Allied Market Research published a new report, titled, “Natural Language Processing (NLP) Market Reach USD 239.9 Billion by 2032 Growing with 31.3% CAGR .” The report offers an extensive analysis of key growth strategies, drivers, opportunities, key segments, Porter’s Five Forces analysis, and competitive landscape. This study is a helpful source of information for market players, investors, VPs, stakeholders, and new entrants to gain a thorough understanding of the industry and determine steps to be taken to gain competitive advantage.
The global natural language processing (NLP) market was valued at USD 16.2 billion in 2022, and is projected to reach USD 239.9 billion by 2032, growing at a CAGR of 31.3% from 2023 to 2032.
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Driving Factors
The surge in increasing automation as a result of the integration of NLP with deep learning (DL) and machine learning (ML), drives the market growth. In addition, growing demand for smart devices, and increasing demand for advanced text analytics drive the growth of the market. Increase in automation as a result of the integration of NLP with deep learning and machine learning (ML) and rise in investments in the healthcare sector are expected to create lucrative growth opportunities for the market.
Market Segmentation
The natural language processing market is segmented on the basis of component, deployment mode, enterprise size, type, industry vertical, and region. By component, it is bifurcated into solution and services. By deployment mode, it is segregated into on-premises and cloud. By enterprise size, it is categorized into large enterprise and small and medium-sized enterprise. On the basis of type, it is segregated into statistical NLP, rule-based NLP, and hybrid NLP. By industry vertical, it is segregated into BFSI, IT and telecom, retail and e-commerce, healthcare, education, media and entertainment, and others. Region wise, it is analyzed across North America, Europe, Asia-Pacific, and LAMEA.
Key Players
The key players operating in natural language processing industry include Apple Inc., Intel Corporation, SAS Institute Inc., SAP SE, Google LLC, Microsoft Corporation, Oracle Corporation, International Business Machines Corporation, Amazon Web Services, Inc., and Hewlett Packard Enterprise Development LP. Furthermore, it highlights the strategies of the key players to improve the market share and sustain competition for NLP industry.
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By region, North America garnered the highest share in 2022, holding nearly two-fifths of the global natural language processing market revenue in 2022, and is projected to retain its dominance by 2032, owing to developed IT infrastructure in countries such as the U.S. and Canada, also increasing usage of NLP in BFSI, IT and government sector to improve businesses and customer experience. The Asia-Pacific region would also portray the fastest CAGR of 35.2% during the forecast period, owing to adoption of process automation across all industry verticals to enhance customer engagement and increase effectiveness of IT infrastructure in Asia-Pacific.
By deployment mode, the on-premise segment accounted for more than three-fourths of the global natural language processing market share in 2022, and is expected to rule the boost by 2032, owing to provides complete control and visibility over the data, as well as strong authentication security measures. The cloud segment would also display the fastest CAGR of 33.1% throughout the forecast period, owing to lower deployment costs, predictable running expenses, increased flexibility and scalability in AI-driven NLP, and risk reduction for system downtime.
By type, statistical NLP segment accounted for nearly half of the global natural language processing market share in 2022, and is expected to rule the boost by 2032, owing to offers quantization, maximum likelihood & related rules and class conditional density function, such advantageous features. The rule-based NLP segment would also display the fastest CAGR of 34.1% throughout the forecast period, owing to offering advantages such as availability, cost efficiency and enhanced Speed.
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COVID-19 Scenario
● As business experienced operational delays and adjustments as an outcome of COVID-19 outbreak, consumer queries and assistance requests were increased sharply.
● Organizations restored to natural language processing technologies to automate customer care procedures due to a lack of manpower and resources. In order to handle client inquiries, provide information and offer support NLP-powered chatbots and virtual assistance were widely used which minimized the workload on human customer care staff.
● The pandemic has driven the implementation of NLP in customer service, resulting in higher productivity, lower cost, and better client experiences.
● The COVID-19 pandemic has had a major influence on the healthcare sector as well, necessitating an instant and correct analysis of a huge amount of medical data. Medical literature, clinical notes and research articles about the illness were all processed and useful insights were drawn from them using natural language processing.
● In order to find patterns, retrieve pertinent data, and support COVID-19 treatment development and medical research, NLP algorithms were deployed. The pandemic had drawn attention to the value of NLP in healthcare and inspired development in the field, resulting in better knowledge of the infection and possible solution.
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