Natural language processing (NLP): The bridge between human communication and intelligent automation
Typing "teh" in a text message ... automatically corrects to "the." (Autocorrect)
Putting "best pizza near me" in a search engine ... results in a list of the highest-rated pizza places in whatever city you are currently in. (Modern search engines)
Saying, "Hey Siri, set a timer for 10 minutes"... opens your iOS clock app and sets a timer for 10 minutes. (Voice assistants)
The above examples illustrate how technology, specifically Natural Language Processing (NLP), works behind the scenes to make consumers' lives easier.
NLP stands at a fascinating intersection of computers and humans, enabling the understanding and interpretation of everyday language and communication.
Before there was AI as we know it today, NLP was quietly revolutionizing how humans interact with technology.
Today's NLP uses computational linguistics + machine learning + AI to bridge the gap between the complexities (and subtleties) of human language and the 0s and 1s world of computers.
What exactly is NLP?
NLP enables computers to understand, interpret, and generate human language in a way that feels natural and meaningful.
Think of speech recognition and other "speech-to-text" technology as the "ears" that hear your words, and NLP as the "brain processing" that understands your intent.
NLP bridges the gap between how humans naturally communicate and how computers process information.ย
The "natural language" part means these AI systems can work with everyday human speech and text โ complete with slang, typos, context, and all the messy complexity of how people communicate.
But here's the challenge for IT teams: Manual ticket classification is time-consuming, error-prone, and often results in misrouted tickets. Without NLP, support agents frequently resort to generic tags, such as "other," just to keep up, resulting in delayed resolutions and frustrated users.
What does NLP look like in ITSM?
NLP has its fingerprints all over the ITSM world, specifically in automating and improving processes.
One typical example is automated ticket classification and routing. When users submit support tickets, NLP algorithms analyze the text automatically to:
Categorize incidents: "My wifi is broken" automatically classifies to "Network/Connectivity."
Determine priority levels: Depending on the keywords a user submits (e.g., "urgent" or "my system is down"), the request will be assigned a proper priority level.
Route to appropriate teams: User-submitted content is analyzed, and tickets are auto-assigned to the best support team.
And NLP can even extract key information to identify specific details like software versions, error codes, or affected systems mentioned.
A user submits: "Hey, my email's acting up again. I'm unable to send anything important to clients. This is urgent!" The system identifies keywords such as "email" (technology), "can't send" (action/problem), "clients" (business impact), and "urgent" (priority level) and detects the tone (frustration).
NLP reduces manual triage time, improves consistency in ticket handling, and directs issues to the correct resolver more efficiently.
However, for NLP to be effective in the ITSM world, it needs to be well-versed in domain-specific terminology, organizational context, and the subtle ways people describe technical problems. Ideally, it can also seamlessly handle multiple languages and communication styles.
To be clear, NLP doesn't just parse words โ it interprets and understands intent and then responds to those words in the best way for a human to understand. NLP is like a Rosetta Stone (the historical key that unlocks translation between different languages or systems) between humans and machines.
These real-world ITSM examples rely on NLP:
- Intelligent (and automatic) ticket classification and routing, per the example above
- Automated sentiment analysis for escalation
- Chatbot interactions that feel conversational
- Knowledge base search that understands questions, not just keywords
- Multi-language support for global organizations
NLP works behind the scenes to make technology feel more human.
What about advanced NLP capabilities?
Advanced NLP in ITSM primarily focuses on enhancing semantic understanding, generating more sophisticated language, and improving entity and relationship extraction from text.
While basic NLP focuses on understanding language, advanced AI-powered NLP can also learn patterns and make decisions.
For example, instead of manually programming rules like "if text contains 'slow' OR 'timeout' then category = performance," AI learns from examples โ and over time โ that these concepts are related. Even better? Eventually, the AI will recognize new variations, such as "sluggish," "unresponsive," or "taking forever," without explicit programming.
AI discovers language patterns and relationships automatically rather than requiring human experts to anticipate and code every possible way users might express themselves.
Let's look at how leading ITSM platforms are implementing these NLP capabilities.
How Xurrent is using NLP and AI (NLP+AI) to transform Service Management
Xurrent has been leveraging NLP in our platform since our early days โฆ and continues to invest heavily in NLP expertise to deliver these capabilities to our customers.
The most apparent use case of this is with Xurrent's AI Virtual Agent โ your digital specialist that ensures everything gets done and nothing gets lost in the shuffle.
It pulls key insights from your knowledge base and delivers them in concise summaries (also known as Knowledge Article Summaries), helping teams find answers quickly and keep moving forward.
For more on Xurrent's AI capabilities, read our Complete guide to Xurrent's AI-related features and functionality.
TL;DR
NLP does a fantastic job of guessing what we mean when we write prompts, especially ones with misspelled words, poor grammar, and even slang.
NLP is the bridge between man and machine.
Machines need to understand how humans communicate to interact with us properly. This understanding is essential for developing GenAI, the technology that many consider a major step toward artificial general intelligence (AGI).
Ready to see NLP in action? Xurrent's platform demonstrates how NLP and AI can transform your service management operations.