Natural Language Processing (NLP) allows machines to improve human-machine interaction by offering filtered information after decoding human inputs and studying unstructured data. The filtered information obtained by using NLP solutions is more appropriate and specific. In contemporary times, Siri, Alexa, and Cortana are some of the widely used technological solutions, where the NLP technology is used to improve the semantic search experience. Thus, the increasing use of such semantic search platforms will boost the adoption of NLP services and applications in the foreseeable future.
Additionally, the increasing focus of end-use industries on the adoption of automated solutions is also expected to propel the natural language processing market at a robust CAGR of 19.7%. Automated solutions assist businesses in consolidating their position by enhancing human-machine interactions. Additionally, NLP-enabled automated solutions, such as chatbots, aid enterprises in improving customer interaction, as they can study the input from customers and automatically provide an appropriate response.
Moreover, the surging volume of unstructured data being generated by business organizations will also propel the usage of NLP solutions, such as text analytics, optical character recognition, auto coding, speech analytics, pattern and image recognition, and interactive voice response (IVR). These solutions help enterprises deal with business-related problems by analyzing the large volume of data extracted from video and images, social media, and documents and blogs. At present, these solutions are being adopted by the retail, media and entertainment, information technology (IT) and telecommunication, electronics, public utilities and defense, healthcare, automotive, and banking, financial services, and insurance (BFSI) industries.
The type segment of the natural language processing market is categorized into hybrid, statistical, and rule-based. Among these, the statistical category accounted for the largest market share in 2018, as statistical solutions are more advantageous than rule-based solutions. Whereas, the hybrid category is expected to demonstrate the fastest growth during the forecast period, owing to the rising volume of data being generated by business organizations. Hybrid NLP solutions are basically a combination of rule-based and statistical models.
In recent years, the North American region has emerged as the largest user of natural language processing solutions and services due to the mounting investments made by non-profit organizations, businesses, and academic institutions in research and development (R&D) of AI-based technologies, increasing volume of data across industries, and escalating demand for improved customer experiences in the region. Among North American countries, the U.S. holds the leading position due to the existence of a large number of financial institutions that use NLP for greater efficiency in the country.
Whereas, the Asia-Pacific (APAC) natural language processing market is expected to exhibit the fastest growth throughout the forecast period, owing to the mounting number of small and medium-sized enterprises (SMEs) and customer contact centers, rapid technological developments in India, Japan, and China, and surging use of cloud-enabled services and applications in the region. In the APAC market, China generated the highest revenue in 2018, due to the launch of several innovation programs aimed at deploying AI technologies, such as machine learning (ML), NLP, and deep learning.
Thus, the accelerating automation rate in the manufacturing sector and booming demand for semantic search platforms will increase the deployment of NLP solutions and services in the forthcoming years.
