tailored to each customer.

For example: Amazon ever published 35% of their sales come from the hint system products based on AI. This suggests personalization not only increase conversion rate but also increase the value of orders average. In Vietnam, many floor ecommerce as Shopee, Lazada also use AI to suggest products and help retain customers longer on the platform.

Real value for business:

• Increase the rate of repeat purchases, increased customer loyalty.
• Reduce marketing costs thanks to the right approach needs instead of ad the tea.
• Improve user experience, from which enhance brand reputation.

2.8. Applications in manufacturing, supply chain

AI plays an important role in the optimization of production and logistics, which is the “backbone” of many businesses. Through sensors, IoT, data analysis, real-time, AI can monitor line fault detection products immediately to give warnings predictive maintenance.

For example, corporations automobile manufacturers such as BMW, Toyota has been using AI to detect error components in the production process, to help reduce product damage. In logistics, AI predict transportation needs, the optimal delivery route, save fuel and time.

Real value for business:

• Reduce production costs, limit waste materials.
• Increase performance line, ensure the quality of the product evenly.
• Shorten the delivery time, improve the satisfaction of customers.

2.9. Content creation and Generative AI

In the field of marketing communications, management, commissioning, Generative AI bring creative possibilities excel. AI can write content, advertising, compose email, customer care, create business reports, even aided design photos, videos.

For example: The company communication technology has application AI to shorten the production time content from several days down to just a few hours. HubSpot is a platform global marketing has integrated AI to support marketer write blog posts and email marketing help save up to 30% of the time to deploy campaigns.

Real value for business:

• Speed up the deployment media campaign, marketing.
• Reduce the cost of rent or creative resources internal.
• Ensure consistency in content, at the same time easy to customize according to each target customer group.

3. Actual benefits businesses receive when the application AI

3.1. Increase performance, reduce costs

One of the values most pronounced when the application AI in business is the ability to increase the working performance. AI will help automate the repetitive tasks like data entry, document check or handle email. Not only does this reduce the load for employees, but also to limit errors due to human causes.

For example, a logistics company can use AI to automatically optimize delivery routes help shorten the shipping time, reducing fuel costs. With business, this means saving hundreds to thousands of hours of work each year, at the same time reduce operating costs significantly.

3.2. A decision fast more accurate

AI does not replace humans in decision-making, but it is powerful tool to help leaders have accurate data to predict trends in risk reduction. Machine learning algorithms can analyze the data volume is huge market, customer behavior or performance to take out the forecast.

For example, in the retail industry, AI predict demand for seasonal merchandise, help businesses proactively source, avoid excess inventory. This helps managers reduce dependence on subjective judgements, thereby improving the accuracy in the strategic decisions.

3.3. Improve customer experience, increase revenue

Customers today expect fast service, personalization and are available 24/7. AI help businesses meet this expectation through the chatbot, virtual assistant, the hint system smart.

For example, the chatbot can support the customer immediately when they need to be answered, instead of having to wait for support staff. In the field of e-commerce, AI analysis of shopping behavior to put out product suggestions, accordingly, increase the ability to convert a purchase. In fact, Amazon has said that more than 35% of their sales come from the hint system based on AI – clear proof for business value from this technology.

3.4. Innovation, enhance competitive advantage

Application AI not only help businesses operate more efficiently, but also opens up opportunities, product development, new service. For example, banks can use AI to build scoring systems, auto credit, extension services to customers unprecedented access to finance traditional. Business in the forefront of the operators AI often built photo pioneer, increase brand reputation and create competitive advantage sustainable than the opponent.

3.5. The data demonstrate the value AI

The effect of AI not only be felt through experience, which is also expressed in specific numbers. According to the survey of AWS in Vietnam, among the business has application AI

• 61% reported revenue increased an average of about 16%.
• 58% expected cost savings of about 20%.
  (Source: Vietnam News)

Globally, reported AI Index 2025 of Stanford University found that 78% of organizations already using AI at least in one department or business function (hai.stanford.edu). This proves AI has become an important part in the development of modern enterprise, it is no longer the trend trial.

4. The steps for deploying AI in business (Roadmap)

Step 1. Assess the current state define clear goals

Before investing in any solution AI, businesses need to start by taking a look at ourselves. This includes the analysis of internal processes to determine:

• Where are the stage is spending a lot of time, cost;
• Where are the points need to support decision-making;
• Where is the opportunity to create products, new services, thanks to AI.

For example, a retail business may have noticed predicting inventory needs are often slow to false. AI can help with more accurate forecasts based on historical data and market trends.

Besides, enterprise also need reviews about infrastructure, data and technology are used, human capacity is at to see was ready for the application AI or not.

Step 2. Strategic planning AI

Application AI should not stop at the range each department that needs associated with the strategy of turns the whole business. At this stage, leaders need to clearly define the business goals that will support: increase revenue, reduce costs, optimize customer experience or improve competitiveness.

Business should also be given KPIs specific to measure the effectiveness, such as: the rate of reduction in processing time of customer requirements, the rate of increase accuracy in forecasting revenue.

According to the report of PwC, AI can contribute to to 15.7 trillion to global GDP by 2030 thanks to improving productivity, product innovation (PwC Global AI Report).

Step 3. Select technology partner matching

Businesses can choose the solution on-premise (installed in place, control data closely) or cloud (easy extension, flexible cost). Each model has advantages and disadvantages, depending on the security requirements and budget of each business.

In addition, enterprises need to consider between the self-developed internal or partnered with the solution provider AI. With business not to have a team of strong technology, the cooperation with reputable partners will help save deployment time, ensure the quality.

Step 4. Test and expand (Pilot → Scale-up)

Start with a test project to help businesses test the feasibility of AI without investing too much right from the start.

For example, a financial company can test chatbot AI in customer care, before expanding to the entire channel support.

When the test project is successful, the business can gradually expand into many parts, guaranteed AI actually creates values before large-scale investment.

Step 5. Ensure the administration, security, ethical, legal compliance

AI only truly sustainable when deployed come with the frame data administration closely. Enterprises need to build a process to ensure data is secure, transparent, non-biased, and comply with legal regulations, industry standards.
For example, in the financial sector – banks, AI must comply with the rules on security of personal data and the prevention of money laundering. Failure to comply could lead to legal risk, loss of reputation brand.

Step 6. Personnel training, culture change

One of the biggest barriers when the application AI is not technology, that is human. Businesses need to implement training programs to raise skill (upskill) and re-training (reskill) for employees so they can work effectively with the new tool.

Besides, internal communications play an important role in the change of the corporate culture. When employees understand that AI is not to replace but rather to support, they will ready to receive, extraction of maximum value from technology.

5. Challenge risk when the application AI in business

5.1. Lack of manpower and skills

One of the biggest barriers that organizations and businesses are finding out information about the application AI in the enterprise are often encountered is the lack of a team of qualified personnel deployment. According to Vietnam News, more than 50% of businesses in Vietnam, said that the biggest difficulty when applying AI lies in the lack of skilled personnel and appropriate professional (Vietnam News).

Fact, to successfully implement a solution, AI, businesses need both skill and technology (data processing, programming, operating system) and skills business analysis (understanding the market, internal processes). This deficiency causes multiple projects AI is prolonged or does not reach the desired results.

5.2. Data and data management

AI only works effectively when is “nourished” by the data sufficiently accurate, well-managed. However, many business Vietnam today is still stored data scattered in many different systems, even data is missing or wrong.

Besides, the security issue, privacy is increasingly important, especially for industries such as finance, health and banking. If the business is not built frame data governance transparency, while ensuring the compliance with the law and maintain trust with customers, then AI is very difficult to develop practical value.

5.3. Investment costs and profitability difficult to measure

Investment in AI is not just in software but also including storage infrastructure, data processing, personnel training, system integration. This is a considerable cost, especially for small and medium enterprises. Greater challenge lies in the accurate measurement ROI (rate of return on investment).

Some of the benefits of AI to improve customer experience or increase the accuracy of forecast generally only evident after a long time, that business leaders, difficult to determine the payback period, the decision to expand investment.

5.4. Ethical issues, legal, faith

AI operate based on algorithms learn from data, which can easily occur deviation (bias) or decision-making lacks transparency. This is especially sensitive in areas such as recruitment, finances or health, where the decision of AI can directly affect humans.

In addition, the legal framework in Vietnam and around the world on data protection, personal responsibility, when people make wrong decisions are still in the process of finishing. Lack of transparency, concerns about privacy may reduce the trust of customers/partners in business when the application AI.

5.5. Organizational culture and change management

AI is not just a technological tool, but also requires a cultural change management. In many cases, the employee concerned AI will replace their jobs, which leads to the resistance with the new project.

To overcome this, businesses need a strong commitment from leadership in the communications clear that AI is support tool, to help people focus on work of higher value. At the same time, need to build a roadmap training to staff ready to adapt to the new working environment.

Application of AI in business has brought enormous benefits, and constantly open up the new development opportunities. From the app AI are in the business to analyze data and assist employees with virtual assistant optimization, management accounting, to the digitization process, approvers, AI showed the ability to improve performance and increase management efficiency. Therefore, businesses need to quickly apply AI to catch new trends, manage risks, a proactive and create momentum for sustainable development in the business environment competitive.

CONTACT INFORMATION:

• Lac Viet Computing Corporation
• Hotline: (+84.28) 3842 3333
• Email: info@lacviet.vn – Website: www.lacviet.vn
• Headquarters: 23 Nguyen Thi Huynh, P. 8, Q. Phu Nhuan, Ho Chi Minh city

Related questions

1. AI help you for business?

AI helps businesses automate processes, optimize operations and improve decision-making abilities. Specific:

• Increase work performance: AI automatically handles recurring task, reduce the load of manual work.
• Data analysis, prediction: AI analysis of big data, make predictions, market trends, financial, customer needs.
• Improve customer experience: AI personalization service customer support 24/7 via chatbot and virtual assistant.
• Enhance security, reduce risks: AI to detect financial fraud, data protection, business.
• Optimization of personnel management: AI recruitment support, assess performance, predict the rate of the holiday.

2. Application of AI in business management?

• Financial management: AI analyze financial statements, forecast cash flows, detect financial risks.
• Customer management (CRM): AI track customer behavior, personalize marketing campaigns.
• Optimized supply chain: AI predict demand goods, optimized logistics, logistics.
• Hr management: AI, process automation recruitment, performance reviews, training support staff.
• Strategic decisions: AI, data analysis, market, business support oriented business strategy.

Source reference information:

• Sizing the prize What's the real value of AI for your business and how can you capitalise?
• The 2025 AI Index Report by Stanford TWO
• Vietnam sees rapid AI growth