The application of natural language processing (NLP) in business presents tremendous opportunities for development and automation. It applies to areas as diverse as analyzing emotional reactions in social media, where it can hint at how a brand is perceived, to voice and intuitive operation of industrial machinery. What are the prospects for NLP applications soon?

Business NLP today and tomorrow – table of contents:

  1. Introduction
  2. NLP in business – what can it do today?
  3. The future of NLP in business
  4. Summary

Introduction

We wrote about how natural language processing works, or how machines and artificial intelligence can understand language, in this article. We’ve also already mentioned how it works for automatic document processing, social media analysis, automatic translation , and chatbots, both text and voice. Today, however, we will focus on a brief overview of other business-interest applications of NLP (Natural Language Processing). On what is available today. And also on what opportunities are opening up for NLP in the near future.

NLP in business – what can it do today?

One exciting application of NLP that is really handy in running e-commerce is text analysis. For example, analyzing product reviews posted on customer feedback sites can suggest valuable suggestions for store offerings or improvements to the products themselves. Studying customer reviews enables you to make business decisions more effectively, as well as to develop strategies that respond to customer expectations.

Text analysis is also called text mining. Because through the use of artificial intelligence, it is possible to “dig out” data and behavioral patterns from text written in a casual, natural way. These can be, for example, patterns about the frequency of purchase of specific products, or the degree of satisfaction after selection, which are not seen by humans analyzing the comments. Instead, they can provide valuable knowledge about customers. This knowledge, in turn, will make it possible to apply personalization, or data-driven marketing strategies and AI to the needs of a specific customer.

Artificial intelligence, combining analysis and text mining capabilities, is also capable of preparing accurate and factual summaries. This includes the content of business meetings, after which each participant can receive a textual note containing the most important findings. The ability to summarize texts and draw conclusions from source materials also greatly speeds up market and competitive research, as one can quickly review a larger report using notes prepared by AI taking advantage of the capabilities provided by natural language processing.

However, it is worth mentioning not only comprehension but also speech generation in a business context. Various types of chatbots and voicebots are common in the hotel and tourism industry, among others. Thanks to automatic translation and the natural voice way of communication, the use of NLP ensures excellent customer satisfaction. From choosing a hotel, booking a flight, to tourist information based on location retrieved in real-time. All of these facilities are made possible just by natural language processing.

The future of NLP in business

A washing machine that reminds you with a polite voice to finish a program, or a refrigerator that reminds you to refill your supply of orange juice are solutions available today. The world around us will talk more and more: the Internet of Things (IoT) and the rapid development of artificial intelligence are making sensors and voice interactions ubiquitous.

Future analysis of natural language may include not only written and spoken utterances but also accompanying signs that express emotions. In spoken language, this will include volume and tone of voice, as well as the pace of speech. And in colloquial written language – analysis of posted emoticons, memes or images. An even greater field for analysis opens up when an utterance is analyzed from a video recording, where the person or person speaking can be seen.

If the analysis of nonverbal communication, supported by artificial intelligence, is part of NLP, there is the way to understand not only the meaning of an utterance but also its intention. Non-verbal communication opens the field for interpreting behaviors and attitudes that convey meaning, accompanying emotions, and indicate the purpose of the message. NLP combined with image analysis (computer vision) will enable interpretation of the meaning of facial expressions, movements as well as gestures. And AI-supported analytical tools will draw additional conclusions about when and where customers are interested in a product or service.

Business NLP today and tomorrow

Summary

The words of Albert Mehrabian accompany our analysis of natural language processing: Human communication is only 7% based on information conveyed through words. The tone of the voice 38% is determined by and as much as 55% is non-verbal communication. Those involved in natural language processing and its connections to other branches of artificial intelligence also know this. We will definitely marvel at what conclusions the fast-learning AI will soon draw from our behavior and gestures.

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Business NLP today and tomorrow | AI in business #12 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. Artificial intelligence in business - Introduction
  2. Threats and opportunities of AI in business (part 1)
  3. Threats and opportunities of AI in business (part 2)
  4. AI applications in business - overview
  5. What is NLP, or natural language processing in business
  6. Automatic document processing
  7. AI and social media – what do they say about us?
  8. Automatic translator. Intelligent localization of digital products
  9. AI-assisted text chatbots
  10. The operation and business applications of voicebots
  11. Virtual assistant technology, or how to talk to AI?
  12. Business NLP today and tomorrow
  13. How can artificial intelligence help with BPM?
  14. Will artificial intelligence replace business analysts?
  15. The role of AI in business decision-making
  16. What is Business Intelligence?
  17. Scheduling social media posts. How can AI help?
  18. Automated social media posts