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What are the advantages of Natural Language Processing in AI?

by | Mar 15, 2022

Natural language processing (NLP) is the ability to understand human language in context. Like machine learning, it is a subset of artificial intelligence (AI). By using NLP, you can better extract data or information from text-based documents and improve on more complex analytics tasks like sentiment analysis. Support automation platforms like Capacity can empower you with the tools needed to provide you with AI software that streamlines your business and utilizes the power of NLP.

Every internet user has experienced an NLP application. Search engines such as Google or Bing use natural language processing to propose possible search requests. Search engines are not the only NLP applications. Voice-activated devices such as Siri or Alexa use NLP techniques like natural language understanding (NLU), natural language generation (NLG), tokenization, lemmatization, and computational linguistics to help process language. Chatbots rely on NLP to deliver more accurate responses to the end user’s requests. The technology can be used to extract pertinent information from unstructured data for improved data sets.

There are many clear advantages of natural language processing in AI for organizations that utilize it.

Better data analysis.

Unstructured data such as documents, emails, and research results are difficult for computers to process. With NLP technology, large amounts of text-based information can be processed and analyzed. Repetitive tasks such as collating surveys or processing forms can be completed with more accuracy using NLP.

NLP can play a crucial role in recruitment. Instead of having employees review hundreds of resumes, companies can deploy NLP applications to screen them based on desired characteristics. By using NLP, companies have an advantage when it comes to hiring the best candidate. The process is faster and more accurate with a ranking of where to focus hiring resources. Deep learning models can be applied to NLP tasks to make recruiting processes even more effective.

Streamlined processes.

Many professional service companies such as law offices or accounting firms must review volumes of contractual information. Creating a natural language processing solution calibrated for legal and accounting professionals can reduce the time spent looking for specific clauses. Because many contracts use similar verbiage, staff can spend hours looking for the right document. With NLP systems, a chatbot can be trained to find specific clauses across multiple documents without human intervention.

Deploying a chatbot streamlines the process of contract creation and review. It also frees staff to work on other projects while documents are being searched. Professional services are not the only place that NLP can improve efficiencies. Chatbots, whether implemented on webpages, apps, or social media, can help customer-support staff answer questions quickly in plain English. Instead of manually searching a knowledge base or helpdesk, employees can use Capacity’s chatbot functionality, which uses NLP techniques to search across multiple sources, return results with faster response times, and automate conversations.

Improved customer experience.

Enterprise-wide artificial intelligence can provide valuable information to improve customer interactions and question-answering. For example, the hospitality sector depends on surveys and reviews to understand customer behavior. Part of the process is learning how customers feel about the experience, not just how they rank it. NLP can be trained to recognize sentiment in customer messages using industry-specific algorithms and identifying elements that suggest the underlying emotion in a sentence structure.

The best NLP chatbots can understand and analyze syntax and sentence structure and utilize machine learning methods, data science, syntactic analysis, computer science, word sense disambiguation, language models, text segmentation, part-of-speech tagging, named entity recognition, and other complicated elements. 

Capacity features chatbot functionality that improves customer experiences by answering questions quickly and correctly. People do not have to wait on hold or for an email response, making for a more positive customer experience.

Empowered employees.

Eliminating repetitive functions allows employees to perform higher-level tasks. Deploying NLP technology can create a more productive real world workforce.

Capacity is equipped with chatbot functionality that can help staff find information quickly. Because the technology processes real-time big data from multiple sources, it can return a more comprehensive data set. Employees can use the information to respond to customer requests or facilitate the completion of assigned tasks. They don’t have to spend time scrolling through files. Implementing these chatbots doesn’t require any complicated Java, Python, Microsoft C++, or other programming languages. Giving employees the independence to work autonomously increases employee satisfaction and engagement. Engaged employees are better ambassadors for a company and deliver improved customer experiences, resulting in strong customer loyalty.

Reduced costs.

More efficient operation means increased productivity. Whether it is responding to customer requests, ingesting customer data, or other use cases, natural language processing in AI reduces cost. Instead of needing six people to respond to customer requests, a business can reduce that number to two with an NLP solution. Enterprise AI can process data faster with more meaningful insights that result in improved customer experiences.

Realizing benefits.

To capitalize on NLP advantages, organizations must evaluate their culture. Change impacts people as well as processes, and your corporate culture must be prepared to address the anxiety that comes from change. Companies must comprehend AI requirements, machine learning algorithms, speech recognition, semantic analysis, summarization, neural networks, predictive analytics, neural networks, and other elements of natural language understanding. If NLP is to be successful, it needs volumes of data that it can process. Businesses have to consider the resources required to deliver the necessary data before starting an NLP project.

Once the foundation is in place, organizations can experience the advantages of this branch of artificial intelligence. Customer and employee experiences improve, making for an increased customer base.