Artificial intelligence (AI) is gaining more and more attention. However, AI is actually a collective term for multiple software technologies, and it is essential to think about applying it to business only after understanding the features and challenges of each of these technologies.
AI is becoming a management theme
In March 2016, the AlphaGo software from DeepMind, a company affiliated with Google, soundly defeated a professional Go player from South Korea. This was a major event that showed the general public how AI can exceed human ability. Now various examples of AI, from basic research to advanced applications, are featured in newspapers and magazines on a daily basis.
The distinguishing characteristics of this current boom in AI are the prevalence of methods for making decisions and predictions based on statistical trends (machine learning) and the increase in the types and amounts of data that can be used.
Japanese companies are also starting to take an interest in utilizing AI. Upon surveying Japanese company’s CIOs (Chief Information Officers) about AI and machine learning, it was found that almost all the companies had some kind of interest in and were exploring the possibilities of AI.
fig：1 Initiatives for AI and Machine Learning
Various AI technologies
The scope of technologies relating to AI is extremely broad, and it is difficult to accurately categorize those technologies. As a technology that replaces human decision making and communication, AI technology can be categorized as below.
Table：1 Categories of AI Technology
Improving business performances with AI
Although a precise model must be created in order to utilize AI based on the principles of machine learning, the key to doing so is collecting large amounts of high quality data. Also, in order to create a model that will improve competitiveness, it is necessary to create a unique model that adequately leverages the knowledge of one's company. AI and machine learning are starting to be widely adopted in various industries overseas, and companies that use data and statistical models to create previously unknown business models are now starting to appear.
Companies that are thinking about starting to utilize AI and machine learning must tackle the challenges of exploring themes from a company-wide perspective, creating a realistic hypothesis, improving human resource and organization capability, improving data reliability, and identifying appropriate tools.
Nomura Research Institute, Ltd.
Corporate Communications Department