Global Natural Language Generation Market
市场规模（十亿美元）
CAGR :
% 
 Forecast Period |
2024 –2031 |
 Market Size (Base Year) |
USD 899.47 Million |
 Market Size (Forecast Year) |
USD 4,651.29 Million |
 CAGR |
% |
| Major Markets Players |
|
>全球自然语言生成市场，按组件（软件和服务）、应用（欺诈检测和反洗钱、预测性维护、风险和合规管理、客户体验管理等）、业务功能（财务、法律、营销和销售、运营和人力资源）、部署模型（云和本地）、组织规模（中小型企业和大型企业）、垂直行业（银行、金融服务和保险、零售和电子商务、政府和国防、医疗保健和生命科学、制造业、电信和 IT、媒体和娱乐、能源和公用事业等）划分 - 行业趋势和预测到 2031 年。
自然语言生成市场分析和规模
在商业智能 (BI) 和分析领域，自然语言生成 (NLG) 通过将复杂的数据洞察转化为易于理解的叙述和摘要，发挥着至关重要的作用。NLG 算法分析大型数据集并生成文本报告、仪表板和演示文稿，突出关键发现、趋势和建议。此功能使业务利益相关者（从高管到分析师）能够快速掌握洞察并做出明智的决策。NLG 通过提供针对特定用户查询量身定制的自动化和个性化洞察来增强 BI 工具，从而提高数据可访问性并提高全球组织决策流程的整体效率。
2023 年全球自然语言生成市场规模为 8.9947 亿美元，预计到 2031 年将达到 46.5129 亿美元，2024 年至 2031 年预测期内的复合年增长率为 22.8%。除了市场价值、增长率、细分市场、地理覆盖范围、市场参与者和市场情景等市场洞察外，Data Bridge 市场研究团队策划的市场报告还包括深入的专家分析、进出口分析、定价分析、生产消费分析和 pestle 分析。
报告范围和市场细分
|
报告指标 |
细节 |
|
预测期 |
2024-2031 |
|
基准年 |
2023 |
|
历史岁月 |
2022 (可定制为 2016-2021) |
|
定量单位 |
收入（单位：十亿美元）、销量（单位：台）、定价（美元） |
|
涵盖的领域 |
组件（软件和服务）、应用程序（欺诈检测和反洗钱、预测性维护、风险和合规管理、客户体验管理等）、业务功能（财务、法律、营销和销售、运营和人力资源）、部署模型（云和本地）、组织规模（中小型企业和大型企业）、垂直行业（银行、金融服务和保险、零售和电子商务、政府和国防、医疗保健和生命科学、制造业、电信和 IT、媒体和娱乐、能源和公用事业等） |
|
覆盖国家 |
U.S., Canada and Mexico in North America, Germany, France, U.K., Netherlands, Switzerland, Belgium, Russia, Italy, Spain, Turkey, Rest of Europe in Europe, China, Japan, India, South Korea, Singapore, Malaysia, Australia, Thailand, Indonesia, Philippines, Rest of Asia-Pacific (APAC) in the Asia-Pacific (APAC), Saudi Arabia, U.A.E, South Africa, Egypt, Israel, Rest of Middle East and Africa (MEA) as a part of Middle East and Africa (MEA), Brazil, Argentina and Rest of South America as part of South America. |
|
Market Players Covered |
Amazon Web Services, Inc. (U.S.), IBM (U.S.), Yseop (France), AX Semantics (Germany), 2txt - natural language generation GmbH (Germany), Linguastat Inc. (U.S.), Textual Relations AB. ( Gothenburg), newsrx. (U.S.), Arria NLG (U.K.), Artificial Solutions (Sweden), Restresco (U.S.), Conversica (U.S.), NewsRx (U.S.), CoGenTax Inc. (U.S.) , Phrasetech (Sweden), vPhrase (India) |
|
Market Opportunities |
|
Market Definition
Virtual reality content creation involves the development and production of immersive digital experiences that users can engage with in a virtual environment. This process includes designing and crafting 3D models, environments, animations, and interactive elements tailored for VR platforms. Content creators utilize specialized tools and techniques to bring these virtual worlds to life, offering users immersive and interactive experiences across various applications such as gaming, education, training, simulation, and entertainment.
Natural Language Generation Market Dynamics
Drivers
- Growing Adoption of Automated Content Generation
Businesses are increasingly turning to NLG solutions to automate the creation of textual content such as reports, summaries, articles, and product descriptions. This trend is driven by the need for efficiency gains and cost savings in content production processes. NLG enables organizations to generate large volumes of content quickly while maintaining consistency and quality. Moreover, as digital content consumption rises, NLG helps meet the demand for personalized and relevant content tailored to specific audiences. This adoption is supported by advancements in AI and NLP technologies, which continue to improve the accuracy and naturalness of generated content, further driving the market's growth.
- Expansion of the Internet of Things (IoT)
IoT devices generate massive amounts of data from sensors, machines, and connected devices across various industries such as manufacturing, healthcare, transportation, and smart cities. NLG plays a crucial role in interpreting and communicating insights derived from this IoT-generated data in a human-readable format. By converting complex data streams into actionable insights and reports, NLG enables businesses to optimize operations, improve decision-making processes, and enhance efficiencies. This integration of NLG with IoT facilitates real-time monitoring, predictive maintenance, and personalized customer experiences, driving demand for NLG solutions in IoT-driven ecosystems worldwide.
Opportunities
- Emergence of Industry-Specific Applications
As different sectors recognize the potential of NLG to streamline operations and enhance decision-making, tailored solutions are being developed to address specific industry challenges. In healthcare, NLG is used to generate patient reports and medical summaries, improving efficiency and accuracy in healthcare delivery. In financial services, NLG aids in automating financial reporting and market analysis, enabling faster insights and informed decision-making. Similarly, in retail and e-commerce, NLG powers personalized product recommendations and customer service interactions, enhancing user experience and driving sales. These industry-specific applications highlight NLG's versatility and its ability to cater to diverse business needs, fueling its adoption and market growth globally.
- Rising Importance of Customer Experience
NLG enables businesses to deliver personalized and contextually relevant interactions through chatbots, virtual assistants, and automated customer service solutions. Organizations can respond to customer queries promptly, provide tailored recommendations, and enhance overall engagement by employing NLG. This capability improves customer satisfaction, increases retention rates and strengthens brand loyalty. As businesses prioritize delivering seamless and personalized experiences, NLG plays a crucial role in meeting these expectations by automating the generation of human-such as responses and ensuring consistent, high-quality interactions across digital channels.
Restraints/Challenges
- High Initial Costs
Implementing NLG solutions involves substantial upfront investments in software development, customization, and integration with existing systems. Organizations also incur costs for training staff and ensuring the technology meets specific business needs. These financial barriers can be particularly challenging for smaller enterprises or those operating on tighter budgets, limiting their ability to adopt NLG at scale. Moreover, ongoing maintenance and upgrades further contribute to the total cost of ownership, requiring careful budget allocation and ROI justification for widespread adoption across industries.
- Shortage of Skilled Professionals
Developing and deploying NLG solutions requires expertise in artificial intelligence, natural language processing, data analytics, and software development. However, there is a scarcity of professionals with specialized knowledge in these areas, slowing down the adoption and implementation of NLG technologies across industries. This shortage increases competition for qualified talent, drives up hiring costs, and may delay the development of innovative NLG applications.
This market report provides details of new recent developments, trade regulations, import-export analysis, production analysis, value chain optimization, market share, impact of domestic and localized market players, analyses opportunities in terms of emerging revenue pockets, changes in market regulations, strategic market growth analysis, market size, category market growths, application niches and dominance, product approvals, product launches, geographic expansions, technological innovations in the market. To gain more info on the market contact Data Bridge Market Research for an Analyst Brief, our team will help you take an informed market decision to achieve market growth.
Natural Language Generation Market Scope
The market is segmented on the basis of component, application business function, deployment model, organization size, and industry vertical. The growth amongst these segments will help you analyze meagre growth segments in the industries and provide the users with a valuable market overview and market insights to help them make strategic decisions for identifying core market applications.
Component
- Solution
- Services
Application
- Fraud Detection and Anti-Money Laundering
- Predictive Maintenance
- Risk and Compliance Management
- Customer Experience Management
- Others
Business Function
- Finance
- Legal
- Marketing and Sales
- Operations
- Human Resources
Deployment Model
- Cloud
- On-Premises
Organization size
- Large Enterprises
- Small and Medium-Sized Enterprises
Industry Vertical
- Banking
- Financial Services
- Insurance
- Retail and Ecommerce
- Government and Defence
- Healthcare and Life Sciences
- Manufacturing
- Telecom and IT
- Media and Entertainment
- Energy
- Utilities
- Others
Natural Language Generation Market Region Analysis/Insights
The market is analysed and market size, volume information is provided by component, application business function, deployment model, organization size, and industry vertical as referenced above.
The countries covered in the market report are U.S., Canada, Mexico, Brazil, Argentina, the Rest of South America, Germany, Italy, U.K., France, Spain, Netherlands, Belgium, Switzerland, Turkey, Russia, Rest of Europe, Japan, China, India, South Korea, Australia, Singapore, Malaysia, Thailand, Indonesia, Philippines, Rest of Asia-Pacific, Saudi Arabia, U.A.E., South Africa, Egypt, Israel, Rest of the Middle East and Africa.
由于先进技术的广泛采用以及渴望发挥其潜力的各大公司投入大量资金，北美占据了市场主导地位。例如，2019 年 9 月，管理公司 NextStage AM 宣布对知名 NLG 解决方案提供商 Yseop 进行投资。这项投资旨在加强 Yseop 的全球扩张努力，并加快 NLG 解决方案在美国各个领域的部署，凸显了该地区在推动 NLG 创新和增长方面的关键作用。
亚太地区预计将在市场上实现增长，因为该地区注重提升消费者服务，从而推动竞争差异化和收入增长。该地区致力于利用先进技术实现客户互动和个性化体验，这为其带来了战略优势。通过优先考虑消费者需求并通过自然语言生成的创新应用来改进服务交付，亚太地区的企业不仅满足了市场需求，而且超越了市场需求，从而巩固了其在这个快速发展的领域的领导地位。
全球销售自动化软件市场报告的国家部分还提供了影响单个市场因素和国内市场法规变化，这些因素和变化会影响市场的当前和未来趋势。消费量、生产地点和产量、进出口分析、价格趋势分析、原材料成本、下游和上游价值链分析等数据点是用于预测单个国家市场情景的一些主要指标。此外，在提供国家数据的预测分析时，还考虑了全球品牌的存在和可用性以及它们因来自本地和国内品牌的激烈或稀少竞争而面临的挑战、国内关税和贸易路线的影响。
竞争格局和自然语言生成市场份额分析
市场竞争格局按竞争对手提供详细信息。详细信息包括公司概况、公司财务状况、收入、市场潜力、研发投资、新市场计划、全球影响力、生产基地和设施、生产能力、公司优势和劣势、产品发布、产品宽度和广度、应用主导地位。以上提供的数据点仅与公司对市场的关注有关。
市场上的一些主要参与者包括：
- 亚马逊网络服务公司（美国）
- IBM（美国）
- Yseop（法国）
- AX Semantics（德国）
- 2txt-自然语言生成有限公司（德国）
- Linguastat Inc.（美国）
- 文本关系 AB。（哥德堡）
- newsrx。（美国）
- Arria NLG（英国）
- 人工解决方案（瑞典）
- Restresco（美国）
- Conversica（美国）
- NewsRx（美国）
- CoGenTax Inc.（美国）
- Phrasetech（瑞典）
- vPhrase（印度）
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研究方法
Data collection and base year analysis are done using data collection modules with large sample sizes. The stage includes obtaining market information or related data through various sources and strategies. It includes examining and planning all the data acquired from the past in advance. It likewise envelops the examination of information inconsistencies seen across different information sources. The market data is analysed and estimated using market statistical and coherent models. Also, market share analysis and key trend analysis are the major success factors in the market report. To know more, please request an analyst call or drop down your inquiry.
The key research methodology used by DBMR research team is data triangulation which involves data mining, analysis of the impact of data variables on the market and primary (industry expert) validation. Data models include Vendor Positioning Grid, Market Time Line Analysis, Market Overview and Guide, Company Positioning Grid, Patent Analysis, Pricing Analysis, Company Market Share Analysis, Standards of Measurement, Global versus Regional and Vendor Share Analysis. To know more about the research methodology, drop in an inquiry to speak to our industry experts.
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