Natural Language Processing Market Growth, Leading Players and Forecast Report, 2030

Market Research Consultants

Updated on Feb 28, 2024

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In 2023, the market for NLP was valued at USD 18.5 billion. Forecasts indicate it will grow significantly, reaching USD 112.0 billion by 2030, with a projected compound annual growth rate (CAGR) of 29.4% between 2024 and 2030.

This development of the market can be credited to the growing utilization of chatbots for assisting client services. Furthermore, other reasons like growing expenditure throughout the healthcare industry, growth in text-analyzing computer programs, and increasing need for enterprise solutions to rationalize business operations for better client experience are projected to boost the acceptance of natural language processing.

Based on type, during the projection period, the rule-based category is projected to experience substantial development. This is mainly because rule-based NPL places a robust focus on pattern matching, a vital skill in the healthcare sector. The approach proves worthy in healthcare by advancing the electronic health record process through the identification of precise phrases, thus advancing data management effectiveness.

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North America currently commands the largest portion of revenue in the NLP market, and this trend is projected to persist in the future. This dominance can be attributed to factors like swift advancements in AI technology and the concentration of major market players in the region.

Furthermore, key companies like Google, IBM, Microsoft, and Meta have played pivotal roles in introducing innovative NLP technologies. These advancements have notably improved accuracy, speed, and problem-solving capabilities, thereby making NLP increasingly indispensable for computer scientists and professionals grappling with intricate challenges.

The major drivers of the NLP market include the increasing use of chatbots for assisting customer services and AI-powered chatbots and cloud-based voice-recognizing systems aid in most business operations and help in making data-driven decisions.


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