Should you invest in Natural Language Processing (NLP) technology?

What is the need for Natural Language Processing (NLP) technology in software products?

I think NLP as a basic technology would be needed in all the software products especially in the end user interfaces (eg: Web Site, Mobile Apps, Amazon Echo apps etc). NLP implementation requirement would be like a standard functionality, something  very similar to a monitoring functionality or a multi-language (I18N & L10N) feature in a standard product.

Why do you say that NLP would be an integral part of every IT products? Can you explain few NLP use-cases in IT products?

For answering the need of an integrral usage of NLP, lets first look at the various use-cases of NLP that would be useful in your product and how it can add value to your product.

1. Chatbots - Every website would need to have this real-time customer interaction tool to filter lot of customer queries before routing to the sales and support team.
2. Search Engine - Customers and internal teams should be able to have human-like queries to be issued on the knowledge base.
3. Spam Filtering - Standard filtering, organizing and prioritizing an incoming job task or email. 
4. Transcription of Audio/Video -  The option of automatically scripting all the human speech (Speech to Text). In the past, this used to a major task for health care transcription for legal purposes, but today, many tools would also want to create the words automatically.
   For example, when uploading to Youtube like application, it should also have subtitle or wants to search someone's speech for certain words and point out where such a term was referenced.
5. Content or News Curation - This is a very interesitng usecase for industry specific business use case such as identifying some content and then do some processing in the domain of fake news, advertising, market Intelligence, Recruitments, Social Media monitoring etc.
6. Sentiment Analysis - Organziations can find out what is the emoition of a customer or end-user based on the usage of terms that a customer is using and can take appropriate action based on their emotion.
7.  Intelligent Conversational Systems for Voice driven applications(Voice Bots): Human to machine interface over voice. Examples are Amazon Alexa, Google OK and Apple Siri.
8. Automatic Machine Translation -  This can automatically give language translation like Google Translate and also provide computer-assisted Coding of a standard business rules or even coding from one language to another langugue. 
9. Cognitive Assistant - Personal assistant who will store all your information including your schedules, and also remind you your activities or also recommend you some improvement activities like time to stand up or to sip some water or you need to cool down and not raise your blood pressure/heart beat etc after integrating with your heart beat/BP monitoring application.

Why should you invest in NLP?  

• As a Product Owner -  If you do not invest right in the NLP technology, your products would be lagging behind your competior solution. If your novice developer has copied some public NLP code/library, the customer experience might be really pathetic and customer might think your NLP interface is too idiotic. (I personally felt this very often with many NLP applications).

• As a Developer: This is going to be a great opportunity for getting a new job which gives you a competitive advantage over the other developers who does not know NLP technology. If you know the fundamentals of this technology, you can tune your NLP application based on the business usecase and provide valuable contribution to your product and thereby giving a good customer experience and competitive advantage.