The Global Natural Language Processing Market Growth, COVID-19 Impact and Forecast (2021-2025)
The global natural language processing market is segmented on Deployment type as cloud and On-Premise; based on Size of the organization as a small and medium organization(SME) and large organization; based on the End-user as BFSI, IT & Telecom, healthcare, Retail & eCommerce, government & defense, media & entertainment, manufacturing, and others; based on geography as APAC, Europe, North America, and ROW.
Introduction
Natural language processing (NLP) is a computer application under artificial intelligence that can understand human language. This computerized technique allows human communication to be analyzed and interpreted by the computer based on a set of technologies and theories.
The goal of natural language processing is to minimize the time taken to understand computer languages such as Ruby, C, C++, and Java. NLP finds application in the analysis of big data owing to the fact that massive amounts of data are being generated in current business scenarios from sources such as audio, emails, web blogs, documents, social networking sites, and forums.
The major types of natural language processing solutions include statistical NLP, rule-based NLP, and hybrid NLP.
Natural language processing includes recognition, analytics, and operational technologies such as optical character recognition (OCR), auto coding, text analytics, interactive voice response (IVR), pattern and image recognition, classification and categorization, and speech analytics.
Table of Contents
Market Overview
The Global natural language processing market is expected to grow to $29.23 billion by 2025 at CAGR of 20.30%.
Worldwide revenue from the natural language processing (NLP) market is forecast to increase rapidly in the next few years.
It is expected that 85% of business engagement will be done without human interaction over the forecast period. Also, by 2020, it is estimated that Chatbots will save over USD 8 billion dollars to organizations globally.
Key Trends
The demand for NLP solutions and services is expected to increase due to the increased demand for enhancing customer experiences and building personalized relationships with prospects.
Growing demand for cloud-based NLP solutions to reduce overall costs and better scalability and increasing usage of smart devices to facilitate smart environments are expected to drive the NLP market in the future.
Key Market Players
The market is dominated by global vendors like Microsoft, Micro Focus International PLC, SAS institute, IBM, Google, and Intel.
Growth Drivers and Challenges
As many organizations are increasingly adopting deep learning, along with supervised and unsupervised machine learning technologies for various applications, the adoption of NLP is likely to increase and drive the growth of the market.
Cost and risk are some of the major factors which have driven the market of these technologies among large organizations.
Code-switching or Code-Mixed (CM) language is the alternation of languages within a conversation or utterance and is a common communicative phenomenon that occurs in multilingual communities across the world.
NLP tasks, such as normalization, language identification, language modeling, part-of-speech tagging, and dependency parsing, machine translation, and Automatic Speech Recognition (ASR), face issues while working on non-canonical multilingual data in which two or more languages are mixed.
The COVID-19 pandemic has increased the churn rate and shuddered almost every vertical. The lockdown is impacting global manufacturing and supply chain, and logistics as the continuity of operations for various verticals are getting badly impacted.
The verticals facing the greatest drawbacks are manufacturing, transportation and logistics, and retail and consumer goods.