Future of Natural Language Generation Global Market Report 2025 to 2034

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What are the recent trends in market size and growth for the natural language generation (nlg) market?

The natural language generation (NLG) market size has grown exponentially in recent years. It will grow from $0.88 billion in 2024 to $1.06 billion in 2025 at a compound annual growth rate (CAGR) of 21.4%. The growth in the historic period can be attributed to Increased data availability, rise of big data analytics, improvements in natural language processing (NLP), demand for data-driven insights, and integration with business intelligence (BI) tools.

The natural language generation (NLG) market size is expected to see exponential growth in the next few years. It will grow to $2.32 billion in 2029 at a compound annual growth rate (CAGR) of 21.5%. The growth in the forecast period can be attributed to rapid advances in deep learning, integration with voice assistants, increasing demand for content automation, growing importance of explain ability, and expanding use cases in healthcare. Major trends in the forecast period include AI-powered creativity, ethical ai and bias mitigation, technological advancements, product developments, and real-time language translation.

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What have been the primary factors driving the natural language generation (nlg) market’s growth?

Increasing volume and variety of data are expected to propel the growth of the natural language generation (NLG) market going forward. Volume and variety of data refers to the immense quantity and diverse types of information generated, collected, and processed by systems, applications, and devices, reflecting the ever-growing scale and heterogeneity of data in each context. Natural Language Generation (NLG) is used to effectively communicate insights from the increasing volume and variety of data by transforming complex datasets into coherent and understandable narratives, enabling businesses to derive meaningful information and make informed decisions in a more accessible and human-readable format. For instance, in February 2023, G2.com, a US-based software marketplace company, revealed that 87.8% of companies increased their data investments, which is 41% up from 2022. Therefore, the increasing volume and variety of data are driving the next language generation market.

What are the key segments within the natural language generation (nlg) market?

The natural language generation (NLG) market covered in this report is segmented –

1) By Deployment: On-Premise, Cloud

2) By Organization Size: Small and Medium Enterprises (SMEs), Large Enterprises

3) By Application: Fraud Detection, Predictive Maintenance, Risk And Compliance Management, Performance Management

4) By Vertical: Banking, Financial Market Research And Insurance (BFSI), Retail And Ecommerce, Government And Defense, Healthcare And Life Sciences, Manufacturing, Telecom, IT, Media & Entertainment And Entertainment, Energy And Utilities

Subsegments:

1) By On-Premise: Local Server Installations, Customized NLG Software Solutions, Integrated Enterprise Systems, Self-Hosted Data Processing Systems

2) By Cloud: Software As A Service (Saas) NLG Platforms, API-Based NLG Market Research, Cloud Storage And Processing Solutions, Multi-Tenant Cloud Environments, Subscription-Based NLG Applications

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Which key players are shaping the natural language generation (nlg) market?

Major companies operating in the natural language generation (NLG) market report are Amazon.com Inc., Alphabet Inc., Microsoft Corporation, International Business Machines Corporation, Deloitte Touche Tohmatsu Limited, Oracle Corporation, SAP SE, NVIDIA Corporation, Infosys Limited, Baidu Inc., SAS Institute Inc., Conversica Inc., Automated Insights Inc., OpenAI Inc., Narrative Science Inc., Persado Inc., Arria NLG plc, Hugging Face Inc., Retresco GmbH, AX Semantics GmbH, vPhrase Analytics Solutions Pvt. Ltd., Yseop SA, Phrasetech, Narrativa, Gabriele Sarti

How will emerging trends drive the natural language generation (nlg) market throughout the forecast period?

Major companies operating in natural language generation (NLG) are developing innovative technology and products by integrating stacks purpose-built for AI-powered applications. Integrating stacks refers to the process of combining different software components or systems to work together seamlessly. A software stack is a collection of independent components that work together to support the execution of an application. For instance, in 2023, Microsoft Corporation, a US-based technology company, launched the Azure OpenAI Service. This ecosystem adapts to the growing needs of developers and organizations. Azure offers a full, integrated stack purpose-built for AI-powered applications and provides a set of pre-built task-optimized NLU/NLG capabilities powered by Azure OpenAI, giving it a competitive edge and superior performance. These models can be adapted to tasks such as content summarization, image understanding, semantic search, and natural language to code translation.

How do regional factors impact the natural language generation (nlg) market, and which region is the largest contributor?

North America was the largest region in the natural language generation (NLG) market in 2024. Asia-Pacific is expected to be the fastest-growing region in the forecast period. The regions covered in the natural language generation (NLG) market report are Asia-Pacific, Western Europe, Eastern Europe, North America, South America, Middle East, Africa.

What Does The Natural Language Generation (NLG) Market Report 2025 Offer?

The natural language generation (nlg) market research report from The Business Research Company offers global market size, growth rate, regional shares, competitor analysis, detailed segments, trends, and opportunities.

Natural language generation (NLG) is a subfield of artificial intelligence (AI) and natural language processing (NLP) that focuses on the automatic generation of human-readable text or speech from structured data or other non-linguistic forms. NLG aims to transform data into coherent and contextually relevant narratives that humans can easily understand.

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