Japan Natural Language Processing (NLP) Market size is poised to cross USD 10.32 Billion by the end of 2031, growing at a CAGR of 24.5% during the forecast period, i.e., 2022-2031. In the year 2022, the industry size of Japan natural language processing was over USD 0.87 Billion. Natural language processing is a sub-category of artificial intelligence that helps computer systems to understand the ways of human conversations. Therefore, the growth of the market can be attributed to the growing usage of artificial intelligence in the region and the rise in the development of new AI systems. In 2021, the end users in Japan spent almost 2 billion on artificial intelligence systems. Moreover, the expenditure is expected to grow at a rate of 24% and reach to nearly USD 6 million by 2026. In 2020, the Japan Patent Office received more than 5700 applications for patents relating to artificial intelligence (AI).
In addition to these, factors that are believed to fuel the market growth of Japan’s natural language processing include the government’s rising effort for advancing the use of AI in the region which can boost the development and innovation in the country. For instance, the government presented new strategies for AI in the year 2022. It includes establishing a framework to build and boost the human resources suitable for the AI era, followed by building strategies to develop the research, education, and infrastructure network for artificial intelligence. This initiative resulted in the creation of the "Artificial Intelligence Research and Development Network" and the encouragement of information sharing between member companies. Additionally, NLP also allows various voice assistant devices to understand human speech and commands, therefore, the launch of various voice assistant platforms is further expected to augment the growth of the market. For instance, Kore.ai, a leading AI software provider, launched the enterprise-grade virtual assistant platform. The platform includes various conversational AI technologies, such as NLP, machine learning, NLU, predictive analytics, and deep learning.
Author Credits: Abhishek Verma
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