Text Analytics Market - Global Industry Size, Share, Trends, Opportunity, and Forecast, Segmented By Analytics Type (Sentiment Analysis, Entity Recognition, Keyword/Concept Extraction, Text Categorization, Predictive Analysis), By Application (Customer Experience Management, Risk & Compliance Management, Human Resource Management, Market Intelligence, Others), By End User (Banking, Financial Services, and Insurance, Retail and E-commerce, Healthcare and Life Sciences, Information Technology and Telecommunications, Manufacturing, Government and Public Sector, Others), By Region & Competition, 2020-2030F

Market Overview

The Global Text Analytics Market was valued at USD 15.17 billion in 2024 and is expected to reach USD 51.37 billion by 2030 with a CAGR of 22.36% during the forecast period.

The Text Analytics Market refers to the industry focused on extracting meaningful insights from unstructured textual data generated across various sources such as social media, emails, customer reviews, surveys, documents, and online content. This market encompasses solutions and services that leverage natural language processing, machine learning, and artificial intelligence technologies to analyze text, detect patterns, identify trends, and provide actionable intelligence to organizations. By converting unstructured data into structured, analyzable formats, text analytics enables businesses to improve decision-making, enhance customer experiences, monitor brand reputation, manage risks, and gain competitive advantage.

The market is rising rapidly due to the exponential growth of data generated from digital platforms, the increasing need for real-time insights, and the expanding adoption of artificial intelligence-driven tools across multiple industries. Key applications driving market growth include customer experience management, where organizations analyze feedback and sentiment to refine products and services; risk and compliance management, where regulatory documents and communications are monitored for adherence to legal frameworks; and market intelligence, where companies analyze competitor strategies and industry trends to make informed decisions. Additionally, the proliferation of cloud computing and software-as-a-service models is enabling businesses of all sizes to access scalable, cost-effective text analytics solutions without significant infrastructure investment.

Enterprises are increasingly deploying both on-premise and cloud-based solutions depending on their security requirements, data volume, and operational needs, contributing to overall market expansion. Geographically, North America dominates due to advanced technological infrastructure, early adoption of analytics tools, and strong presence of key market players, while the Asia Pacific region is emerging as a high-growth market driven by rapid digital transformation, increasing internet penetration, and government initiatives promoting data-driven strategies. The integration of advanced analytics with artificial intelligence, machine learning, and predictive modeling is expected to further propel the market by enabling organizations to not only understand historical and current trends but also forecast future outcomes.

Key Market Drivers

Explosive Growth in Unstructured Data Volume

In the rapidly evolving landscape of the Text Analytics Market, the explosive growth in unstructured data volume stands as a paramount driver, compelling enterprises to adopt advanced analytical solutions to harness insights from vast repositories of textual information. Unstructured data, encompassing emails, social media posts, customer reviews, documents, and multimedia content, is proliferating at an unprecedented rate due to digital transformation initiatives across industries. Businesses are increasingly recognizing that traditional data management techniques fall short in processing this deluge, leading to the imperative integration of text analytics tools that employ natural language processing and machine learning algorithms to extract actionable intelligence.

This driver is particularly salient in sectors like healthcare, where patient notes and medical literature require sophisticated analysis for improved diagnostics and personalized care, or in retail, where consumer feedback informs product development and marketing strategies. The Text Analytics Market benefits from this trend as organizations seek to convert raw, chaotic data into structured formats that facilitate decision-making, risk assessment, and operational efficiency. Moreover, the integration of cloud computing platforms amplifies this growth by providing scalable storage and processing capabilities, enabling real-time analysis without substantial upfront investments in infrastructure.

As enterprises grapple with data silos and information overload, text analytics emerges as a strategic asset, enabling predictive modeling and trend forecasting that drive competitive advantage. The market's expansion is further fueled by the need for sentiment analysis, entity recognition, and topic modeling, which uncover hidden patterns and correlations within unstructured datasets. In finance, for instance, analyzing news articles and regulatory filings through text analytics mitigates risks and identifies investment opportunities. The convergence of big data technologies with text analytics solutions underscores a shift towards data-driven cultures, where insights derived from unstructured sources inform everything from supply chain optimization to customer relationship management.

This driver not only accelerates adoption but also spurs innovation in tool development, with vendors enhancing capabilities to handle multilingual and multimodal data. Ultimately, the relentless increase in unstructured data volume propels the Text Analytics Market forward, positioning it as an indispensable component of modern business intelligence frameworks, ensuring resilience and agility in an information-saturated world.

According to IBM, unstructured datasets comprise 90% of all enterprise-generated data, driven by the emergence of big data from connected technologies. This volume is growing exponentially, with large organizations producing four times as much unstructured data as structured data annually. Edge Delta reports that unstructured data grows at an annual rate of 55% to 65%, fueled by AI trends, while 95% of businesses acknowledge risks in managing it. IBM further notes that by 2025, semi-structured and unstructured data will represent up to 80% of the world's information, highlighting the urgent need for analytics to derive value from this massive influx. These figures underscore how the sheer scale and velocity of unstructured data creation are key catalysts for market expansion, prompting investments in tools that process hundreds of millions of pages efficiently.

Advancements in Artificial Intelligence and Natural Language Processing Technologies

Advancements in artificial intelligence and natural language processing technologies are fundamentally transforming the Text Analytics Market, enabling unprecedented accuracy and efficiency in interpreting human language for business applications. These innovations allow systems to understand context, nuance, and intent in text data, moving beyond keyword matching to sophisticated comprehension that mirrors human cognition. In the Text Analytics Market, this driver manifests through enhanced algorithms that power applications like automated summarization, machine translation, and conversational AI, which are critical for global operations in diverse linguistic environments.

Enterprises leverage these technologies to automate labor-intensive tasks, such as contract review in legal sectors or fraud detection in banking, reducing errors and accelerating workflows. The integration of deep learning models, including transformers and generative AI, has elevated the market by facilitating real-time processing of massive datasets, thereby supporting dynamic decision-making in volatile business landscapes. For example, in e-commerce, NLP-driven recommendation engines analyze user queries and reviews to personalize experiences, boosting conversion rates and customer loyalty. The Text Analytics Market thrives on this momentum as vendors incorporate open-source libraries and cloud-based services, democratizing access for small and medium enterprises previously constrained by resource limitations.

Furthermore, ethical AI frameworks ensure bias mitigation and transparency, fostering trust and wider adoption across regulated industries. This driver also intersects with edge computing, allowing on-device analytics for privacy-sensitive scenarios like healthcare diagnostics from patient narratives. As AI evolves, the market sees synergies with other domains, such as computer vision for multimodal analysis, expanding applications to video transcripts and image captions. Ultimately, these technological strides position the Text Analytics Market at the forefront of digital innovation, empowering organizations to derive strategic value from textual data in an era defined by information abundance and complexity.

Sentiment analysis, a key NLP application, processes over 80 million customer reviews annually, improving retention by 20% for businesses. AI adoption in NLP has seen open-source libraries used by 78% of companies, while the market for sentiment analysis is projected to reach USD 6.3 billion by 2028 at 14.1% CAGR.

Rising Demand for Enhanced Customer Experience Management

The rising demand for enhanced customer experience management is a critical driver propelling the Text Analytics Market, as businesses prioritize deriving insights from customer interactions to foster loyalty and drive revenue growth. In today's customer-centric economy, organizations utilize text analytics to mine feedback from surveys, chat logs, and support tickets, enabling proactive issue resolution and tailored service delivery. This driver is evident in the Text Analytics Market through tools that perform sentiment analysis and theme extraction, revealing pain points and preferences that inform product enhancements and marketing campaigns. For instance, in telecommunications, analyzing call transcripts identifies service gaps, leading to improved satisfaction scores and reduced churn.

The market's growth is amplified by the shift to omnichannel engagement, where text analytics integrates data from emails, apps, and voice channels for a holistic view of the customer journey. Enterprises invest in these solutions to achieve competitive differentiation, as personalized experiences correlate with higher lifetime value and advocacy. Additionally, the incorporation of predictive analytics anticipates customer needs, such as recommending solutions before complaints escalate, optimizing resource allocation. The Text Analytics Market benefits from this trend as it aligns with broader digital transformation efforts, where data-driven CX strategies yield measurable ROI. In retail, for example, analyzing online reviews refines inventory decisions and pricing models.

This driver also encourages collaboration between CX teams and IT, ensuring seamless deployment of analytics platforms that scale with business needs. As consumer expectations evolve towards instantaneous and empathetic interactions, text analytics becomes indispensable, transforming raw feedback into strategic assets that sustain long-term growth in the Text Analytics Market.

Text analytics holds 39% share in analytical tools, with speech analytics growing at 18.4% CAGR. Call centers dominate touchpoints at 31%, while cloud deployment expands at 18.3%. Businesses using sentiment analysis see 20% better retention, processing millions of reviews to cut negative feedback by 35% in e-commerce.

Stringent Regulatory Compliance Requirements

Stringent regulatory compliance requirements are driving robust growth in the Text Analytics Market, as organizations deploy solutions to navigate complex legal landscapes and mitigate non-compliance risks. Regulations like GDPR, HIPAA, and SOX mandate thorough monitoring of communications and documents, where text analytics automates detection of sensitive information and ensures adherence to standards. This driver fuels the market by enabling efficient auditing of vast textual data, such as emails and contracts, to identify violations and support reporting. In finance, text analytics scans transaction notes for fraud indicators, aligning with anti-money laundering laws.

The Text Analytics Market expands as compliance functions integrate AI for continuous monitoring, reducing manual efforts and enhancing accuracy. Enterprises face escalating penalties for breaches, prompting investments in tools that provide audit trails and risk assessments. This trend is accentuated in healthcare, where analyzing patient records ensures privacy compliance while improving care quality. The market's evolution includes features like PII redaction and policy enforcement, critical for multinational operations under varying jurisdictions.

As regulations evolve with digital advancements, text analytics offers proactive compliance, forecasting potential issues through pattern recognition. This driver fosters innovation, with vendors developing sector-specific modules that streamline workflows and bolster governance. Ultimately, stringent requirements position the Text Analytics Market as a vital ally in maintaining ethical operations and reputational integrity amid regulatory scrutiny.

Social media users grew by 138 million in the past year, a 2.5% increase, with global users exceeding 5 billion in 2025. Over 80 million customer reviews are processed annually via sentiment tools, reducing negative feedback by 35% in e-commerce. Voice assistants handle 60% of calls, with 1 in 4 US users engaging daily. NLP for social monitoring is deployed by 74% of organizations, boosting engagement by 25% through AI-driven insights

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Key Market Challenges

Data Privacy and Security Concerns

One of the foremost challenges confronting the Text Analytics Market is ensuring robust data privacy and security. As organizations increasingly collect and analyze unstructured textual data from diverse sources such as social media, customer reviews, emails, and internal communications, the volume of sensitive information being processed rises significantly. This data often contains personally identifiable information, financial details, or proprietary business insights, making it a prime target for cyberattacks, data breaches, and unauthorized access. Text analytics solutions rely on centralized platforms, cloud storage, or on-premise infrastructure, each carrying inherent security risks that could compromise the integrity and confidentiality of data.

Regulatory compliance further complicates the landscape, as stringent data protection laws such as the General Data Protection Regulation in Europe, the California Consumer Privacy Act in the United States, and emerging privacy regulations in Asia-Pacific require companies to implement strict governance frameworks, audit trails, and access controls. Non-compliance can result in substantial financial penalties, reputational damage, and operational disruptions. Moreover, organizations deploying third-party analytics platforms face additional challenges, as these vendors must adhere to the same privacy standards and demonstrate robust security protocols. The complexity increases when text analytics is integrated with artificial intelligence and machine learning algorithms, which necessitate large datasets to train models, raising concerns regarding the secure handling of sensitive information during processing.

Enterprises must invest heavily in encryption, anonymization, and tokenization techniques, along with comprehensive cybersecurity measures to mitigate risks. Ensuring secure data transmission between endpoints, monitoring for potential vulnerabilities, and maintaining compliance with evolving regulations across multiple jurisdictions requires continuous investment and expertise. These privacy and security concerns can slow adoption rates, particularly among industries dealing with highly sensitive data such as banking, healthcare, and government services. Consequently, the Text Analytics Market must address these challenges through a combination of advanced security solutions, regulatory alignment, and best practices in data governance to maintain stakeholder trust and support sustainable market growth.

Complexity of Unstructured Data and Integration Issues

Another significant challenge hindering the growth of the Text Analytics Market is the inherent complexity of unstructured textual data and the difficulties associated with integrating analytics solutions into existing enterprise systems. Unlike structured data stored in databases, unstructured text is highly diverse, containing varying formats, languages, slang, jargon, abbreviations, and contextual nuances that complicate accurate analysis. Processing such data requires advanced natural language processing, machine learning models, and semantic analysis algorithms, which must be continuously updated to handle evolving language patterns and domain-specific terminology. Additionally, organizations often operate multiple legacy systems, enterprise resource planning platforms, and disparate data sources that were not initially designed to support advanced analytics solutions.

Integrating text analytics tools with these existing systems can be technically challenging, requiring extensive customization, data cleaning, and standardization efforts. Data silos, inconsistent data quality, and lack of interoperability between systems further exacerbate these issues, limiting the ability to derive comprehensive insights across organizational operations. Moreover, the deployment of predictive and prescriptive analytics models demands continuous monitoring, retraining, and validation to ensure accuracy, adding operational complexity and resource requirements. Enterprises with limited technical expertise or insufficient IT infrastructure may struggle to fully utilize the potential of text analytics, impacting adoption rates and return on investment.

The need for skilled personnel, including data scientists, natural language processing specialists, and integration engineers, further increases costs and resource constraints. As organizations aim to leverage text analytics for real-time decision-making, the challenge of processing massive volumes of unstructured data quickly and accurately becomes even more pronounced. Addressing these integration and complexity challenges is critical for the Text Analytics Market to enable seamless deployment, maximize analytical value, and ensure scalable, reliable solutions that support informed business strategies across industries.

Key Market Trends

Integration of Artificial Intelligence and Machine Learning in Text Analytics

A prominent trend shaping the Text Analytics Market is the growing integration of artificial intelligence and machine learning technologies into analytics solutions. Organizations are increasingly leveraging these advanced technologies to enhance the accuracy, efficiency, and depth of textual data analysis. Artificial intelligence-powered algorithms, including natural language processing and deep learning models, enable enterprises to extract sentiment, context, and intent from unstructured data with greater precision. Machine learning facilitates continuous model improvement by learning from historical data patterns, allowing predictive and prescriptive insights that support strategic decision-making.

This trend is particularly impactful in industries such as banking, financial services, healthcare, and retail, where organizations must analyze large volumes of customer feedback, social media interactions, regulatory documents, and internal communications. By automating the analysis process, businesses can reduce reliance on manual intervention, minimize errors, and accelerate time-to-insight, enabling more agile responses to market changes and customer expectations. Additionally, the combination of artificial intelligence and machine learning allows for multilingual text analysis, which is critical for global enterprises operating across diverse regions and languages. The increasing adoption of AI-driven chatbots, virtual assistants, and automated customer support systems further reinforces this trend, as these applications generate and rely on real-time textual data that must be analyzed for continuous improvement and operational efficiency.

Vendors in the Text Analytics Market are increasingly incorporating explainable artificial intelligence features into their platforms, providing transparency and interpretability of insights, which enhances trust and adoption among enterprises. As organizations seek to harness the full potential of unstructured data, the integration of artificial intelligence and machine learning is becoming a key differentiator in the Text Analytics Market, driving innovation, enabling advanced analytics capabilities, and fostering widespread adoption across industries. This trend is expected to continue shaping the market landscape by empowering businesses to transform data into actionable intelligence that informs strategy, optimizes processes, and enhances competitive advantage.

Growing Adoption of Cloud-Based Text Analytics Solutions

The adoption of cloud-based solutions is a significant trend transforming the Text Analytics Market, as enterprises increasingly prefer scalable, flexible, and cost-effective deployment models. Cloud-based platforms allow organizations to analyze large volumes of unstructured textual data without significant upfront investment in infrastructure, enabling small and medium-sized enterprises to access advanced analytics capabilities previously limited to large corporations. These solutions support real-time data processing and seamless integration with existing enterprise applications, enhancing operational efficiency and decision-making. Cloud platforms also facilitate collaboration across geographically dispersed teams, enabling centralized access to insights and consistent application of analytics tools.

Additionally, cloud-based deployments provide enhanced security features, automated updates, and maintenance, reducing the burden on internal IT resources and ensuring compliance with evolving data protection regulations. The scalability of cloud solutions allows businesses to expand analytics capabilities as data volumes grow, accommodating spikes in workload without compromising performance. With the increasing adoption of remote work models and digital transformation initiatives, cloud-based text analytics platforms are becoming essential for organizations seeking agility, flexibility, and rapid deployment. Furthermore, integration with other cloud services, such as customer relationship management, enterprise resource planning, and marketing automation platforms, enhances the value of text analytics by providing comprehensive insights across organizational functions.

As more enterprises prioritize cost efficiency, operational scalability, and data accessibility, the shift toward cloud-based text analytics solutions is expected to accelerate, driving market growth and enabling organizations to harness the full potential of unstructured data. The combination of scalability, real-time processing, and seamless integration positions cloud-based solutions as a strategic choice for enterprises aiming to gain a competitive edge through data-driven insights.

Increased Focus on Sentiment Analysis and Customer Experience Management

A key trend in the Text Analytics Market is the growing emphasis on sentiment analysis and customer experience management, driven by the need for businesses to understand and respond to consumer perceptions in real time. Organizations are leveraging text analytics to analyze customer feedback from multiple channels, including social media, online reviews, surveys, and call center interactions, in order to identify satisfaction levels, preferences, and pain points. Sentiment analysis enables enterprises to quantify customer opinions, detect emerging trends, and proactively address issues before they escalate, thereby enhancing customer loyalty and brand reputation.

This trend is particularly significant in sectors such as retail, e-commerce, banking, and hospitality, where customer experience directly impacts revenue and market positioning. Advanced text analytics solutions now incorporate emotion detection, intent analysis, and contextual understanding, allowing companies to derive nuanced insights that inform product development, marketing campaigns, and service improvements. Additionally, the integration of sentiment analysis with predictive analytics empowers businesses to forecast customer behavior, anticipate churn, and optimize engagement strategies. Organizations are increasingly embedding these insights into customer relationship management systems to ensure data-driven, personalized interactions across touchpoints.

The growing importance of omnichannel engagement further fuels this trend, as enterprises seek to maintain consistent and positive customer experiences across digital and physical platforms. As businesses recognize that effective customer experience management can drive competitive advantage, the demand for sophisticated sentiment analysis solutions is expected to rise, positioning this capability as a central component of the Text Analytics Market. The focus on actionable insights derived from customer sentiments underscores the market’s shift toward proactive, intelligence-driven strategies aimed at enhancing customer satisfaction, loyalty, and overall business performance.

Segmental Insights

Analytics Type Insights

In 2024, the Sentiment Analysis segment dominated the Text Analytics Market and is expected to maintain its leading position throughout the forecast period, driven by the increasing need for organizations to understand customer opinions, brand perception, and market trends. Sentiment analysis enables enterprises to extract actionable insights from unstructured textual data generated across multiple channels, including social media, online reviews, surveys, emails, and customer feedback. By analyzing the emotional tone and contextual meaning of text, organizations can identify positive, negative, or neutral sentiments, allowing them to make informed decisions that enhance customer satisfaction, improve brand reputation, and optimize overall business performance.

Industries such as retail, e-commerce, banking, financial services, healthcare, and hospitality are increasingly deploying sentiment analysis to monitor customer interactions in real time, anticipate emerging trends, and respond proactively to potential issues. The integration of artificial intelligence and machine learning technologies has further strengthened the capabilities of sentiment analysis solutions, enabling more accurate interpretation of language nuances, slang, sarcasm, and multilingual content, which enhances decision-making accuracy. Additionally, sentiment analysis supports predictive applications, allowing organizations to forecast customer behavior, product performance, and potential market risks based on sentiment patterns. The rising volume of user-generated content and digital communications across global platforms is creating a strong demand for tools that can efficiently process and analyze textual data at scale.

Application Insights

In 2024, the Customer Experience Management segment dominated the Text Analytics Market and is expected to maintain its leadership throughout the forecast period, driven by the growing emphasis on delivering personalized, data-driven interactions that enhance customer satisfaction and loyalty. Organizations across industries such as retail, e-commerce, banking, financial services, healthcare, and telecommunications are increasingly leveraging text analytics solutions to analyze unstructured data generated from multiple sources, including social media, customer reviews, emails, surveys, and call center interactions.

By processing this data, enterprises gain actionable insights into customer preferences, sentiment, pain points, and emerging trends, enabling them to optimize products, services, and engagement strategies. Text analytics empowers businesses to monitor brand perception in real time, respond proactively to negative feedback, and implement improvements that directly impact customer retention and revenue growth. The integration of artificial intelligence and machine learning technologies into text analytics platforms further enhances the ability to detect sentiment, context, and intent accurately, even within complex, multilingual, or nuanced textual content. Moreover, predictive and prescriptive analytics capabilities allow companies to forecast customer behavior, anticipate demands, and tailor marketing campaigns to target audiences more effectively.

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Regional Insights

Largest Region

In 2024, North America dominated the Text Analytics Market and is expected to maintain its leading position throughout the forecast period due to the region’s advanced technological infrastructure, early adoption of digital transformation initiatives, and strong presence of key market players. The increasing deployment of text analytics solutions across industries such as banking, financial services, healthcare, retail, and information technology in North America is driving substantial demand. Organizations in the region are leveraging text analytics to extract actionable insights from vast amounts of unstructured data generated through social media platforms, customer feedback, emails, surveys, and enterprise communications, enabling improved decision-making, enhanced customer experience management, and operational efficiency.

The presence of major technology vendors and analytics solution providers, coupled with significant research and development investments, has accelerated innovation in natural language processing, artificial intelligence, and machine learning, which are critical for advanced text analytics applications. Additionally, enterprises are increasingly adopting cloud-based and hybrid deployment models that allow scalable, flexible, and cost-effective analytics, further fueling market growth. The regulatory environment in North America, with a focus on data privacy and cybersecurity, encourages organizations to implement robust text analytics solutions that ensure compliance while deriving maximum value from unstructured data.

Furthermore, the growing emphasis on customer-centric strategies, predictive analytics, and real-time monitoring across industries reinforces the adoption of text analytics platforms. The high rate of digitalization, coupled with increasing awareness about the strategic importance of data-driven insights, positions North America as the dominant region in the Text Analytics Market. With its combination of technological maturity, supportive business environment, and strong adoption across multiple sectors, North America is expected to continue leading the global Text Analytics Market throughout the forecast period, setting a benchmark for analytics deployment and innovation worldwide.

Emerging Region

In the forecast period, South America is emerging as a significant region for the Text Analytics Market, showing strong potential for growth and increasing adoption of advanced analytics solutions across industries. Countries such as Brazil, Mexico, and Argentina are witnessing rising investments in digital transformation, cloud computing, and artificial intelligence, which are enabling enterprises to deploy scalable text analytics platforms. Organizations in banking, financial services, retail, healthcare, and telecommunications are beginning to leverage text analytics to extract actionable insights from unstructured data generated through social media, customer feedback, surveys, emails, and internal communications.

The growing focus on improving customer experience, optimizing operations, and supporting data-driven decision-making is driving the initial adoption of text analytics solutions in the region. Government initiatives promoting digitalization, smart city projects, and innovation hubs are creating a conducive environment for technology investment, while the emergence of local analytics solution providers offers affordable and customized platforms tailored to regional needs. Moreover, South America’s diverse linguistic landscape increases demand for text analytics tools capable of processing multiple languages and dialects, further highlighting the strategic importance of advanced solutions.

Although the region currently represents a smaller share of the global Text Analytics Market compared to North America or Europe, its increasing enterprise adoption, improving technological infrastructure, and supportive policy frameworks indicate that South America is an emerging market with strong long-term potential. As organizations in the region continue to recognize the value of unstructured data for customer insights, operational efficiency, and market intelligence, South America is poised to play a more prominent role in the global Text Analytics Market, attracting further investment and innovation in the coming years.

Recent Development

• In April 2025, IBM announced a landmark USD150 billion investment in the United States over five years, allocating more than USD30 billion specifically for research and development. This strategic commitment is aimed at accelerating innovation in mainframe systems and quantum computing, strengthening IBM’s technological capabilities and global leadership. The investment will support the development of advanced computing solutions, enhance enterprise infrastructure, and drive breakthroughs in complex computational applications, reinforcing IBM’s position as a key player in shaping the future of technology worldwide.
• In August 2025, IBM launched watsonx BI on IBM Cloud, integrating artificial intelligence-driven intelligence with a governed semantic model to provide reliable and consistent business insights. The platform is designed to empower organizations with accurate, actionable data for improved decision-making. Alongside this, IBM introduced AI-powered Text2SQL, enabling users to access and analyze data more efficiently by translating natural language queries into structured database queries, thereby democratizing data access and accelerating the generation of meaningful insights across enterprises.
• In February 2024, Google launched Gemini, a generative AI chatbot and advanced language model, as a successor to Bard. Gemini offers support for over 40 languages and is integrated with numerous Google services, including Android, Chrome, Photos, and Workspace. It features real-time web searching, detailed prompt customization, and creative persona-based interactions. By the end of 2025, Google plans to fully replace Google Assistant with Gemini across devices, expanding support to smart homes, tablets, and other hardware.
• In May 2025, Google launched Veo 3, an advanced AI video generator capable of integrating audio, including music and voices, perfectly synchronized with video content. This innovation represents a major leap in AI-generated media, transforming traditional silent or manually edited videos into fully immersive audiovisual experiences. By combining sophisticated AI-driven video and audio processing, Veo 3 enables creators and businesses to produce high-quality, dynamic content efficiently, enhancing engagement and storytelling capabilities across digital platforms and redefining the standards for automated video generation.

Key Market Players

• IBM Corporation
• Microsoft Corporation
• SAS Institute Inc.
• SAP SE
• Oracle Corporation
• Lexalytics, Inc.
• Clarabridge, Inc.
• Amazon Web Services, Inc.
• Google LLC
• Adobe Systems Incorporated

Report Scope:

In this report, the Global Text Analytics Market has been segmented into the following categories, in addition to the industry trends which have also been detailed below:

•  Text Analytics Market, By Analytics Type:

o   Sentiment Analysis

o   Entity Recognition

o   Keyword/Concept Extraction

o   Text Categorization

o   Predictive Analysis

• Text Analytics Market, By Application:

o   Customer Experience Management

o   Risk & Compliance Management

o   Human Resource Management

o   Market Intelligence

o   Others

• Text Analytics Market, By End User:

o   Banking, Financial Services, and Insurance

o   Retail and E-commerce

o   Healthcare and Life Sciences

o   Information Technology and Telecommunications

o   Manufacturing

o   Government and Public Sector

o   Others

• Text Analytics Market, By Region:

o   North America

§  United States

§  Canada

§  Mexico

o   Europe

§  Germany

§  France

§  United Kingdom

§  Italy

§  Spain

o   South America

§  Brazil

§  Argentina

§  Colombia

o   Asia-Pacific

§  China

§  India

§  Japan

§  South Korea

§  Australia

o   Middle East & Africa

§  Saudi Arabia

§  UAE

§  South Africa

Competitive Landscape

Company Profiles: Detailed analysis of the major companies present in the Global Text Analytics Market.

Available Customizations:

Global Text Analytics Market report with the given market data, TechSci Research offers customizations according to a company's specific needs. The following customization options are available for the report:

Company Information

• Detailed analysis and profiling of additional market players (up to five).

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