While more companies leverage AI (artificial intelligence) in their business, many still struggle to understand its specific applications, hindering widespread adoption. Even if they consider leveraging AI, without a clear understanding of its mechanisms and potential capabilities, they struggle to come up with ideas for integrating it into their operations.
Leveraging AI will become essential for business expansion. This article reviews the basic structure of AI and provides detailed explanations, including examples of business applications, tips for improving business efficiency, and insights into how AI will evolve and will meet the needs of the business.
Demystifying AI: reviewing the basics
Popular culture often presents AI as computer systems that exceed human capabilities to solve myriad problems or as the types of robots we see in animated films.
However, a universal AI like the one described above does not yet exist, and there are limits to what AI can do. First of all, let’s check the basic knowledge, such as the definition and structure of AI.
Define AI
The term AI has been around since the mid-1950s, when commercial computing development exploded. But even though technology has since progressed by leaps and bounds, there is still no clear definition of AI.
Nevertheless, people widely use and recognize this term. They generally understand it as a mechanism or technology that recognizes human speech, reproduces human perceptions and capabilities, and performs reasoning and problem solving based on varied information. AI is essentially artificially developed intelligence.
The basics of AI
AI understands spoken language, replicates perceptions and abilities, and performs reasoning and problem solving using mechanisms much like how humans learn language and process information from images and images. videos.
In other words, by accumulating experience and learning from large amounts of data, AI can understand words and interpret images and videos. The key concepts here are machine learning and deep learning.
Machine learning
Machine learning involves loading huge volumes of data into computers and allowing AI to learn patterns and features that distinguish different types of data.
For example, if presented with an image of a dog and another of a cat, the AI cannot independently determine which is which. By telling the computer various characteristics such as body size, nose and ear shape, and coat length, the AI can learn to distinguish whether the animal is a dog or a cat.
Deep learning
With deep learning, a computer identifies features and learns on its own instead of relying on human instructions as in traditional machine learning.
By processing hundreds or thousands of images of dogs and cats, AI can independently extract and identify features such as body size, nose and ear shape, and coat length, without the need for specific human advice. The data used in this process is called training data. The more training data provided, the more accurate the AI becomes.
The latest five business applications of AI
AI is becoming more and more integrated into society and the business world. Here are some key examples of AI applications in various fields:
1. Finance: Predicting Stock Prices
Stock traders make decisions based on various pieces of information, including company performance, industry trends and historical valuations. Traditionally, traders gather this information and select investments based on their knowledge, experience and intuition. However, recently, services have emerged that use AI to predict stock prices.
2. Health care: cancer imaging
Cancer is one of the leading causes of death. The best defense is early detection through frequent screenings. However, the small tumors characteristic of early-stage cancers can be difficult to detect in tests. Using AI to diagnose cancer at these early stages would help specialists more easily identify abnormalities that might otherwise go unnoticed, leading to earlier treatment.
3. Construction: supporting risk forecasting activities
Construction sites are inherently dangerous, so the risk of death increases during major disasters. Site management teams mitigate these risks by undertaking hazard forecasting activities before commencing work.
This process involves anticipating potential dangers and deploying countermeasures. However, identifying specific examples can be time consuming and difficult. Risks may escape attention if people do not sufficiently understand disaster prevention measures. Some construction companies use AI, which learns from numerous incidents to better predict and prepare for them.
4. Energy: predict and optimize electricity supply
The demand for electricity, which is essential, fluctuates depending on the time of day, season and day of the week. Utilities cannot store it like gas or water and must transmit it quickly for instant consumption. Balancing supply and demand is essential to stabilize electricity availability.
New services have emerged that use AI to analyze electricity demand records, energy market prices, weather information and other data to forecast demand. This capability enables highly accurate power forecasts and promotes rational, waste-free planning of power generation.
5. Logistics: volume forecast
Labor shortages and growing demand for e-commerce are putting enormous pressure on the logistics sector. People have relied on logistics companies to forecast shipping volumes and properly allocate vehicles and personnel.
Some companies are using AI to learn from logistics records, climate, dates and other information to automatically project these volumes.
Insights into leveraging AI applications that can streamline operations
People tend to view AI as an asset to solving key business problems. In fact, AI can help improve routine operations. This article will discuss operations streamlining techniques and their prospects while exploring the potential of AI.
Customer Service Center Chatbot Support
Customer service centers and help desks handle significant traffic of inquiries every day and have typically tasked carriers with providing answers. Most requests are routine, like confirming billing charges or resetting passwords.
AI-powered chatbots can automatically evaluate requests and present appropriate options and solutions. This can significantly reduce operator workload and labor costs and improve customer satisfaction by reducing inquiry times.
Conduct contractual due diligence
Contracts with business partners can present unexpected legal risks and significant problems. Due diligence is essential to prevent such problems and requires legal expertise.
AI can acquire such knowledge. There are services that allow AI to check contract risks and detect parts requiring revision or identify omissions of required items.
Writing professional emails
Writing emails that convey the right content and tone to customers and business partners can take a surprising amount of time. When handling complaints or grievances, it is particularly important to choose wording that does not upset the recipients.
Services are already available that allow users to simply enter the content or keywords they want to convey and let AI automatically create text-matching business situations. Even new employees or people unfamiliar with business email can create tailored messages.
Improve multinational communication
An increasingly interconnected world provides businesses with more opportunities to communicate with foreign customers, business partners and other stakeholders. AI-based translation and interpreting services are attracting particular attention in this regard.
Even though many online services and applications support foreign language translation, the result does not always convey intentions accurately and the choice of words can often seem strange.
As AI natural language processing becomes more precise, it will become possible to accurately and naturally translate text in foreign languages and convert it into multiple languages in real time during video and voice calls without having to need the help of interpreters. This will make it easier for everyone to communicate with people around the world and cultivate international business opportunities.
Harnessing Generative AI to Streamline Tasks
Generative AI can create text, images, audio, video, programs, and other content. It can rely on large databases to respond to prompts.
A famous example of generative AI is ChatGPT, developed by the American company OpenAI. ChatGPT is a so-called “text generation model/natural language processing model” that can generate sentences that appear to have been written by a human, using a learning model trained on a large amount of data .
Generative AI is essential for streamlining business operations, especially with chatbots and the due diligence capabilities mentioned previously. How internal company information can be integrated into generative AI and how to create methods to achieve this are important questions for the future.
Solving Workplace Problems with AI
The large-scale use of AI in a business environment is still in its infancy. Few companies have made it an essential part of improving productivity or new business models.
Ricoh understands workplace challenges and is committed to creating value by developing and deploying the optimal AI solutions.
Supervising Editor
Masatoshi Mori
Mr. Mori received his Ph.D. in engineering from the University of Tokyo. He is a professor at the Faculty of Economics and Business Administration at Saitama Gakuen University, where he helps companies improve their operational efficiency. He has been researching AI-driven efficiency improvements for nearly a decade. In 2023, he draws on his extensive research to publish Accelerating the Development of Generative AI Services to Support Business Innovation: Improving Operational Efficiency through ChatGPT and Bard.
