While more companies are leveraging AI (artificial intelligence) in business, many still struggle to understand its specific applications, hindering widespread adoption. Even if they consider tapping into AI, without a clear grasp of its mechanisms and potential capabilities, they find it challenging to generate ideas for integrating it into their operations.

Harnessing 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 serve business needs.

Demystifying AI: Reviewing the Basics

Popular culture often portrays AI as computer systems that surpass human capabilities in solving 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, let’s check the basic knowledge, such as the definition and structure of AI.

Defining AI

The term AI has been around since the mid-1950s when commercial computer development rocketed. But while technology has since progressed by leaps and bounds, there remains no clear definition of AI.

Nonetheless, people widely use and recognize the term. They generally understand it as a mechanism or technology that recognizes human speech, replicates human perceptions and abilities, and performs reasoning and problem-solving based on varied information. AI is essentially artificially developed intelligence.

The Basics of AI

AI understands spoken language, reproduces perceptions and abilities, and performs reasoning and problem-solving using mechanisms a bit like how humans learn language and process information from images and videos.

In other words, by accumulating experience and learning from vast amounts of data, AI can comprehend words and interpret images and videos. The key concepts here are machine learning and deep learning.

Machine Learning

Machine learning entails loading massive volumes of data into computers and enabling AI to learn patterns and features that distinguish different data types.

For example, if presented with an image of a dog and another of a cat, AI cannot independently determine which is which. By instructing the computer on various characteristics like body size, nose and ear shapes, and fur 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 by itself instead of relying on human instructions as in traditional machine learning.

By processing hundreds or thousands of images of dogs and cats, the AI can independently extract and identify features such as body size, nose and ear shapes, and fur length, without needing specific human guidance. The data used in this process is called training data. The more training data provided, the more accurate the AI becomes.

The Top Five Latest Business Applications of AI

AI is increasingly integrating into society and the business world. Here are some key examples of AI applications across various fields:

1. Finance: Forecasting Share 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. Recently, however, services have emerged that use AI to predict share prices.

2. Healthcare: Cancer Imaging

Cancer is a leading cause of death. The best defense is early detection through frequent screenings. However, tiny tumors characteristic of early-stage cancers can be challenging to detect in tests. Using AI to diagnose cancer at these early stages would help specialists to more easily identify abnormalities that might otherwise get under the radar, leading to earlier treatment.

3. Construction: Supporting Hazard Prediction Activities

Construction sites are inherently dangerous, so fatality risks surge during major disasters. Site management teams mitigate these risks by undertaking hazard prediction activities before commencing work.

This process involves anticipating potential hazards and deploying countermeasures. However, identifying specific examples can be time-consuming and challenging. Risks may escape attention if people lack sufficient understanding of disaster prevention measures. Some construction firms thus tap AI, which learns from numerous incidents to better predict and prepare for hazards.

4. Energy: Predicting and Optimizing Electricity Supply

Demand for all-important electricity fluctuates according to the time of day, season, and day of the week. Utilities cannot store it like gas or water and must promptly transmit it for instant consumption. Balancing supply and demand is essential to stabilize power availability.

New services have emerged that utilize AI to analyze electricity demand records, energy market prices, weather information, and other data to forecast demand. This capability enables highly accurate power supply forecasts and promotes rational, waste-free power generation planning.

5. Logistics: Forecasting Volumes

Labor shortages and increased e-commerce demand are putting enormous pressure on the logistics sector. People have relied on logistics firms to forecast shipping volumes and properly allocate vehicles and personnel.

Some companies use AI to learn from logistics records, climate, dates, and other information to automatically project these volumes.

Prospects from Leveraging AI Applications that Could Streamline Operations

People tend to consider AI as a trump card for resolving key business issues. In truth, AI can help improve routine operations. This article will discuss techniques for streamlining operations and prospects for them while exploring the potential of AI.

Customer Service Center Chatbot Support

Customer service centers and help desks handle heavy inquiry traffic every day, and have generally tasked operators to provide responses. Most inquiries are routine, such as confirming billing charges or resetting passwords.

AI-powered chatbots can automatically evaluate inquiries and present suitable options and solutions. This can slash operator workloads and labor costs and enhance customer satisfaction by cutting inquiry times.

Conducting Contractual Due Diligence

Contracts with business partners can present unexpected legal risks and considerable trouble. Due diligence is vital to prevent such issues and requires legal expertise.

AI can acquire such knowledge. There are services that enable AI to check contractual risks and detect parts needing revision or identify omissions of required items.

Drafting Business Emails

It can take a surprising amount of time to draft emails conveying the right content and tone to customers and business partners. When handling complaints or grievances, choosing wording that does not upset recipients is particularly important.

Services are already available that let users simply enter the content or keywords they wish to convey and have AI automatically craft text-matching business situations. Even new employees or individuals unfamiliar with business emailing can create suitable messages.

Enhancing Multinational Communication

An increasingly interconnected world is affording more opportunities for companies to communicate with overseas customers, business partners, and other stakeholders. AI-based translation and interpretation services are attracting particular attention in that regard.

While many online services and applications support foreign language translation, the output does not always convey intentions accurately, and word choices can often seem strange.

As AI’s natural language processing becomes more accurate, 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 needing assistance from interpreters. This will make it easier for anyone to communicate with people everywhere and cultivate international business opportunities.

Harnessing Generative AI to Streamline Tasks

Generative AI can create text, image, audio, video, programs, and other content. It can draw on large databases to respond to prompts.

A famous example of a 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 look like they were written by a human, using a learning model trained on a large amount of data.

Generative AI is essential to streamline corporate operations, including with the chatbots and due diligence capabilities mentioned earlier. How internal company information can be incorporated into generative AI and how to create methods for doing so are important issues for the future.

Resolving Workplace Issues with AI

The full-scale use of AI in a business setting is still in its infancy. Few companies have made it a core component for productivity improvements or new business models.

Ricoh understands the challenges of the workplace and is committed to delivering value by developing and deploying the optimal AI solutions.

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