Natural Language Generation Market Size is Expected to grow at higher CAGR 29.4 % Over the Forecast Period.
Natural language generation is a software process that exploits artificial intelligence and computational linguistics to transform structured data into natural language. Natural language generation facilitates easier and faster decision-making processes. It can simplify complex tasks by converting machine language into natural language. It is an indispensable component in the spoken dialogue system utilized to bridge the communication gap between humans and machines. The types of natural language generation software available in the market are basic natural language generation, template natural language generation, and advanced natural language generation. Basic natural language generation software relies on excel functions to translate data into text. Template natural language generation software utilizes template-driven mode to produce the desired output.
| Report Metric | Details |
|---|---|
| Base Year | 2021 |
| Study Period | 2017-2029 |
| Forecast Period | 2023-2031 |
| CAGR | 29.4% |
| Market Size | 1320 |
| Fastest Growing Market | Asia Pacific |
| Largest Market | North America |
| Report Coverage | Revenue Forecast, Competitive Landscape, Growth Factors, Environment & Regulatory Landscape and Trends |
| Geographies Covered |
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Advanced natural language generation software can communicate as humans, as well as understands the intent, increases the intelligence of the product, and displays a result in an understandable and readable manner. Growing research and development activities to explore the potential of NLG among several industries, such as weather forecasting, healthcare, and journalism, are some of the trends in the market. As of now, this software is a necessary feature for most of the modern analytics and business intelligence platforms. The Pollen forecast system for Scotland utilizes template natural language generation software to predict pollen levels in several parts of Scotland. It takes six numbers as input from historical data and generates a brief textual summary of estimated pollen levels as output.
Increasing customer preferences towards advanced technologies and the emergence of big data and akin technologies boost market growth. NLG-based tools are widely used among enterprises as it provides business information that helps to make data-driven decisions. For instance, NLG tools are extensively used in chatbots. The natural language capabilities possessed by these tools aid chatbots to interact more humanly. NLG allows chatbots to deliver an individualized user experience to customers while resolving queries, complaints, and virtual assistants for online processes. Therefore, companies are widely adopting NLG software to enhance their customer experience and satisfaction. Furthermore, it also employs machine learning algorithms to imitate the analysis technique done by human analysts. Data generation performed by this technology streamlines business operations, thereby increasing the efficiency of the organizations. However, lack of expertise in tandem with the lack of awareness among the customers concerning the benefits of NLG technology acts as a threat impeding the market growth.
The software segment, among other solution types, is a primary revenue generator and is anticipated to continue the trend in upcoming years. NLG software encompasses various tools, platforms, engines, and interfaces that aid in the conversion of machine language into understandable human language. NLG software helps non-technical employees and data analysts to generate data by dint of deep learning and to produce fruitful insights from digital information. The service segment is estimated to grow with the highest CAGR, as it offers a gamut of services to enterprises that utilize natural language generation. These services help companies in the effective utilization of natural language generation tools, thereby accelerating the service segment’s demand.
The risk and compliance management segment possess significant market share, as NLG allows compliance teams to examine and identify critical information stored in structured data sets. The technique also helps to discover the abnormalities and hidden patterns from large data sets by utilizing topic tagging and sentiment analysis. The predictive maintenance segment is projected to snowball during the forecast period, as data analysis experts can make use of the technology to swiftly deliver crucial information to other people in the organization. NLG tools can be applied to the narrative component of suspicious reports, which helps in the detection of fraud and anti-money laundering issues. It converts data into text with high precision and is currently utilized in the automatic generation of suspicious transaction reports. By using natural language generation tools, data is processed quickly and accurately, reducing reporting time and anomalies.
NLG helps business organizations to improve their sales by customer experience management. Companies use customer experience management to augment customer loyalty and satisfaction. It offers personalized and customer-centric messages by extracting data from intricate sources to generate natural language content. Natural language generation tools automate report writing by translating the information into human language. This delivers precise and accurate performance reports, impacting the performance of organizations. Large enterprises dominate the market due to the initial seed money invested for software set-up. Small scale and medium scale enterprises fail to fully adopt the technology, owing to the high initial investment. However, the increasing number of cloud providers and the cost-effective nature of cloud NLG tools are expected to revise present scenarios.
The on-premise segment holds customer-hosted NLG solutions; it allows an organization to take the helm of the complete data processed in its IT environment. This eliminates the risk of data accessed by a third party or unauthorized author. Furthermore, some organizations are subjected to regulations to host all the processes in house, thereby calling the demand fo the on-premise deployment of NLG tools. The cloud segment holds the largest share among other deployment modes and is anticipated to retain supremacy during the forecast period. It offers less operational cost, flexibility, and quick setup.
The BFSI segment (banking, financial services, and insurance) held the lion’s share in the market during the year 2018. This is due to the fierce competition among banks, stringent government policies, and escalating demand for transparency urging banking sectors to incorporate automation and artificial intelligence tools. The technology enables banking and insurance companies to automate the fraud detection processes occurring in the organizations. It also allows them to maintain a good relationship with customers by initiating personalized communication between the users and banking organizations. These factors fueled the natural language generation market growth in the banking, financial, and insurance sector.
The retail and e-commerce segment is anticipated to grow with the highest CAGR during the forecast period. Natural language generation technology assists marketers to address customer preferences and requirements, offering them customized suggestions on the basis of their recent search histories. Therefore, technology increases the probability of buying goods, providing momentum to the NLG market in the retail and e-commerce sector.
The on-premise segment holds customer-hosted NLG solutions; it allows an organization to take the helm of the complete data processed in its IT environment. This eliminates the risk of data accessed by a third party or unauthorized author. Furthermore, some organizations are subjected to regulations to host all the processes in house, thereby calling the demand fo the on-premise deployment of NLG tools. The cloud segment holds the largest share among other deployment modes and is anticipated to retain supremacy during the forecast period. It offers less operational cost, flexibility, and quick setup.
The BFSI segment (banking, financial services, and insurance) held the lion’s share in the market during the year 2018. This is due to the fierce competition among banks, stringent government policies, and escalating demand for transparency urging banking sectors to incorporate automation and artificial intelligence tools. The technology enables banking and insurance companies to automate the fraud detection processes occurring in the organizations. It also allows them to maintain a good relationship with customers by initiating personalized communication between the users and banking organizations. These factors fueled the natural language generation market growth in the banking, financial, and insurance sector.
The retail and e-commerce segment is anticipated to grow with the highest CAGR during the forecast period. Natural language generation technology assists marketers to address customer preferences and requirements, offering them customized suggestions on the basis of their recent search histories. Therefore, technology increases the probability of buying goods, providing momentum to the NLG market in the retail and e-commerce sector.
They are increasingly collaborating and partnering with technology providers to blend natural language generation with innovative and new technologies.
