NLP Market Provides Detailed Insight by Trends, Challenges, Opportunities, and Competitive Analysis

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The increasing adoption of such technological solutions will fuel the natural language processing industry growth at a high CAGR of 19.7% during 2019–2024

Natural language processing (NLP) allows machines to decode manual inputs and analyze unstructured data, to offer filtered information to improve human–machine interaction. The results obtained by NLP are more appropriate and specific. Technological solutions such as Alexa, Cortana, and Siri are some examples where NLP is used to enhance the semantic search experience.
 
The increasing adoption of such technological solutions will fuel the natural language processing industry growth at a high CAGR of 19.7% during 2019–2024. The market stood at $8.3 billion in 2018, and it is expected to reach $22.9 billion by 2024. Additionally, the rising penetration of virtual assistants among businesses will boost the deployment of NLP-based chatbots in the coming years.
 
 
Developers across the world are introducing chatbots that leverage NLP to bridge the gap between enterprises and customers, thereby enhancing customer service. NLP-supported chatbots can work in multiple languages and aid organizations in streamlining their processes, especially those related to customer care. Such chatbots can handle the queries of customers by becoming the initial point of contact.
 
 
Moreover, the quick shift of businesses toward automation will fuel the adoption of the NLP technology in the foreseeable future. Business entities are switching to automated business models to streamline work processes, reduce human errors, accelerate business growth, and enhance product/service quality. The automated models use the NLP technology to automate data entry and invoicing, to improve business performance.
 
For example, Botkeeper, an artificial intelligence (AI)-enabled program offered by Botkeeper Inc., is used by various entities to manage accounts, as it can handle several tasks within seconds, which otherwise need multiple hours.
 
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