Differences Between AI and IT: A Comprehensive Explanation of Their Characteristics and Relationship with IoT and DX

AI and IT: A clear understanding of two often confused concepts

AI (artificial intelligence) and IT (information technology) are both indispensable technologies in modern society, but their meanings and roles are very different. AI is a technology that imitates human intelligence, while IT is a technology for processing and transmitting information.

In this article, we will clarify the differences between AI and IT, and provide a detailed explanation of the characteristics of each technology, their roles in business, and their relationship with IoT and DX. By deepening your knowledge of these topics, you will be able to correctly understand AI and IT and use them more effectively in business and everyday life.

What is AI (Artificial Intelligence)?

AI is an abbreviation for Artificial Intelligence, and is a general term for technology that mimics human intelligence and enables computers to perform intellectual activities such as learning, inference, and judgment. AI can be divided into “specialized AI” that performs specific tasks, and “general-purpose AI” that can perform a variety of tasks like humans.

Definition of AI and historical background

The origins of AI research date back to the 1950s. The “Turing test” proposed by Alan Turing was a test to determine whether a machine could behave intelligently enough to be indistinguishable from a human, and played an important role in defining the concept of AI.

The term “artificial intelligence” was first used at the Dartmouth Conference in 1956, marking the start of full-scale AI research. Since then, AI research has developed with ups and downs, and is currently in its third AI boom.

• First AI boom (1950s to 1960s): Basic AI techniques such as inference and search were developed, but due to the limitations of computers at the time, they were unable to solve complex problems.
• Second AI boom (1980s to 1990s): Expert systems, a type of AI that incorporated specialized knowledge in specific fields into computers, were developed, but the boom came to an end due to the difficulty of representing knowledge and limitations in responding to changing situations.
• The Third AI Boom (2010s to present): With the advent of machine learning, especially deep learning, AI has made great strides. AI that exceeds human capabilities in fields such as image recognition, natural language processing, and voice recognition is being developed one after another.

Main AI technologies

There are a wide variety of technologies to realize AI, but here we will introduce some of the most representative technologies.

• Machine learning: A technique that allows computers to learn from data and discover patterns and regularities. There are various learning methods, including supervised learning, unsupervised learning, and reinforcement learning.
• Deep learning: A type of machine learning that uses neural networks that mimic the neural circuits of the human brain to learn more complex patterns. It has demonstrated high performance in a variety of fields, including image recognition and natural language processing.
• Natural language processing: A technology that enables computers to understand and process human language. It is applied to a variety of tasks, including machine translation, text generation, and sentiment analysis.
• Image recognition: A technology that enables a computer to recognize what is in an image or video. It is applied to a variety of tasks, including facial recognition, object detection, and image classification.
• Speech recognition: A technology that enables a computer to recognize human speech. It is used in a variety of applications, including voice assistants, voice input, and voice search.

What AI is good at and what it’s not good at

AI can process large amounts of data quickly and recognize complex patterns, making it good at tasks such as data analysis, prediction, and optimization.

On the other hand, AI is not good at tasks based on human sensibility and values, such as creativity, emotional understanding, and ethical judgment. It can be said that humans still outperform AI in these tasks.

What is IT (Information Technology)?

IT is an abbreviation for Information Technology, a general term for technology that handles information digitally. It refers to all technologies related to information processing and communication, such as computers, software, networks, and databases. IT is the fundamental technology that supports business and daily life in modern society, and its evolution has greatly changed our lives.

Definition and scope of IT

IT broadly includes the following technologies:

• Hardware: This refers to physical devices used to process and transmit information, such as computers, smartphones, servers, and network equipment.
• Software: This refers to the programs and applications that make a computer work. There are various types of software, such as operating systems (OS), office software, web browsers, and game software.
• Network: A technology for connecting computers and communicating data. There are various types of networks, including the Internet, LAN (Local Area Network), and WAN (Wide Area Network).
• Database: A system for efficiently storing and managing large amounts of data. Various types of data, such as customer information, product information, and sales data, are stored in the database.

The role of IT and its contribution to business

IT plays the following roles in business and contributes to the growth of a company.

• Business efficiency: By introducing IT tools and systems, you can automate and streamline business operations. For example, accounting software and ERP (Enterprise Resource Planning) systems can streamline accounting and inventory management tasks and reduce human error.
• Automation: Using technologies such as RPA (Robotic Process Automation), routine tasks can be automated, freeing up employees to focus on more creative tasks.
• Information sharing: By utilizing tools such as intranets and groupware, you can promote information sharing within the company, improving work efficiency and stimulating communication.
• Communication: By utilizing tools such as email, chat, and web conferencing, you can communicate regardless of time or place. This will improve work efficiency and enable global business expansion.

The relationship between IT and digitalization

IT is the technology that underpins digitalization. Digitalization is the process of converting information into digital data so that it can be processed by computers. Digitalization makes it easier to store, search, share, and analyze information, leading to greater efficiency and innovation in various areas of business and society.

For example, digitizing paper documents makes them easier to search and share, and reduces costs by going paperless. Digitalizing music and video content also allows content to be shared with people around the world via the Internet.

A thorough comparison of
the differences between AI and IT

Although AI and IT are
both types of information technology, their technical characteristics and roles
in business are significantly different. Here, we will thoroughly compare the
differences between AI and IT and explain the key points for correctly understanding
each technology.

Technical differences

●     
AI is part of IT: AI is
realized by utilizing IT technology. The software to realize AI runs on a
computer and transmits and receives data through a network. In other words, AI
can be said to be a technology that is an extension of IT technology.

●     
Learning and evolving: The defining feature of AI is its ability to learn from data and
evolve autonomously, whereas IT operates exactly as programmed by humans and
does not learn on its own.

●     
Differences in purpose: AI aims to mimic human intelligence and automate intellectual
tasks, whereas IT is a tool for processing and transmitting information and
does not directly mimic human intellectual activities.

Different business roles

●     
Role of AI: AI plays various roles
in business including decision support, predictive analytics, automation,
personalizing customer experience, etc. For example, AI can analyze customer
data to predict purchasing behavior or automate customer interactions as
chatbots.

●     
The role of IT: IT plays a fundamental
role in business, including infrastructure construction, system development,
data management, security measures, etc. For example, IT provides the
technology to build corporate websites and internal systems and safely manage
customer data.

Although AI and IT each
play different roles, by linking the two, it is possible to create greater
business value. For example, by reflecting the results of AI analysis in IT
systems, it is possible to automate business processes and personalize customer
experiences.

The relationship between AI, IT, IoT, and DX

AI and IT are closely
related, but they are different concepts. You may also often hear terms such as
IoT (Internet of Things) and DX (digital transformation). These technologies
work together and complement each other to create new value for business and
society. Here we will explain the relationship between AI, IT, IoT, and DX.

What is IoT (Internet of
Things)?

IoT, translated as
“Internet of Things,” is a technology that connects various things
(such as home appliances, automobiles, and factory equipment) to the Internet
and transmits and receives data. IoT devices are equipped with sensors,
cameras, GPS, etc., and can collect data such as temperature, humidity,
location information, images, and audio.

The types of data
collected by IoT are diverse, and the scope of its use is expanding. For
example, in a smart home, by linking IoT home appliances, you can control the
air conditioner or turn off the lights while away from home. In factories, IoT
sensors can be used to monitor the operation status of equipment and predict
breakdowns.

IoT and AI collaboration

IoT and AI are a perfect
combination. New value can be created by using AI to analyze the large amounts
of data collected by IoT devices.

For example, AI can
analyze data collected by IoT sensors in factories to predict equipment
failures and perform maintenance in advance, reducing equipment downtime and
improving production efficiency.

Additionally, in smart
cities, combining IoT sensors that monitor traffic volume and congestion
conditions in real time with AI-based traffic flow analysis can optimize
traffic light control and contribute to easing congestion.

What is DX (Digital
Transformation)?

DX stands for
“business transformation using digital technology.” The aim is to
fundamentally transform traditional business models and business processes
using digital technology, creating new value.

Unlike simple IT
adoption, DX involves company-wide transformation, including corporate culture,
organizational structure, and human resource development. To make DX
successful, it is necessary to consider various elements in an integrated
manner, including not only AI and IT but also business strategy, organizational
management, and human resource development.

AI and IT drive digital
transformation

AI and IT are essential
to promoting DX. AI is the core technology of DX and is used in a variety of
situations, including data analysis, prediction, and automation. Meanwhile, IT
is the infrastructure that supports DX, providing technologies such as cloud
computing, networks, and security.

Collaboration between AI
and IT will accelerate digital transformation. For example, IT systems can
provide personalized services based on customer data analyzed by AI, or
optimize inventory management based on demand predicted by AI.

Case studies of business transformation through collaboration
between AI and IT

The collaboration
between AI and IT is bringing about business transformation in a variety of
industries. Here, we will introduce specific examples in manufacturing, retail,
finance, and medical/healthcare.

Manufacturing

• Automating production lines and improving quality control:
  • Robots equipped with AI are replacing tasks previously performed by humans, and production lines are becoming more automated. In addition, by utilizing AI-based image recognition technology, it is possible to automate the appearance inspection of products and improve the accuracy of quality control.
  • Case study: An automobile manufacturer introduced AI robots to automate tasks such as welding and painting, significantly improving production efficiency. In addition, by introducing an AI-based appearance inspection system, the company improved the detection rate of defective products and reduced quality control costs.
• Predictive maintenance, supply chain optimization:
  • By analyzing sensor data and past failure history, AI can predict equipment failures and enable “predictive maintenance,” which allows for advance maintenance. It can also optimize the entire supply chain through demand forecasting and inventory status analysis.
  • Case study: A manufacturing company introduced a predictive maintenance system using AI to prevent production stoppages due to equipment failures and improve production efficiency. In addition, by optimizing the supply chain using AI, the company was able to reduce inventory costs and shorten delivery times.

Retail

• Demand forecasting, inventory management and price optimization:
  • In retail, AI can be used to analyze historical sales data, weather, seasons, trends, and more to forecast product demand, preventing overstocking and out-of-stocks and maximizing sales while reducing inventory costs.
  • Case Study: A major supermarket chain introduced an AI-based demand forecasting system and succeeded in reducing food waste. This system analyzes past sales data and weather information to predict demand for each product and calculate the optimal order quantity. In addition, by introducing price optimization AI, the company dynamically changes product prices according to competitor prices and market conditions, improving profit margins.
• Personalized Marketing, Recommendation Engines:
  • AI provides a recommendation engine that analyzes customers’ purchase history, browsing history, attribute information, etc., and recommends products and information tailored to each individual customer. This increases customer satisfaction and encourages purchasing.
  • Case Study: An online fashion store introduced an AI-powered recommendation engine to provide personalized product suggestions to each customer, which resulted in increased customer time on the site and improved purchase rates.

Finance

• Fraud Detection, Risk Management and Algorithmic Trading:
  • AI-based fraud detection systems are widely used in the financial industry. AI can learn fraudulent patterns from past fraudulent transaction data and monitor transactions in real time, making it possible to detect fraudulent use early and minimize damage.
  • Case study: A credit card company introduced an AI-based fraud detection system and significantly reduced losses due to fraud. The system uses advanced machine learning algorithms to detect behavior that differs from normal transaction patterns and alerts users to transactions that are likely to be fraudulent.
• Chatbot customer service, personal finance:
  • AI chatbots respond to customer inquiries 24/7 and provide fast and accurate answers, while AI-powered personal finance apps can suggest optimal asset management plans based on customers’ income and expenditures and investment goals.
  • Example:
    • Sumitomo Mitsui Banking Corporation has introduced the AI chatbot “SMBC-GPT” to more efficiently handle customer inquiries.
    • WealthNavi provides an AI-powered robo-advisor service that proposes optimal portfolios based on clients’ investment goals and risk tolerance.

Medical and Healthcare

• Optimizing diagnostic imaging, drug discovery and treatment planning:
  • In the medical field, AI is used in a variety of situations, including image diagnosis support, drug discovery, and optimization of treatment plans. Image diagnosis support using AI can support doctors’ diagnoses and reduce the risk of oversights and misdiagnosis. In addition, drug discovery using AI contributes to shortening the time and reducing the cost of new drug development.
  • Example:
    • AISing develops medical devices that utilize AI, and provides products such as a brain MRI image diagnostic support system that is useful for early detection of cerebral infarction.
    • AlphaFold, developed by the British company DeepMind, is an AI that predicts the three-dimensional structure of proteins with high accuracy, and is expected to be useful in developing new drugs and elucidating the mechanisms of diseases.
• Health management and telemedicine using wearable devices:
  • Wearable devices equipped with AI can collect health data such as heart rate, sleep time, and activity level, helping people understand their health condition and improve their lifestyle. In addition, in remote medical systems, AI can analyze patients’ symptoms, refer them to appropriate medical institutions, and support online medical examinations.
  • Case study: The Apple Watch has the ability to measure heart rate and electrocardiograms, and is said to be useful for health management. In addition, CureApp provides a smoking cessation treatment app that uses AI, and offers a smoking cessation program personalized to each individual’s smoking situation.

others

The collaboration between AI and IT is creating new possibilities in various fields, including agriculture, education, and transportation.

• Agriculture:
  • AI systems are being developed that monitor crop growth and determine the optimal timing for watering and fertilizing, which is expected to increase crop yields and improve quality, while reducing the burden on farmers.
  • Example:
    • OPTiM provides agricultural support services that utilize AI, and is developing a system that automatically diagnoses the growth status of agricultural crops and proposes optimal cultivation management.
• education:
  • The AI-based adaptive learning system provides optimal learning materials and assignments according to the learning situation of each student, thereby increasing students’ motivation to learn and maximizing their learning effectiveness.
  • **Case Study:** Atama Plus runs a cram school that uses AI to provide individualized instruction tailored to each student’s level of understanding. AI analyzes students’ weak areas and provides optimal teaching materials and questions to support efficient learning.
• traffic:
  • AI-based autonomous driving technology is expected to contribute to reducing traffic accidents and easing congestion, while AI-based traffic flow analysis can help optimize public transportation schedules and improve the efficiency of city-wide transportation systems.
  • Example:
    • Waymo is a company that was born out of Google’s self-driving car project and is a leader in the development of self-driving technology.
    • The University of Tokyo is developing an AI-based traffic flow analysis system that can grasp traffic conditions throughout a city in real time and use it for congestion prediction, traffic signal control, and more.

These examples show that the collaboration between AI and IT is bringing about changes in various aspects of our lives and society. AI and IT will continue to evolve, creating new business models and services and contributing to solving social issues.

The Future of AI and IT: Challenges and Prospects

AI and IT are expected to continue to evolve and merge in the future. Here, we will explain the future prospects for AI and IT and the challenges they will face along the way.

Accelerating integration of AI and IT

The fusion of AI and IT is already progressing in various fields, but it will likely accelerate in the future. By incorporating AI into IT systems, more advanced functions will be provided, and IT infrastructure will make AI learning and processing more efficient. It is expected that the two will continue to evolve while complementing each other.

• AI-enabled IT systems:
  • By incorporating AI into IT systems, it is possible to provide more advanced functions. For example, by incorporating AI into a CRM (customer relationship management) system, it is possible to provide more personalized services based on the customer’s behavioral history and attributes. In addition, by incorporating AI into an ERP (enterprise resource planning) system, it is possible to automate demand forecasting and inventory management, improving the efficiency of the entire supply chain.
• AI-based IT infrastructure:
  • IT infrastructure is also evolving with AI. For example, in cloud computing, AI is used to balance server load and optimize resources, ensuring stable system operation and reducing costs. In the field of network security, AI can detect abnormal traffic patterns and prevent cyber attacks before they occur.

Addressing ethical issues

As the fusion of AI and IT progresses, it will become increasingly important to address ethical issues.

• AI Fairness, Transparency and Accountability:
  • AI makes decisions based on data, but if that data is biased or biased, the AI may also make biased decisions. To ensure the fairness of AI, it is necessary to train it using diverse data sets and to develop algorithms that detect and correct bias.
  • It is also important to develop “Explainable AI (XAI),” which explains AI’s decision-making process in a way that humans can understand. XAI will solve the black box problem of AI and contribute to improving the reliability of AI.
  • Developers and users need to be accountable for decisions made by AI. Rules and guidelines for the use of AI must be established to promote the ethical use of AI.
• Personal information protection and security measures:
  • Because AI handles large amounts of personal information, privacy protection and security measures are extremely important. It is necessary to comply with laws and regulations such as the Personal Information Protection Act and to clarify the rules regarding the collection, use, and provision of personal information. It is also necessary to strengthen security measures to protect data from cyber attacks and information leaks.

Human Resource Development and Education

In order to keep up with the evolution of AI and IT, it is essential to develop and educate AI talent.

• AI talent shortage:
  • With the rapid development of AI technology, there is a shortage of AI engineers, data scientists, and other personnel with specialized AI knowledge. Companies need to work to secure AI personnel through in-house human resource development and collaboration with universities and vocational schools.
• Improving AI literacy:
  • AI technology has become important knowledge not only for experts, but also for business people and the general public. AI literacy is the ability to understand the mechanisms, possibilities, and limitations of AI, and to use AI appropriately. Companies need to introduce training programs to improve employees’ AI literacy, and educational institutions need to enrich their AI curricula.

Summary: Understanding AI and IT to drive business transformation

Both AI and IT are indispensable technologies in modern society, and the collaboration between the two creates new value for business and society. By understanding the differences between AI and IT and using each technology appropriately, companies will be able to gain a competitive advantage and achieve sustainable growth.

The fusion of AI and IT will continue to accelerate in the future, and will bring about major changes to our lives and society. By overcoming challenges such as AI ethics and human resource development, and maximizing the potential of AI and IT, we should be able to realize a more prosperous and sustainable society.