Natural Language Processing (NLP) Market Size, Revenue, Growth Rate Analysis

According to a research report "Natural Language Processing (NLP) Market by Offering (Solutions, Services), Type (Rule-based, Statistical, Hybrid), Application (Sentiment Analysis, Social Media Monitoring), Technology (IVR, OCR, Auto Coding), Vertical & Region - Global Forecast to 2028" published by MarketsandMarkets

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The market for natural language processing is estimated to grow from USD 18.9 billion in 2023 to USD 68.1 billion by 2028, at a CAGR of 29.3% during the forecast period. Natural Language Processing (NLP) refers to the branch of computer science, specifically the branch of Artificial Intelligence (AI), concerned with giving computers the ability to understand text and spoken words in much the same way human beings can. NLP drives computer programs that translate text from one language to another, respond to spoken commands, and quickly summarize large volumes of text-even in real time.

Services segment to account for higher CAGR during the forecast period

NLP market relies heavily on its services segment to achieve effective software operations. To increase the efficiency of the entire process, managed and professional services are installed, which are the services considered in this report. Companies such as Microsoft, IBM, and SAS Institute have started providing platforms for embedding NLP technologies. These platforms can be coded across various programming languages. Major players like Microsoft have formed partnerships with SMBs that develop speech-to-text software, making them available across their integrated platforms. For example, AWS offers an Amazon Comprehend service that uses machine learning for extracting key phrases and identifying the language in each text. Amazon Comprehend works seamlessly with any AWS-supported application and offers useful features such as sentiment analysis, tokenization, and automated text file organization.

Cloud segment is expected to hold the largest market size for the year 2023

Organizations can reap numerous benefits by deploying their systems on the cloud. These benefits include easy availability, scalability, reduced operational costs, and hassle-free deployments. AI platform providers are focusing on developing robust cloud-based deployment solutions for their clients, as many organizations have migrated to either private or public cloud. This mode of deployment offers additional flexibility for business operations and real-time deployment ease to companies implementing real-time analytics. The cloud-based deployment of NLP has made it easy for users to apply predictive capabilities to the entire organization. The major vendors offering cloud-based NLP solutions are IBM, Microsoft, AWS, and Google.

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The healthcare and life sciences vertical is projected to grow at the highest CAGR during the forecast period

In the healthcare industry, accuracy and efficiency are crucial because they directly impact human health. Therefore, the margin of error must be close to zero. Natural Language Processing (NLP) offers several applications and use cases that address healthcare challenges. NLP technologies are revolutionizing the healthcare sector by automating the tedious task of transcribing notes from clinical staff, extracting essential information, and enabling clinicians to refine their problem list. With the help of NLP tools, clinicians can quickly filter relevant clinical data from unstructured patient-related documentation, flag any necessary updates, and cross-reference the same with the current problem list. The adoption of Electronic Health Records (EHRs) has increased the demand for NLP solutions in the healthcare sector. NLP solutions are readily implemented in EHRs to convert free text conversations into insights, thereby bridging the gap between complex medical terms and patients' understanding of their health. This helps improve patient interactions, and, in turn, the quality of patient care. NLP solutions also aid in identifying gaps in physicians' performance and potential errors in care delivery, thereby contributing to value-based reimbursements.

The report profiles key players such as IBM (US), Microsoft (US), Google (US), AWS (US), Meta (US) and 3M (US).

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