Natural Language Generation

March 31, 2026
|By Julia Schönau

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NLG is a key component of Natural Language Processing (NLP) and refers to the process by which software converts structured data into fluent, coherent, and grammatically correct text. This technology enables systems to generate human-like content, such as dialogue responses, reports, or product descriptions. The goal is for systems to not only understand human language but also to independently produce linguistic output.

 

How Natural Language Generation Works

The generation of text using NLG occurs in several steps. First, the underlying data is analyzed to identify relevant information and patterns. Next, a plan for the text structure is created, determining which content should be presented and in what order. In the subsequent phases, sentences are aggregated and grammatical rules are applied to form a linguistically correct and natural-sounding text. Finally, the final text output is generated based on predefined templates or formats.

 

Applications of Natural Language Generation in Business

Natural language generation is used in a wide range of business areas. One key application is the automation of customer service. For chatbots and voicebots , Natural Language Generation is essential for responding to user inquiries with relevant and understandable answers. The technology enables the improvement of customer communication through personalized messages and contributes to increased efficiency and the freeing up of human resources.

 

Benefits of Using NLG

By using natural language generation in customer service, companies benefit from a massive reduction in response times, as inquiries are answered in milliseconds—effectively in real time. The technology ensures consistent language quality that is free of human errors and always aligns with the company’s tone. By resolving recurring standard inquiries fully automatically and accurately, procedural costs per ticket are significantly reduced. This leads to a noticeable reduction in the workload for service staff, who thereby gain valuable capacity to handle complex and consultation-intensive customer issues.

 

Frequently Asked Questions (FAQ)

Natural Language Generation (NLG) deals with the automatic generation of natural language from data. Natural Language Understanding (NLU), on the other hand, focuses on computers’ ability to understand human language. While NLU analyzes the meaning and intent of text or spoken language, NLG enables the formulation of responses or reports. Both are subfields of Natural Language Processing (NLP) and often work together, for example in conversational AI systems such as chatbots or voicebots.

NLG is used across various industries to improve the quality of communication. This primarily includes automated customer communication through the generation of responses for chatbots and voicebots, which provide customers with information independently without the need for human intervention. In businesses, it also leads to efficiency gains through the automated creation of reports (e.g., in the finance or sports sectors) or the generation of product descriptions in e-commerce.

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