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The global natural language processing (NLP) in healthcare and life sciences market, valued at USD 3.26 billion in 2024, is projected to reach USD 3.99 billion in 2025 and USD 20.04 billion by 2035, representing a CAGR of 17.5% during the forecast period.
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Given the growing shift towards predictive analytical tools for disease diagnosis and treatment planning, there is a surge in the demand for natural language processing in the healthcare industry. Natural language processing (NLP) program refers to the computer programs capability to understand and analyze human language in written and speech format. NLP is a part of artificial intelligence (part of metaverse in healthcare) that play a significant role in machine translation, speech recognition, text summarization and language translation.
The integration of NLP based tools, such as virtual assistants and chatbots facilitate patient communication in real time to receive optimal treatment on time, streamlining healthcare support and patient care. It is worth noting that natural language processing programs leverage advanced predictive analytic tools for exploring extensive database, such as real-life data and electronic health records to offer critical insights abouts patients unmet needs and making a tailored treatment plan.
Notably, the growing adoption of natural language processing software and programs to optimize the healthcare industry workflow, enhance patient compliance and offer better predictive analysis of clinical conditions. For instance, in February 2024, Persistent Systems, in collaboration with Microsoft, launched Generative AI-powered population health management solution. This AI-powered solution is aligned with value-based care models that helps to identify social determinants of health to understand patients unmet nonclinical requirements. The primary objective of integrating NLP technologies in the healthcare system is to enhance patient care with higher precision.
In order to make treatment more efficient, several industrial players are aiming to integrate healthcare IT solutions with artificial intelligence and machine learning to leverage automation and precision for tailoring the treatment plan. For instance, in October 2024, Microsoft launched healthcare artificial intelligence tools that include healthcare AI models in Azure AI Studio, developers tools in Copilot Studio and healthcare data capabilities within Microsoft Fabric. These new healthcare AI tools help to reveal conversational data for better clinical insights, imaging and reporting.
With increasing initiatives by the industrial players for technological innovations, we believe that the natural language processing (NLP) in healthcare and life sciences market will remain progressive throughout the projected period.
The market report provides in-depth information about the leading industrial players who are presently active across various segments of the industry.
| Key Report Attributes | Details | |
| Historical Trend | Since 2019 | |
| Forecast Period | Till 2035 | |
| Current Market Size | USD 3.99 Billion | |
| Market Size 2035 | USD 20.04 Billion | |
| CAGR (Till 2035) | 17.5% | |
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| PowerPoint Presentation (Complimentary) |
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| Customization Scope | 15% Free Customization | |
| Excel Data Packs (Complimentary) |
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One of the key objectives of natural language processing (NLP) in healthcare and life sciences market report was to estimate the current size, opportunity and the market growth potential, over the forecast period, till 2035. We have provided informed estimates on the likely evolution of the market for the forecast period.
The market analysis also features the likely distribution of the current and forecasted opportunity within the market distributed across various segments, such as type of technique (smart assistance, optical character recognition, auto coding, text analytics, speech analytics and classification and categorization), type of function (speech recognition, text analytics, sentiment analysis), type of application (clinical documentation, patient engagement, medical coding, and data mining), type of deployment (cloud-based, on-premises, and hybrid), end user (healthcare providers and payers), end user (healthcare providers, payers, life science companies and other end users), geographical region (North America, Europe, Asia-Pacific, Middle East and North Africa, and Latin America) and leading players.
In order to account for future uncertainties associated with some of the key parameters and to add robustness to our model, we have provided three market forecast scenarios, namely conservative, base, and optimistic scenarios, representing different tracks of industry’s evolution.
All actual figures have been sourced and analyzed from publicly available information forums and primary research discussions. The financial figures mentioned in this market report are in USD, unless otherwise specified.
Based on the type of technology, the global natural language processing (NLP) in healthcare and life sciences market is segmented into smart assistance, optical character recognition, auto coding, text analytics, speech analytics and classification and categorization. According to our analysis, smart assistance accounts for the highest share (nearly 20%) of the market driven by the increasing preferences of personalized medicine demand and enhanced patient care.
However, the classification and categorization segment is anticipated to register a higher CAGR during the forecast period. This is primarily due to the fact that healthcare providers are widely adopting the classification and categorization technology for detecting patients at greater risk of diseases, from medication records. Text classification generally involves phrases and specific keywords to make quick search. Further, the increasing technological innovation in this field is anticipated to be a key growth driver of the market.
On the basis of function type, the global natural language processing (NLP) in healthcare and life sciences market is segmented into speech recognition, text analytics, sentiment analysis. According to our market study, speech recognition accounts for the largest share of the market driven by the growing usage of natural language processing systems for recognizing speech to streamline the process of documentation. Further, NLP solutions allow healthcare practitioners to convert their speech into text for medical prescriptions and treatment planning.
Text analytics segment also holds a promising share in the market as it allows analysis of vast amount of clinical unstructured data to enhance patient outcomes. It is important to highlight here that patient’s feedback has become prominent for delivering personalized care and enhance their overall experience. Driven by the ongoing trend, we believe sentiment analysis segment is likely to grow at a higher CAGR during the forecast period.
This segment highlights the distribution of global natural language processing (NLP) in healthcare and life sciences market across different types of applications, such as clinical documentation, patient engagement, medical coding, and data mining. According to our projection, clinical documentation holds the largest share (nearly 35%) of the market and the trend is likely to remain unchanged during the forecast period. This dominance is due to the fact that natural language processing solutions play a significant role in managing clinical documentation and enhance the accuracy of electronic health records. Driven by the increasing usage for clinical documentation, this segment is likely to grow at a higher CAGR during the forecast period.
On the basis of type of deployment, the global natural language processing (NLP) in healthcare and life science market is distributed into cloud-based, on-premises and hybrid. Driven by the growing preferences for scalable and accessible deployment, cloud-based deployment solution accounts for the largest share of the market. Cloud-based solutions are cost-effective and easy to integrate with existing healthcare infrastructure, making it an exceptional solution for deploying NLP technologies without any extensive infrastructure requirement.
On the basis of end user, the global natural language processing (NLP) in healthcare and life sciences market is distributed into healthcare providers, payers, life science companies and other end users. According to our projection, currently life science companies segment accounts for the highest share (nearly 45%) of the market. This can be attributed to the fact that natural language processing solutions play a significant role in analyzing unstructured data and managing the database for research and clinical studies. With the integration of NLP technologies researchers are able to gain insight on necessary data from unstructured databases, such as news articles, PDFs, images and text documents, enabling them to make appropriate decisions.
Based on the end user, the global natural language processing (NLP) in healthcare and life sciences market is distributed across North America, Europe, Asia-Pacific, Middle East and North Africa, and Latin America. Among these, North America holds the largest share (nearly 40%) of the market driven by the supportive regulatory frameworks, advanced healthcare and IT infrastructure and higher adoption of NLP solutions by life science and research companies.
It is important to highlight here that key players active in this domain are accelerating their efforts for the development of advanced natural language processing solutions. For instance, in May 2024, IBM revealed the next family of IBM Granite models into its open-source platform Watsonx that includes efficient code LLMs aiming to drive enterprise AI at scale. Earlier, IBM and Red Hat conjointly launched InstructLab, a first-of-its kind model alignment technique that will be bring open-source community contributors straight into the LLM. The aim of integration of the new models is to accelerate generative AI infusion into resource management products, automation, and consulting services.
However, in Asia-Pacific, the market for natural language processing (NLP) in healthcare and life sciences is expected to register a higher CAGR during the forecast period. This is likely to be the result of increasing patient sufferings with chronic conditions, rising initiatives by the government to support AI and NLP technologies for open communication and data management in the healthcare industry. In addition, the rising acceptance of cloud services for streamlining workflow and managing patient pool is likely to be the key contributor of highest growth rate.
The “Natural Language Processing (NLP) in Healthcare and Life Sciences Market: Industry Trends and Global Forecasts, till 2035” market report features an extensive study of the current market landscape, market size and future opportunity within the bioprocess containers industry, during the given forecast period. The NLP in healthcare and life sciences market report highlights the efforts of several stakeholders involved in this rapidly emerging segment of the service providers industry. Key takeaways of the market data analysis are briefly discussed below.
The market landscape is witnessing a wide array of established and new entrants who are presently exploring advanced solutions for the healthcare industry. Some of the top industrial players who have been consistently offering advanced NLP solutions to the healthcare industry include IBM, Microsoft, IQVIA Holdings, and Wave Health Technologies.
In order to leverage the competitive edge, several market players have taken strategic initiatives with the aim of technological innovations and strengthening product portfolio. For instance, in July 2024, John Snow Labs announced the release of the latest Automated Responsible AI Testing Capabilities (the first-of-its-kind no-code tool for testing safety and efficacy of custom language models) in its Generative AI Lab and medical chatbots. It is aimed to define, share test suites and run AI models with higher accuracy.
As more market players continue to deliver robust natural language processing solutions, we believe that this market will remain competitive throughout the projected period.
The healthcare industry is shifting to standardized digital healthcare solutions including remote patient monitoring devices, smart wearables and data analytic solutions. These interactive healthcare solutions require natural language processing solutions to streamline healthcare operations, data assimilation and analysis to facilitation patient outcomes. With the rising adoption of digital healthcare solutions, the demand for natural language processing solutions has significantly increased, which is anticipated to be a key growth factor for the market.
Some other notable NLP in healthcare and life sciences market drivers includes rising demand for advanced analytic tools for predicting unstructured data generated regularly, such as patient records, clinical diagnosis reports and research reports.
Although natural language processing has gained significant traction during the past few years in healthcare industries, there are some challenges that may hinder its further progress. Some of the potential natural language processing (NLP) in healthcare and life sciences market challenges include data privacy, high implementation cost and complexity associated with technology integration. Notably, the processing of sensitive patient information from NLP solutions may raise a concern of privacy and data breaching.
Hence, industrial players are required to implement cybersecurity methodologies and pave through laws under HIPAA for data security. Standard zero tolerance authentication is required to be adopted in the healthcare industry to ensure data safety of patients. In addition to data security, the complexity of NLP system integration with existing healthcare IT infrastructure, such as clinical systems and EHRs can create a significant barrier for the industrial players. Moreover, the high implementation cost of natural language processing systems may limit its adoption of these solutions across healthcare industry.
Some of the significant natural language processing (NLP) in healthcare and life sciences market trends are growing integration of IoT in wearable medical devices, AI-based chatbots and adoption of NLP in clinical trial management. It is worth noting that wearable technology is consistently booming in the healthcare industry to enhance patient disease monitoring and remote treatment planning. Wearable devices are continuously integrating NLP solutions powered by IoT for real-time data monitoring of patients. Real-time data analysis helps in preparing an actionable treatment plan based on the information collected using smart wearables.
In addition, the healthcare industry is adopting AI-based chatbots empowered by NLP solutions that enable healthcare practitioners in designing individualized treatment plans. Furthermore, the adoption of NLP in medical coding and billing automated the billing by converting physical notes, diagnostics reports and procedure descriptive reports into simple codes that are required in compliance and reimbursement. Moreover, the growing utilization of natural language processing in managing clinical trials for data extraction and analysis has further fueled the demand for NLP solutions during the forecast period.
The NLP in healthcare and life sciences market is expected to be valued at USD 3.99 billion in 2025 and is poised to reach USD 20.04 billion by 2035. Driven by the growing adoption of natural language processing systems and technologies in healthcare industry, we believe that the market is expected to grow at a CAGR of 17.5% during the forecast period. Notably, the key players of the market are forging strategic partnerships to enhance the product portfolio and innovations.
For instance, in February 2024, MyHealthcare and Ashoka University secured the prestigious Johns Hopkins GKII Breakthrough Grant for Health Data Research agreement in order to focus on leveraging technologies, big data and clinical expertise to enhance data-driven evidence generation that aid in delivering appropriate care to the patients. The grant will be used to use natural language processing algorithms and open-source large language models to extract unstructured clinical data.
Examples of key players engaged in this domain (which have also been captured in this report) include 10x Genomics, Amazon, Caresyntax, Cerner, Mayo Clinic, Epic Systems, Google, Health Catalyst, IBM, Invitae, Microsoft, Nuance Communications, PathAI, Tempus and Zebra Medical Vision. This market report includes an easily searchable excel database of all the companies focusing on the development of natural language processing solutions.
Several recent developments have taken place in the natural language processing (NLP) in healthcare and Life Sciences industry. We have outlined some of these recent initiatives below.