Text Analytics Market - Global Forecast 2025-2032

Text analytics is rapidly transforming enterprise intelligence, unlocking actionable insights from large volumes of unstructured text across diverse business functions. As organizations advance digital strategies, leveraging text analytics becomes fundamental for informed decision-making and workflow efficiency.

Market Snapshot: Text Analytics Market Growth and Trends

The Text Analytics Market expanded from USD 8.41 billion in 2024 to USD 10.07 billion in 2025 and is projected to reach USD 35.63 billion by 2032, demonstrating a CAGR of 19.76%.

Strong adoption is driven by expanding regulatory requirements, increasing customer engagement demands, and the proliferation of data generated through digital channels. In the current environment, senior leaders seek advanced solutions that support enhanced analytics, streamlined compliance, and competitive agility. Enterprises are prioritizing scalable deployments, adaptive architecture, and immediate value realization from their text analytics investments.

Scope & Segmentation

This report comprehensively examines text analytics technologies and their applications on a global scale, furnishing decision-makers with actionable comparisons for evaluating deployment strategies and assessing optimal vendor relationships.

• Technology: Includes Entity Recognition, Relationship Extraction, Semantic Analysis, Sentiment Analysis, Text Classification, and Topic Modeling, which enable granular understanding of meaning, emotion, and context within enterprise data streams.
• Application Areas: Covers Compliance Monitoring, Customer Experience Management, Document Management, Risk Management, and Social Media Monitoring, allowing organizations to address both operational and reputational objectives.
• Deployment Modes: Encompasses Cloud (Public, Private, Hybrid) and On Premise, offering tailored solutions for security policies, regulatory compliance, and organizational agility.
• Offering Types: Analysis of both Software and Services, supporting a range of integration needs and support requirements.
• End-use Industries: Spans Banking Financial Services Insurance, Government Defense, Healthcare, IT Telecom, and Retail, reflecting sector-specific drivers and compliance landscapes.
• Organization Size: Addresses the differentiated requirements of Large Enterprises and Small Medium Enterprises by deployment flexibility and cost-effectiveness.
• Geographies: Assesses opportunities and challenges across the Americas (United States, Canada, Mexico, Latin America), Europe, Middle East & Africa (covering major markets), and Asia-Pacific (including China, India, Japan, Australia, Southeast Asia).
• Leading Companies Assessed: Profiles Microsoft Corporation, International Business Machines Corporation, Google LLC, Amazon.com Inc., SAS Institute Inc., Oracle Corporation, SAP SE, OpenText Corporation, Lexalytics Inc., Expert System S.p.A. for a comprehensive view of the competitive landscape.

The segmentation enables stakeholders to identify growth areas, address regional and industry-specific requirements, and benchmark vendors according to specialized capabilities and service offerings.

Key Takeaways

• Text analytics supports digital initiatives by processing unstructured sources such as customer feedback and regulatory filings, enabling informed decisions and improved business outcomes.
• Deployment of advanced AI and natural language processing, including neural networks and deep learning models, enhances analytics accuracy—particularly for sentiment detection and entity extraction.
• Hybrid and cloud architectures allow organizations to meet data sovereignty and compliance mandates while scaling analytics across geographies and business units.
• Adoption of multilingual text analytics, powered by transformer-based models, equips organizations for global operations, unlocking insights from diverse language datasets.
• Low-code and no-code platforms extend access to text analytics tools beyond IT, empowering operational teams to design and manage analytics workflows.
• Sectoral adoption patterns reflect unique priorities: finance and retail focus on customer sentiment and real-time oversight, while healthcare and government emphasize robust data governance and secure, localized deployments.

Tariff Impact: Navigating the Effects of United States Tariffs

The introduction of United States tariffs in 2025 is driving text analytics vendors to adapt supply chains, reevaluate licensing terms, and prioritize regional data center investments. In response, providers are accelerating domestic manufacturing and developing modular hardware to mitigate cost pressures. Enterprises—particularly in government and defense—are increasing adoption of hybrid licensing, on-premise, and private cloud deployments. These shifts are fostering innovations in software and architecture, helping organizations maintain adaptability while optimizing costs and compliance.

Methodology & Data Sources

This research synthesizes primary interviews with industry leaders, structured surveys of decision-makers, and in-depth secondary analysis of leading literature, regulatory sources, and proprietary data. Data triangulation and thorough peer review ensure validity and transparency throughout the research process.

Why This Report Matters: Text Analytics for Strategic Decision-Makers

• Delivers a robust framework for assessing text analytics investments and deployment models to align with both operational and regulatory standards.
• Enables leaders to anticipate disruption points and track adoption trends across regions, facilitating risk management and digital transformation planning.
• Includes competitive benchmarking and granular market segmentation, helping organizations strategize under evolving international trade dynamics.

Conclusion

Text analytics sits at the core of intelligent automation and strategic foresight for modern enterprises. With the guidance of this report, leaders can capitalize on emerging opportunities and successfully navigate an increasingly complex information environment.