Although we don’t always realize it, natural language processing (NLP) is an integral part of modern business technology. Large Language Models (LLMs), which have become prominent with ChatGPT, are a subset of this broad field.

But are ChatGPT or Google Bard the best for all business tasks? Of course not! What then are other business applications of NLP, and how does natural language processing technology benefit business and shape its future?

What is natural language processing?

Natural language processing (NLP) is a technology that enables machines to understand, interpret and generate human language. Its main goal is to allow human-machine communication in natural human speech. To carry on a casual conversation, NLP models must be able to understand context, linguistic nuances and even jokes and sarcasm.

Only large language models (LLMs) can perform these most difficult tasks. Thanks to the vast amount of data they have been trained on, they can understand the subtleties of language and generate answers that are not only technically correct but also sound natural and human.

However, NLP is not just about big language models. Indeed, many of the applications of NLP do not require such powerful tools. If AI is processing credit applications, its language skills don’t need to be great. All it needs is to learn how to search through various types of templates and forms and find the fields in them that contain the necessary data. Such models are much smaller, simpler and require less computing power than LLM.

Why does your company need NLP?

Your company needs NLP first and foremost so that it can be managed based on data, and so that your employees don’t have to do necessary but simple and repetitive tasks and can focus more on the important tasks. But what specifically can artificial intelligence do for you?

  1. Listen to your customers. Analyze the tone and content of statements
  2. NLP enables a better understanding of customers by analyzing texts published on social media. Sentiment analysis and social listening, one application of NLP, helps companies understand what customers think about their products or services. For this purpose, you can try the following tools: Sentione, Brand24 or Hootsuite.

  3. Don’t waste time searching. Finding information in scanned documents
  4. Although soon all company documents will have to be digital, there are still many companies sending out paper invoices and collecting fading receipts. Therefore, the second area where NLP can help is in finding information in company documents. An important part of machine understanding of what has been scanned is to distinguish relevant from irrelevant data. That is, recognizing essential information from, for example, the branding of the company that sent the document or accidental distortions.

    The recognized documents, or the information read from them, are then transferred to a digital database. In this way, they are very easy to find. What’s more, they can provide input for further actions, for example:

    Posting the expense from the photographed receipt, Entering the date of the meeting in the digital calendars of those invited to the charity concert, either Sending a personalized email to the customer to encourage feedback after the complaint process is complete.
  5. Respond quickly to threats and detect anomalies.
  6. Language analysis can identify disturbing patterns that may indicate potential fraud or attacks. For example, a bank can monitor conversations to detect attempts to defraud customers, and your company can notice unusual occurrences. Other similar examples include:

    Remote work reports – when someone forgets to turn off the hour meter overnight, Social media analysis – when suddenly there are an unusually high number of mentions of your company or The analysis of report files (log files) – helps detect errors in the functioning of the software.
  7. Benefit from the experience of others. Knowledge management
  8. NLP can also contribute to better knowledge management in the organization by automatically creating meeting summaries and notes. This way, information is more easily accessible to all team members. Also, searching company documents on the intranet, the product knowledge base, or finding all purchases and documents related to a single customer can be surprisingly easy using NLP.

  9. Skip repetitive steps. Automate natural language processing of documents
  10. Natural language processing makes it possible to automate tedious tasks such as document processing, leading to time savings and increased productivity.

    This is because automatic document processing primarily saves time and relieves employees from performing tedious and repetitive tasks that require high precision.

    Let’s start with the simple transcription of data from paper documents into customer service programs. It may mean many hours of moving your eyes from a black-and-white table to a monitor screen, or it may be limited to putting a paper contract into a scanner and possibly handling ambiguities and exceptions.

    However, automation in natural language processing is not just about handling written documents. AI can, using speech recognition, (STT), speech-to-text systems, create meeting summaries and notes, as they do, among others: Otter, Rev, or Descript.

Areas of application of AI and NLP in business

AI and natural language processing have many applications in business. Popular uses of these technologies in business are shown in the table below:

Type of input data
Examples of AI & NLP applications
Fixed written documents Processing of insurance applications
Personalized automated mail handling
Fixed spoken language Automatic creation of subtitles for movies
Creating bibliographic suggestions
Vivid written language Chatbots on e-commerce sites
Social media content moderation
Live spoken language Voice machine operation
Therapeutic voicebots
Many written languages Automatic localization of mobile applications
Many spoken languages Synchronous translation of international conferences
Natural Language Processing

Natural language processing in the future

Natural language processing (NLP) and artificial intelligence (AI) bring many benefits to business, from automation and increased efficiency to better understanding of customers, to creating natural user interfaces and knowledge management. These technologies are not only crucial to how companies operate today, but also have great potential for the future, opening up new opportunities for innovation and growth.

The future of natural language processing looks promising. It is marked by the unbelievably rapid development of LLMs, which are increasingly powerful and use multimodal solutions, that is, they learn to understand images and sound.

As a result, the technology is likely to become increasingly advanced, enabling machines to understand and generate human language even better. Given the achievements of researchers at Stanford University, who are successfully experimenting with digital agents that autonomously learn the language in a digital environment to accomplish their goals – the future of NLP looks bright and fascinating.

If you like our content, join our busy bees community on Facebook, Twitter, LinkedIn, Instagram, YouTube, Pinterest.

Natural Language Processing (NLP). 5 key benefits for business | AI in business #5 robert whitney avatar 1background

Author: Robert Whitney

JavaScript expert and instructor who coaches IT departments. His main goal is to up-level team productivity by teaching others how to effectively cooperate while coding.

AI in business:

  1. Threats and opportunities of AI in business (part 1)
  2. Threats and opportunities of AI in business (part 2)
  3. AI applications in business - overview
  4. AI-assisted text chatbots
  5. Business NLP today and tomorrow
  6. The role of AI in business decision-making
  7. Scheduling social media posts. How can AI help?
  8. Automated social media posts
  9. New services and products operating with AI
  10. What are the weaknesses of my business idea? A brainstorming session with ChatGPT
  11. Using ChatGPT in business
  12. Synthetic actors. Top 3 AI video generators
  13. 3 useful AI graphic design tools. Generative AI in business
  14. 3 awesome AI writers you must try out today
  15. Exploring the power of AI in music creation
  16. Navigating new business opportunities with ChatGPT-4
  17. AI tools for the manager
  18. 6 awesome ChatGTP plugins that will make your life easier
  19. 3 grafików AI. Generatywna sztuczna inteligencja dla biznesu
  20. What is the future of AI according to McKinsey Global Institute?
  21. Artificial intelligence in business - Introduction
  22. What is NLP, or natural language processing in business
  23. Automatic document processing
  24. Google Translate vs DeepL. 5 applications of machine translation for business
  25. The operation and business applications of voicebots
  26. Virtual assistant technology, or how to talk to AI?
  27. What is Business Intelligence?
  28. Will artificial intelligence replace business analysts?
  29. How can artificial intelligence help with BPM?
  30. AI and social media – what do they say about us?
  31. Artificial intelligence in content management
  32. Creative AI of today and tomorrow
  33. Multimodal AI and its applications in business
  34. New interactions. How is AI changing the way we operate devices?
  35. RPA and APIs in a digital company
  36. The future job market and upcoming professions
  37. AI in EdTech. 3 examples of companies that used the potential of artificial intelligence
  38. Artificial intelligence and the environment. 3 AI solutions to help you build a sustainable business
  39. AI content detectors. Are they worth it?
  40. ChatGPT vs Bard vs Bing. Which AI chatbot is leading the race?
  41. Is chatbot AI a competitor to Google search?
  42. Effective ChatGPT Prompts for HR and Recruitment
  43. Prompt engineering. What does a prompt engineer do?
  44. AI Mockup generator. Top 4 tools
  45. AI and what else? Top technology trends for business in 2024
  46. AI and business ethics. Why you should invest in ethical solutions
  47. Meta AI. What should you know about Facebook and Instagram's AI-supported features?
  48. AI regulation. What do you need to know as an entrepreneur?
  49. 5 new uses of AI in business
  50. AI products and projects - how are they different from others?
  51. AI-assisted process automation. Where to start?
  52. How do you match an AI solution to a business problem?
  53. AI as an expert on your team
  54. AI team vs. division of roles
  55. How to choose a career field in AI?
  56. Is it always worth it to add artificial intelligence to the product development process?
  57. AI in HR: How recruitment automation affects HR and team development
  58. 6 most interesting AI tools in 2023
  59. 6 biggest business mishaps caused by AI
  60. What is the company's AI maturity analysis?
  61. AI for B2B personalization
  62. ChatGPT use cases. 18 examples of how to improve your business with ChatGPT in 2024
  63. Microlearning. A quick way to get new skills
  64. The most interesting AI implementations in companies in 2024
  65. What do artificial intelligence specialists do?
  66. What challenges does the AI project bring?
  67. Top 8 AI tools for business in 2024
  68. AI in CRM. What does AI change in CRM tools?
  69. The UE AI Act. How does Europe regulate the use of artificial intelligence
  70. Sora. How will realistic videos from OpenAI change business?
  71. Top 7 AI website builders
  72. No-code tools and AI innovations
  73. How much does using AI increase the productivity of your team?
  74. How to use ChatGTP for market research?
  75. How to broaden the reach of your AI marketing campaign?
  76. "We are all developers". How can citizen developers help your company?
  77. AI in transportation and logistics
  78. What business pain points can AI fix?
  79. Artificial intelligence in the media
  80. AI in banking and finance. Stripe, Monzo, and Grab
  81. AI in the travel industry
  82. How AI is fostering the birth of new technologies
  83. The revolution of AI in social media
  84. AI in e-commerce. Overview of global leaders
  85. Top 4 AI image creation tools
  86. Top 5 AI tools for data analysis
  87. AI strategy in your company - how to build it?
  88. Best AI courses – 6 awesome recommendations
  89. Optimizing social media listening with AI tools
  90. IoT + AI, or how to reduce energy costs in a company
  91. AI in logistics. 5 best tools
  92. GPT Store – an overview of the most interesting GPTs for business
  93. LLM, GPT, RAG... What do AI acronyms mean?
  94. AI robots – the future or present of business?
  95. What is the cost of implementing AI in a company?
  96. How can AI help in a freelancer’s career?
  97. Automating work and increasing productivity. A guide to AI for freelancers
  98. AI for startups – best tools
  99. Building a website with AI
  100. OpenAI, Midjourney, Anthropic, Hugging Face. Who is who in the world of AI?
  101. Eleven Labs and what else? The most promising AI startups
  102. Synthetic data and its importance for the development of your business
  103. Top AI search engines. Where to look for AI tools?
  104. Video AI. The latest AI video generators
  105. AI for managers. How AI can make your job easier
  106. What’s new in Google Gemini? Everything you need to know
  107. AI in Poland. Companies, meetings, and conferences
  108. AI calendar. How to optimize your time in a company?
  109. AI and the future of work. How to prepare your business for change?
  110. AI voice cloning for business. How to create personalized voice messages with AI?
  111. Fact-checking and AI hallucinations
  112. AI in recruitment – developing recruitment materials step-by-step
  113. Midjourney v6. Innovations in AI image generation
  114. AI in SMEs. How can SMEs compete with giants using AI?
  115. How is AI changing influencer marketing?
  116. Is AI really a threat to developers? Devin and Microsoft AutoDev
  117. AI chatbots for e-commerce. Case studies
  118. Best AI chatbots for ecommerce. Platforms
  119. How to stay on top of what's going on in the AI world?
  120. Taming AI. How to take the first steps to apply AI in your business?
  121. Perplexity, Bing Copilot, or Comparing AI search engines