Leveraging AI for Business Automation: Specific Tools and Use Cases

AI refers to artificial intelligence technology that autonomously learns from accumulated data and can build its own criteria for judgment. By incorporating AI into business operations, automation of tasks previously done manually becomes possible, leading to improved operational efficiency and increased productivity.

"I want to improve productivity and streamline operations through AI automation."

"I want to reduce the burden on employees caused by labor shortages by introducing AI tools."

"I want to utilize AI but don't know the specific methods."

Many people may be facing such concerns. This article summarizes AI-based automation of business operations, explaining the differences between AI and RPA, their advantages and disadvantages, as well as specific tools. In the latter part of the article, we also provide detailed explanations on the steps to introduce automation, key points for success, and examples of usage in various fields.

If you're interested in AI-based automation, please refer to this article.

Akira Shimazoe

CEO of Solashi Japan LLC. Engaged in the development and operation of internal systems at Suntory. Founded Yper Inc., serving as CTO and CPO, contributing to product launch and growth.

What is AI-driven Business Automation?

To understand AI-driven business automation, let's first explain the basics of AI and its differences from RPA.

Overview of AI

AI (Artificial Intelligence) refers to artificial intelligence. AI learns from given data and constructs its own criteria for judgment based on the insights gained. This autonomous learning and judgment are the key strengths of AI.

AI is primarily classified into two types:

• Specialized AI…Capable of learning, processing, and making judgments for specific problems.
• General AI…Capable of learning, processing, and making judgments for a variety of problems.

Currently, specialized AI, which includes functions such as image recognition and speech recognition, is practical. On the other hand, general AI has not yet been realized but is expected to be capable of handling a wide range of problems. It is characterized by its ability to apply past knowledge and experience to new situations, much like humans.

Difference from RPA

RPA (Robotic Process Automation) refers to automation of business processes using software robots. Both AI and RPA are technologies used for business automation, but they have significant differences in their characteristics. AI's strength is its ability to autonomously learn from accumulated data and construct its own judgment criteria. In contrast, RPA follows predefined rules for processing and is unsuitable for tasks that require complex judgments. However, RPA is ideal for automating routine tasks.

By combining AI and RPA, effective automation that leverages the strengths of both can be achieved. Therefore, understanding the characteristics of RPA is important when pursuing AI-driven business automation. If you want to learn more about RPA, please check out the article below.

What is RPA automation? Introducing its benefits, capabilities, and use cases

Advantages of AI-driven Business Automation

Here, we introduce the benefits of AI-driven business automation.

• Can streamline business operations
• Leads to long-term cost reduction
• Can accurately predict market demands
• Can enhance decision-making

Let's take a closer look at each of these.

Streamlining Business Operations

By appropriately introducing AI, business operations can be greatly streamlined. AI can process tasks faster than humans and provide real-time analysis. This leads to speeding up operations.

Additionally, AI prevents human errors and reduces the time spent on error handling. Using AI not only in internal operations but also in customer-facing services can lead to increased customer satisfaction and improved revenue.

Leads to Long-Term Cost Reduction

Advances in business automation lead to the optimization of human resources in the long term. For example, by automating routine tasks that can be replaced by AI, human resources can be redirected to more advanced tasks.

Furthermore, as the workload is reduced through automation, surplus resources become available for employees. These surplus resources can be allocated to important tasks that only humans can perform, which is a significant advantage. This can lead to skill development for employees and greater focus on more creative tasks.

Accurately Predict Market Demands

By utilizing AI, companies can accurately grasp market and customer demands. AI is excellent at identifying patterns from large amounts of data and predicting customer behavior and preferences. This enables companies to identify areas for improvement in products and services, and make proposals that align with customer needs.

Being able to respond more precisely to customer demands will lead to higher satisfaction. As a result, it will also contribute to enhancing the company's brand image and competitiveness.

Enhances Decision-Making

By using AI, companies can quickly extract meaningful information from vast amounts of data and use it for future predictions and strategic planning. AI can easily identify correlations and trends that humans might overlook. Data-driven decisions become possible, leading to improvements in the quality of management.

Disadvantages of AI-driven Business Automation

While AI-driven business automation offers many advantages, it is also important to understand the potential disadvantages before implementation. The disadvantages of AI-driven business automation are as follows:

• High implementation costs
• Need for AI talent
• Requires risk management

Let's discuss each of these in detail.

High Implementation Costs

To introduce AI, initial costs such as the purchase cost of hardware and software, system construction costs, and data organization costs are required. These costs vary greatly depending on the scale and complexity of the tasks to be automated, as well as the degree of integration with existing systems. For small and medium-sized enterprises, the burden of initial investment can be large, which may be a factor in hesitating to introduce AI.

Furthermore, the effects of AI implementation appear over the long term, so seeking short-term revenue improvement may result in no return on investment. Investment decisions for AI require a medium- to long-term perspective. It is important to carefully consider the effects such as operational efficiency and cost reduction and to create an appropriate investment plan that fits the company.

Need for AI Personnel

To effectively utilize AI, it is essential to secure personnel who can properly operate and manage the system. Even if AI is introduced, if there are no skilled personnel to operate it, the desired effects cannot be achieved. If your company lacks personnel with AI skills, new recruitment will be necessary.

In such cases, utilizing external resources is also an effective option. By outsourcing tasks to AI experts or vendors, you can reduce the costs associated with securing and training personnel in-house. Additionally, by obtaining external knowledge and expertise that your company lacks, more effective automation of operations can be achieved.

At our company, Solashi, we have many engineers who are experts in advanced technologies like AI. We can listen to your challenges and propose the optimal system development utilizing AI. If you are interested, feel free to contact us.

Risk Management is Necessary

AI is an advanced system, but it is not perfect. Due to the limitations of machine learning and unforeseen circumstances, there is always the possibility of unexpected malfunctions. Therefore, risk management based on the assumption of AI malfunctions is essential.

For example, it is necessary to establish systems to detect AI decision-making errors early, and to develop procedures for responding to errors. It is important to prepare measures to minimize the impact of malfunctions on business.

Additionally, it is important to define AI operation rules in advance, such as how much decision-making is entrusted to AI and who will make the final decisions.

5 AI-based Business Automation Tools

By utilizing AI, it is possible to automate various tasks. Here are five representative AI business automation tools.

• Chatbot
• Automated phone response system
• AI OCR
• Facial recognition system
• Anomaly detection

Chatbot

Chatbots are AI systems that respond to user inquiries on websites or apps. The AI analyzes the text entered by the user and automatically replies with an appropriate response based on the content.

For example, by implementing a chatbot in customer support, AI can automatically answer user questions that were previously handled by humans. This reduces human labor costs while enabling 24/7 support.

Additionally, chatbots can support multiple languages, making them particularly effective tools for companies expanding globally.

Automated Phone Response System

An automated phone response system is a system in which AI automatically answers calls from users. Like chatbots, it is used in customer support and similar functions.

The key feature of this system is that AI can recognize the user's voice and provide appropriate responses verbally. It can handle not only pre-set options but also free-form responses, such as asking for a user's name or date to process reservations.

AI OCR

AI OCR is a system that combines AI with Optical Character Recognition (OCR). It automatically reads text from paper documents or images and converts it into text data.

Traditional OCR could only recognize characters based on predefined patterns. However, by integrating AI, more accurate recognition is now possible. It can handle handwriting, process large volumes of documents, and analyze complex layouts. This improves efficiency and reduces errors in tasks that are time-consuming and prone to mistakes when done manually.

If you want to learn more about OCR, check out this article:

What is OCR development? Here are 13 recommended system development companies and tips for choosing the right one.

Facial Recognition System

A facial recognition system automatically recognizes a person's face from camera images and verifies their identity. The AI analyzes features such as the position and size of the eyes, nose, and mouth, and compares them to pre-registered facial data to determine whether the individual is who they claim to be.

Facial recognition systems are used in access control and identity verification in financial institutions and various other fields. Since users no longer need to enter passwords or carry physical items, convenience is significantly improved. Additionally, it offers security benefits by reducing the risk of impersonation.

Anomaly Detection

Anomaly detection systems are used in quality control on production lines and detecting equipment failures, among other applications. The system learns from large amounts of normal data to recognize patterns of normal behavior. It then analyzes real-time data to automatically detect anomalies or suspicious signs.

Anomaly detection systems can detect even subtle changes that humans might miss, making a significant contribution to improving quality control and preventing potential issues. Furthermore, they offer the advantage of 24/7 monitoring, ensuring stable anomaly detection without human error.

5 Steps to Automate Operations Using AI

Now, let's go over the steps to automate operations using AI. The process toward automation is as follows:

1. Identify the business workflow
2. Select processes for automation
3. Choose tools
4. Test run
5. Full-scale operation

Let's go over each step in detail.

1. Identify the Business Workflow

The first step in automating business operations is to carefully identify and visualize the current business workflow. List each task and use flowcharts or similar tools to make the workflow visible. This will allow you to get a comprehensive view of the entire process, making it easier to identify areas that can be automated.

2. Select Processes for Automation

Based on the visualized workflow, select the processes that are suitable for automation. Use the automation tools mentioned earlier as a reference to identify the tasks where AI substitution can have a high impact.

Start with tasks that are easiest to automate and offer significant benefits. It is difficult to automate entire business processes all at once, so check individual tasks and see if automation is possible for any of them.

Additionally, in some cases, combining AI with RPA (Robotic Process Automation) can lead to more effective automation. For example, RPA can automate repetitive data entry, while AI can support decision-making based on the analysis results.

At Solashi, we listen to our clients' business needs and propose optimal system development using AI and RPA. We have experience in developing systems that combine AI and RPA, so feel free to reach out if you're interested.

3. Choose the Right Tools

Once you've selected the processes to automate, it's time to choose the right tools. When selecting automation tools, it is crucial to consider not only cost but also features, ease of use, and integration with existing systems.

Specifically, consider the following points:

• Does it have the necessary features?
• Is the user interface intuitive and easy to use?
• Can it integrate with existing systems and tools?
• Does the cost of implementation and operation fit within the budget?
• Is the support system robust?

It is important to comprehensively evaluate these points and choose the tool that best suits your company's needs. We recommend carefully comparing multiple tools and, if necessary, setting a trial period to guide the selection process.

4. Trial Operation

When introducing a new tool, it is crucial not to deploy it company-wide immediately but to start with a limited trial operation. Apply the tool to specific departments or tasks and verify its effectiveness and challenges in actual operations.

Based on insights gained from the trial operation, improvements in tool settings and operational methods should be made. Actively gather user feedback and strive to enhance usability. Additionally, measure the quantitative effects of automation and use these insights to decide on full-scale deployment.

Once sufficient improvements have been made and the tool is confirmed to be suitable for the operations, proceed to full-scale deployment.

5. Full-Scale Operation

After clearing the challenges in the trial operation, it's time to move on to the full-scale automation phase. Design new business processes incorporating AI tools and deploy them across the entire organization.

It takes time to stabilize automated workflows. Especially in the initial phase, closely monitor operations to check system behavior and business quality.

Moreover, continuous improvement is essential even after full-scale operation. Using insights gained from daily operations, enhance automation accuracy while iterating the PDCA cycle. Listening to feedback from the field is crucial for optimizing business processes.

Key Points for Successfully Automating Business Operations with AI

The following summarizes key points for successfully automating business operations with AI.

• Clarify the purpose of automation
• Select tasks suited for AI
• Start with small-scale automation
• Be mindful of cost-effectiveness

Let's explain each of these points in detail.

Clarify the Purpose of Automation

Before starting an AI automation project, it's essential to clarify the purpose of automation. Set specific goals such as cost reduction, quality improvement, and reducing employee burdens.

If the purpose is unclear, the direction of the project will be undefined, and alignment among stakeholders will be difficult. By clarifying the goal of automation, the project can progress smoothly.

Select Tasks Suited for AI

To ensure successful AI automation, it's also important to select tasks that are suitable for AI.

AI excels at pattern recognition from large datasets and processing information at high speeds, but it struggles with comprehending situations as comprehensively as humans and making flexible decisions. Therefore, routine tasks that can be somewhat standardized are more suitable for AI.

Break down the workflow and identify tasks where AI can be most effective. Additionally, for tasks that are too complex for AI alone, consider combining AI with other automation tools such as RPA or collaborating with humans. It's essential to understand the characteristics of AI and apply it appropriately.

Start with Small-Scale Automation

When implementing automation, it's best to start with a small-scale approach rather than automating all tasks at once. By gradually advancing automation, you can minimize confusion at the workplace and its impact on operations.

Based on the insights gained from the small-scale trial, gradually expand the scope of automation. During this process, it is particularly important to listen to feedback from on-site employees regarding the usability of the tools and their proficiency with new workflows. This helps create a more effective and user-friendly system.

Be Mindful of Cost-Effectiveness

Introducing AI requires investment not only in initial costs but also in operational costs and training costs, among other expenses. Therefore, it is necessary to evaluate the medium- to long-term cost-effectiveness and make investment decisions accordingly.

Before implementation, try to quantify and estimate effects such as "labor cost reduction through reduced work hours" or "quality improvement through reduced errors."

While AI implementation may result in temporary cost increases, it holds potential for long-term improvements in productivity and enhanced competitiveness. It is important to make decisions not only based on short-term return on investment but also with a focus on future returns.

Examples of AI Utilization in Business Automation

Finally, here are specific examples of how AI can be utilized in business automation. We've categorized them by industry and field, so please refer to those that may be relevant to your business.

• Manufacturing Industry
• Delivery Industry
• Healthcare Industry
• Agriculture

We will now explain each of these examples.

Manufacturing Industry

The manufacturing industry faces various challenges such as labor shortages, an aging workforce, and intensified global competition. In this context, business automation using AI can lead to improvements across a wide range of areas, including productivity enhancement, advanced quality control, and the transfer of skilled techniques. AI can drive improvements in many aspects of the manufacturing process.

【Productivity Improvement & Efficiency】

• Abnormality detection within processes
• Optimization of equipment operation and workforce allocation
• Automation and efficiency improvement of design processes
• Data conversion of handwritten forms
  

【Quality Control】

• Identification of defect causes
• Improved product traceability
  

【Skill Transfer & Human Resource Development】

• Reproduction of the know-how and techniques of skilled workers
• Support for training new technicians
  

【Safety Measures & Work Environment Improvement】

• Monitoring of restricted areas

【Data Utilization & Analysis】

• Collection and analysis of IoT and sensor data
• Simulations using digital twins

Delivery Industry

In the delivery industry, business automation using AI is advancing to cope with the increased handling volume driven by the expansion of the e-commerce market. AI has been introduced for tasks such as picking, inspection, and document processing in warehouses to improve efficiency and quality. Additionally, AI is used for sleep detection systems, route optimization, and demand forecasting during deliveries, thereby enhancing both safety and efficiency.

【Operational Efficiency】

• Autonomous operation of forklifts
• Automatic inspection systems
• Automation of document processing
  

【Safety Measures & Work Environment Improvement】

• Detection of sleepiness signs

【Data Utilization & Analysis】

• Route optimization for deliveries
• Forecasting delivery workloads

Healthcare Industry

In healthcare, the use of AI is accelerating to ensure patient safety and improve the quality of medical care. AI is contributing to business efficiency and medical advancement through systems like patient monitoring, automated interview systems using chatbots, and image diagnostic support. It is expected that with the increasing use of medical data, the scope of AI applications will expand even further in the future.

【Operational Efficiency】

• Patient monitoring systems
• Chatbot
• AI-based online diagnostics and automated interview systems
  

【Improving Medical Quality】

• Automatic image capture and detection of abnormalities in diagnostic images
• Analysis of medical records
• Manufacturing of high-performance medical equipment

Agriculture

In the agricultural sector, smart farming using AI and robotics is continuing to develop in response to labor shortages and an aging population. AI is being used to visualize growth conditions, automate pesticide spraying, and forecast demand, contributing to increased productivity and stabilized quality.

In an industry facing severe labor shortages, AI will play an increasingly important role as a reliable solution to supplement human resources.

【Improving Productivity & Efficiency】

• Automation of harvesting and sorting tasks
• Automated pesticide spraying
  

【Data Utilization & Analysis】

• Adjustment of shipment volume
• Forecasting the risk of pest and disease outbreaks
• Optimization of pesticide spraying

Consult Solashi for AI-based Business Automation

We have discussed the overview, benefits, and key points for successfully implementing AI-based business automation. When effectively utilized, AI can lead to significant cost reductions and profit increases. However, if your company lacks expertise in AI, selecting the right tools and developing the appropriate systems might be challenging.

In such cases, it's crucial to consult with a development company that can listen to your challenges and propose optimal development plans.

For AI-driven business automation, trust the cost-effective and high-quality system development services from the Vietnamese development company Solashi Co., Ltd. We offer high-quality systems while keeping costs low, and our engineers are well-versed in cutting-edge technologies, supporting everything from B2B to B2C industries.

We will propose the optimal project size based on your business plans and aim to optimize your IT investment. From short-term technology verification projects to long-term main development, we can accommodate flexible development schedules and frameworks.

If you're facing challenges with AI-based business automation, feel free to contact Solashi. We will assist you in streamlining your operations with system development aligned with your business strategy.

Akira Shimazoe

Representative of Solashi Japan LLC. Born in April 1989 in Fukuoka Prefecture. Graduated from the Graduate School of Information and Mathematical Sciences at Osaka Prefecture University. Joined Suntory System Technology Co., Ltd., an IT subsidiary of Suntory Holdings, in 2014. Broadly responsible for the development, operation, and implementation of vending machine delivery management, efficiency improvements, and sales management systems. Founded Yper Inc. in 2017, serving as CTO and CPO. Contributed to the launch and growth of the app-linked delivery bag "OKIPPA." Selected for Toyo Keizai's prestigious "Amazing Venture 100" and Forbes' "Forbes 30 Under 30 Asia 2019."