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Natural Language Processing and Its Impact on Future Intelligence

Charnele Williams

Natural Language Processing and the Revolution of Conversation Intelligence

Artificial Intelligence capabilities continue to evolve at an exponential rate. It is due in part to the growth and acceptance of Natural Language Processing (NLP) features in the tools and systems we use every day. Although NLP has swiftly integrated itself into our world, not everyone understands its true power. So what exactly is it?

Natural Language Processing (NLP) is a branch of artificial intelligence that uses computational power to extract meaning from human languages. Automatic speech recognition (ASR), or speech-to-text, is a capability that enables a program to process human speech into written format. After text conversion has been utilized, NLP models can begin to decipher the meaning of the said text. Natural Language Processing involves interpreting human speech, deducing its meaning, identifying its contexts, and drawing insights from its output. There are a number of practical and/or complex ways that this technology can be used, including improving customer service and simplifying knowledge acquisition.

NLP models are unique in that they combine human-aware AI systems, deep learning machine models, and other complex rules which help computers understand, analyze, and simulate human language. With the help of these technologies, computers can single-handedly process human dialog in the form of text or voice data to decipher the intent and sentiment of a speaker or writer. 

The Current Impact of NLP 

Given its complexity, you may be tempted to assume that language processing solutions exist solely to solve rarified and deeply consequential problems. But ultimately, the AI tools that leverage NLP are both complex and user-friendly enough to address our repetitive, daily tasks and solve the more complex issues known to high-tech companies. 

For instance, intelligent voice-controlled assistants such as Siri and Alexa utilize NLP to answer simple, everyday consumer questions such as, “What time is it?” and “How is the weather?” while million-dollar companies model call center chatbots to understand the natural language communicated through customer interactions. These chatbots use language processing technology to help organizations more effectively interact with their customers and automate repetitive customer tasks. 

 By integrating NLP into our lives and organizations, we can take advantage of its many benefits, including increased efficiency, more accurate data processing, conversational insights,  predictive behavior modeling, and even improved customer service. 

NLP Beyond the Chatbot

In many cases, NLP-utilizing chatbots can actually improve human job performances and make the work of contact center agents more efficient and enjoyable but take heed, these systems are not a fix-all solution. With basic customer service interactions becoming increasingly automated, human representatives are left to handle more complex interactions. When chatbots fail to resolve these customer queries, these heightened calls are passed over to busy customer service agents. 

Here at Cogito, we employ Natural Language Processing in our models as well. Our NLP and emotion activation-powered AI models deliver real-time guidance to agents during their most difficult calls. Our solution identifies and predicts the next steps within the complex, human-led interactions rather than relying on the automatic, pre-inserted algorithmic replies and responses that most call center tools rely on. Cogito combines emotion and conversation-based signals with real-time natural language processing to nudge agents towards better customer conversations, increasing the value of their daily interactions. Cogito helps humans and computers work seamlessly alongside one another and strives to augment human intelligence with NLP solutions rather than replacing the human workforce (a common fear in this digital age).

Modeling the Future for Customer Experience

According to the research firm, MarketsandMarkets, the NLP market will continue growing at a compound annual growth rate of 20.3% (from 11.6 billion to USD 35.1 billion between now and 2026). Customer service is the top use case, with 52% of global IT professionals reporting that their company uses/is considering the use of NLP to help improve their customer experience stats. Therefore, planning how to introduce NLP into your organization is of top priority when thinking about its growing reach and evolution. Let’s take a look at some predicted advancements and technological impacts of NLP.

1. A better grip on human semantics and a greater prediction of human language:

In today’s world, we have Siri and Alexa. These digital assistants can understand words that are said but do not necessarily understand the meaning of the words spoken. 

  • Formats and sequences matter for accurate human language determinations to exist. Future models of NLP will contain algorithms with numerous variations to help better predict linguistic intent.
2. Unprompted recommendations and complex suggestions:

Currently, voice recognition technology only provides information when requested by users, but as NLP becomes more sophisticated in understanding context, it will start recommending items automatically. It is predicted to also suggest alternative structures, formats, and communication types as a recommendation to save the user time and effort.

3. Predicting and interpreting non-verbal human language:

Researchers predict that after mastering verbal human language, non-verbal processing will be next on the docket for artificial intelligence systems.

  • Cogito has successfully tapped into this non-verbal prediction space. Our technology extracts and analyzes over 200 acoustic/voice signals to deliver real-time emotion cues that agents can use to gain insights into how customers feel and improve their conversations.
4. Producing unfiltered, human-like original forms of content:

 Technology is evolving with various forms of Generative AI consistently emerging. Generative AI is a type of unsupervised learning technology that creates original content (i.e. text, image, audio, etc) out of originally sourced large language models.

  • ChatGPT, an OpenAI artificial chatbot that launched late last year is still perfecting the highly controversial functionalities of this intelligent, human-like model. In this system, models are trained to converse with humans in the same way that other humans do, with feedback received continuously reinforcing the machine’s learning capabilities.

Now What?

Technology is undergoing a revolution with advanced language processing models working in tandem with human input. The dependence on NLP-specific gadgets, applications, and solutions has significantly increased in the last decade because it helps resolve ambiguity in language between humans and machines. Its impact on our lives and businesses is expected to multiply tenfold in the next decade. For this reason, we should embrace this revolution and not misunderstand or fear its impact, but rather use its power to better automate, classify, interpret, inform, detect, and analyze our human experiences. With intelligent NLP and non-verbal NLP solutions (such as Cogito’s), contact centers and frontline teams can face the future of AI with confidence and operational strength.

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