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Natural Language Processing Market Future Scope, Size, Share, Trends, Business Growth, Opportunities and Forecast to 2028

02-07-2025 11:32 PM CET | Business, Economy, Finances, Banking & Insurance

Press release from: ABNewswire

IBM (US), Microsoft (US), Google (US), AWS (US), Meta (US), 3M (US).

IBM (US), Microsoft (US), Google (US), AWS (US), Meta (US), 3M (US).

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.
The natural language processing (NLP) market [https://www.marketsandmarkets.com/Market-Reports/natural-language-processing-nlp-825.html?utm_campaign=natural-language-processing&utm_source=abnewswire.com&utm_medium=paidpr] is projected to expand from USD 18.9 billion in 2023 to USD 68.1 billion by 2028, reflecting a CAGR of 29.3% during the forecast period. This rapid growth is fueled by several key factors, including advancements in text analysis technologies, increasing adoption of enterprise solutions to enhance business efficiency and customer experience, rising demand for cloud-based NLP to improve scalability and cost-effectiveness, and the growing need for predictive analytics to mitigate risks and uncover new growth opportunities.

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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.

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.

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Unique Features in the Natural Language Processing Market

The integration of artificial intelligence (AI) and deep learning has significantly enhanced NLP capabilities. Modern NLP models, such as GPT, BERT, and T5, are now capable of understanding context, sentiment, and intent with near-human accuracy, enabling more advanced conversational AI and text analysis solutions.

With the rise of real-time data processing, NLP solutions are increasingly capable of handling instant translations, speech recognition, and live sentiment analysis. Industries such as customer service, finance, and healthcare are leveraging real-time NLP to enhance user experiences and decision-making.

NLP models are evolving to support multiple languages, including those with limited training data (low-resource languages). Advanced machine translation and multilingual NLP solutions are helping businesses expand globally, breaking language barriers in communication and information access.

The adoption of cloud-based NLP is accelerating as organizations seek cost-effective, scalable, and accessible AI-driven solutions. Cloud-based NLP enables seamless integration with existing enterprise systems and offers on-demand processing power for high-volume text and speech analysis.

Beyond traditional text processing, NLP models are now capable of detecting sentiment, emotions, and even human intent. Businesses use these capabilities for customer feedback analysis, social media monitoring, and brand reputation management, gaining deeper insights into user behavior.

Major Highlights of the Natural Language Processing Market

Advancements in artificial intelligence (AI) and deep learning have significantly improved NLP accuracy and efficiency. Models such as GPT-4, BERT, and T5 are enabling context-aware language understanding, improved sentiment analysis, and more natural conversational AI experiences.

Organizations are shifting towards cloud-based NLP solutions for better scalability, cost-effectiveness, and remote accessibility. Cloud NLP enables seamless integration with enterprise applications, improving data processing, real-time analytics, and customer interaction capabilities.

Businesses are increasingly adopting multilingual NLP to enhance communication, improve translations, and engage a global audience. Advanced NLP models now support low-resource languages, reducing language barriers in customer support, content creation, and digital services.

The surge in AI-powered virtual assistants, chatbots, and voice-based interfaces is reshaping industries such as customer service, banking, healthcare, and e-commerce. Companies are integrating NLP-driven chatbots to automate responses, improve customer engagement, and reduce operational costs.

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Top Companies in the Natural Language Processing Market

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

IBM, a multinational technology corporation, provides a range of technology services, including infrastructure hosting. The company operates through five primary business segments: cloud and cognitive software, global business services, global technology services, systems, and global financing. IBM Cloud has emerged as a favored platform for business applications due to its compatibility with artificial intelligence (AI). This unified platform seamlessly integrates IBM's capabilities into a single architecture, encompassing both public and private platforms. This robust cloud platform allows IBM to address the diverse needs of businesses worldwide. IBM serves various industries, including aerospace & defense, education, healthcare, oil & gas, automotive, electronics, insurance, retail & consumer products, banking & finance, energy & utility, life sciences, telecommunications, media & entertainment, chemicals, government, manufacturing, travel & transportation, construction, and metals & mining. The company maintains a strong global presence, with clients in over 175 countries across the Americas, Europe, the Middle East, Africa, and Asia Pacific.

IBM is a prominent player in the NLP market, offering services and solutions based on its IBM Watson platform. IBM Watson simplifies complex NLP technologies, making them accessible to non-data scientists within organizations. IBM's products are designed for non-technical users, enabling businesses to streamline operations, enhance employee productivity, and simplify critical business processes effortlessly.

Microsoft holds a prominent position as a global leader and supplier of a diverse range of software products and comprehensive licensing solutions. The company is actively involved in the development and maintenance of software, services, devices, and holistic solutions. Its extensive product portfolio encompasses Operating Systems (OS), productivity applications for various devices, server applications, business solutions, desktop and server management tools, software development tools, and video games. Microsoft also engages in the design, production, and sale of devices, including personal computers, tablets, gaming consoles, intelligent gadgets, and related accessories. The company provides a wide array of services, including solution support, consulting services, and cloud-based solutions that furnish customers with software, services, platforms, and content. Additionally, Microsoft plays a pivotal role in the creation of analytics platforms and delivers production services for the AI-powered intelligent cloud. Revenue generation primarily hinges on software product licensing and support services. Microsoft serves an extensive range of industries, spanning finance and insurance, manufacturing, retail, media & entertainment, the public sector, healthcare, IT, and telecommunications. With a global presence spanning over 190 countries across North America, Asia Pacific, Latin America, the Middle East, and Europe, Microsoft continues to be a dominant force in the technology landscape.

Meta, formerly known as Facebook, is a social media website, web page, commercial, and predictive analytics company. The company builds augmented reality, enabling people to interact and communicate with technologies throughout its virtual-reality goal, the metaverse. Meta is a public company listed on the NASDAQ under the ticker symbol FB. The company's main products include Meta, Instagram, Messenger, WhatsApp, and Oculus. These products enable people to communicate with peers efficiently. The company is also developing various technologies, such as AI, AR, and VR, which help society become more open and connected. Meta has offices and data centers across 30 countries, with 40 sales offices across the globe. Meta generates most revenues from advertising, such as displaying customer ads on Instagram and Meta. It helps the firm's potential customers based on age, gender, place, hobbies, and activity by selling ad slots.

Meta majorly generates revenue from selling ads on its platform to enable marketers to target specific users and increase their marketing reach, thereby acquiring, engaging, and retaining customers through payments and other fees received from developers using their payments infrastructure. It also has multiple investments in connectivity efforts, AI, and AR to develop and strengthen the technological base to serve its end users better. Among other technologies, Meta uses built-in NLP to understand and extract meaningful information from user interactions on its platform. It heavily focuses on breaking down language barriers worldwide for everyone by deploying robust language translation solutions through R&D on deep learning, neural networks, NLP, language identification, text normalization, word sense disambiguation, and ML.

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