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What Is Natural Language Processing And What Is It Used For?

Artificial intelligence (AI) is changing the way we look at the world. AI "robots" are everywhere. From our phones to devices like Amazon's Alexa, we live in a world surrounded by machine learning.

Google, Netflix, data companies, video games and more all use AI to comb through large amounts of data. The end result is insights and analysis that would otherwise either be impossible or take far too long.

It's no surprise then that businesses of all sizes are taking note of large companies' success with AI and jumping on board. Not all AI is created equal in the business world, though. Some forms of artificial intelligence are more useful than others.

Today, I'm touching on something called natural language processing (NLP). It's a form of artificial intelligence that focuses on analyzing the human language to draw insights, create advertisements, help you text (yes, really) and more.

But Why Natural Language Processing?

NLP is an emerging technology that drives many forms of AI you're used to seeing. The reason I've chosen to focus on this technology instead of something like, say, AI for math-based analysis, is the increasingly large application for NLP.

Think about it this way. Every day, humans say thousands of words that other humans interpret to do countless things. At its core, it's simple communication, but we all know words run much deeper than that. There's a context that we derive from everything someone says. Whether they imply something with their body language or in how often they mention something. While NLP doesn't focus on voice inflection, it does draw on contextual patterns.

This is where it gains its value. Let's use an example to show just how powerful NLP is when used in a practical situation. When you're typing on an iPhone, like many of us do every day, you'll see word suggestions based on what you type and what you're currently typing. That's natural language processing in action.

It's such a little thing that most of us take for granted, and have been taking for granted for years, but that's why NLP becomes so important. Now let's translate that to the business world.

Some company is trying to decide how best to advertise to their users. They can use Google to find common search terms that their users type when searching for their product.

NLP then allows for a quick compilation of the data into terms obviously related to their brand and those that they might not expect. Capitalizing on the uncommon terms could give the company the ability to advertise in new ways.

So How Does NLP Work?

As mentioned above, natural language processing is a form of artificial intelligence that analyzes the human language. It takes many forms, but at its core, the technology helps machine understand, and even communicate with, human speech.

But understanding NLP isn't the easiest thing. It's a very advanced form of AI that's only recently become viable. That means that not only are we still learning about NLP but also that it's difficult to grasp.

I've decided to break down NLP in layman's term. I might not touch on every technical definition, but what follows is the easiest way to understand how natural language processing works.

The first step in NLP depends on the application of the system. Voice-based systems like Alexa or Google Assistant need to translate your words into text. That's done (usually) using the Hidden Markov Models system (HMM).

The HMM uses math models to determine what you've said and translate that into text usable by the NLP system. Put in the simplest way, the HMM listens to 10- to 20-millisecond clips of your speech and looks for phonemes (the smallest unit of speech) to compare with pre-recorded speech.

Next is the actual understanding of the language and context. Each NLP system uses slightly different techniques, but on the whole, they're fairly similar. The systems try to break each word down into its part of speech (noun, verb, etc.).

This happens through a series of coded grammar rules that rely on algorithms that incorporate statistical machine learning to help determine the context of what you said.

If we're not talking about speech-to-text NLP, the system just skips the first step and moves directly into analyzing the words using the algorithms and grammar rules.

The end result is the ability to categorize what is said in many different ways. Depending on the underlying focus of the NLP software, the results get used in different ways.

For instance, an SEO application could use the decoded text to pull keywords associated with a certain product.

Semantic Analysis

When explaining NLP, it's also important to break down semantic analysis. It's closely related to NLP and one could even argue that semantic analysis helps form the backbone of natural language processing.

Semantic analysis is how NLP AI interprets human sentences logically. When the HMM method breaks sentences down into their basic structure, semantic analysis helps the process add content.

For instance, if an NLP program looks at the word "dummy" it needs context to determine if the text refers to calling someone a "dummy" or if it's referring to something like a car crash "dummy."

If the HMM method breaks down text and NLP allows for human-to-computer communication, then semantic analysis allows everything to make sense contextually.

Without semantic analysts, we wouldn't have nearly the level of AI that we enjoy. As the process develops further, we can only expect NLP to benefit.

NLP And More

As NLP develops we can expect to see even better human to AI interaction. Devices like Google's Assistant and Amazon's Alexa, which are now making their way into our homes and even cars, are showing that AI is here to stay.

The next few years should see AI technology increase even more, with the global AI market expected to push $60 billion by 2025 (registration required). Needless to say, you should keep an eye on AI.

How NLP Testing Can Transform Automation Strategy Beyond Speed

Asad Khan is the founder & CEO of LambdaTest, an AI-powered unified enterprise test execution cloud platform.

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Test automation has always been about speed. We measured success by how many tests we ran per minute and celebrated shorter regression cycles. However, we now stand at the edge of the next evolution. With AI on the horizon and intelligent test automation through natural language processing (NLP), business stakeholders are taking notice.

The industry is recognizing this shift, as 78% of testers already use AI for productivity. Market projections confirm this: The NLP market is expected to grow from $18.9 billion in 2023 to $68.1 billion by 2028.

Understanding NLP In Test Automation

NLP in test automation is the convergence of linguistic computing and quality engineering. It helps with writing automation tests using natural language prompts.

Here, NLP acts like an intelligence layer that connects business requirements and technical implementation, enabling all stakeholders to execute test automation without being weighed down by the learning curve or technical aspects of a certain programming language or framework.

Unlike standard parsers that match keywords, AI-native testing tools help implement sophisticated computational linguistics, including:

• Intent recognition that distinguishes between verification objectives and test procedures.

• Semantic parsing that focuses on the intent behind test specifications instead of just the literal instructions.

• Domain-specific language that can understand QA terminology and patterns.

• Contextual understanding that maintains test coherence even if the interface changes.

Benefits Of NLP Test Automation

NLP test automation offers benefits that go beyond traditional testing approaches—making tests more resilient, accessible and aligned with modern development practices.

Resilience To UI Changes

Traditional tests break when developers rename a button (for example, renaming from "Submit" to "Send"). NLP-powered tests continue working because they understand purpose as opposed to just selectors, helping reduce maintenance costs for the overall team.

Democratized Test Creation

When business stakeholders can write "Verify premium customers see the discount offer" and have it automatically transform into executable tests, you can eliminate the translation bottleneck that slows development cycles.

Reduced Training Investment

New QA team members can understand and contribute to natural language test suites without having to spend months understanding complex frameworks or programming languages, helping to reduce onboarding by weeks. When requirements and tests share the same language, you can also help eliminate miscommunications.

Future-Proofed Test Assets

As your application evolves through redesigns and refactoring, NLP tests remain relevant. This is because they capture intent, not implementation. Your investment in test creation becomes a long-term asset.

Enhanced Developer Productivity

NLP testing reduces the barrier between thinking about a test and creating it. Developers can quickly write test scenarios in natural language during development rather than switching context to write complex test code.

Aids Shift-Left Testing

Building upon developer productivity, when NLP test cases can be created early during the development cycle, it helps aid your efforts towards shift-left testing.

Implementation Roadmap For Technology Leaders

For technology leaders evaluating this transition, a phased implementation yields the best results:

• Target high-maintenance tests first. Identify test cases that frequently fail due to UI changes but validate stable business logic. Prioritize converting these to NLP-driven tests to reduce maintenance effort and demonstrate early ROI.

• Facilitate cross-functional knowledge transfer. Host joint workshops with QA, developers and business teams. Use these sessions to align on testing goals, build shared understanding and develop internal advocates for the new approach.

• Convert critical existing tests. Migrate current test scripts that validate key features (e.G., premium customer functionality) to NLP-driven formats. Run them in parallel with legacy tests initially to ensure reliability and build team confidence.

• Empower business teams to author tests. Once the technical team is comfortable, introduce tools that allow business users to write and maintain tests using natural language.

• Integrate AI incrementally. Don't replace everything at once. Start by adding AI at specific points within current workflows to help teams gradually adjust while preserving familiar processes.

• Establish clear success metrics. Track key indicators such as reduced test maintenance time, improved resilience to UI changes and increased participation in test creation by non-technical staff.

NLP's Impact On Testing Roles And Responsibilities

NLP is transforming how testing responsibilities are distributed across teams, making quality assurance a more collaborative and efficient process. Here's how this looks today:

For Business Analysts

NLP enables business analysts to write test cases in plain language—such as "Verify the high value customers on the page and check if the premium offer activates for them"—directly into testing tools. This removes the need to translate requirements into code, closing communication gaps and ensuring that test cases align closely with business objectives.

For Testers

The focus shifts from maintaining fragile scripts tied to UI elements to ensuring robust, conceptual test coverage. Instead of fixing broken selectors every time the interface changes, testers can now concentrate on strategy, coverage and risk—becoming stewards of overall quality rather than code mechanics.

For Developers

NLP reduces the overhead of test maintenance during rapid development cycles. They can build features knowing that the automated tests verify intent, not just implementation details, minimizing disruptions from UI changes and allowing them to stay focused on delivering functionality.

For Managers

NLP brings transparency and clarity to the testing process. Because test cases are written in business-readable language, managers can better understand how quality efforts align with requirements, enabling more informed decision making and stronger governance over product quality.

The Future Of Intelligent Quality Assurance

We're witnessing the third wave of QA evolution: going from manual execution to script automation and now to NLP-based AI testing. When approached strategically, this evolution can help deliver three advantages for the modern DevOps pipeline:

1. Zero-Code Test Orchestration: Product owners and stakeholders author acceptance criteria that transform directly into executable test cases without technical debt accumulation.

2. Unified Quality Governance: The artificial boundary between technical and business teams dissolves as testing language becomes universal across the organization.

3. Resilient Test Intelligence: Test assets maintain validity through UI modernization cycles, preserving institutional knowledge across product iterations.

With 85% of companies already integrating AI tools in their tech stack, it's important to understand NLP for testing and determine a roadmap that works best for your organization.

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Can Neurolinguistic Programming Really Transform Your Life?

Neurolinguistic programming (NLP) is a communication and interpersonal skills training model developed in the 1970s by Richard Bandler and John Grinder. Popularized by their 1975 book, "The Structure of Magic," NLP has become fairly well known around the world.

In a nutshell, NLP suggests that changing unhelpful thoughts, feelings, behaviors, and communication patterns can:

help shift your worldview for the better

improve your relationships

make it possible to influence others

help you achieve goals

boost self-awareness

improve physical and mental well-being

A single approach that offers such a wide range of benefits might sound pretty great, and NLP has received plenty of positive attention and acclaim.

But the approach has also received plenty of scrutiny and criticism from experienced mental health professionals because almost no evidence supports any of its purported benefits.

Is NLP a type of therapy?

You might come across the term "NLP therapy," but experts don't recognize NLP as a type of psychotherapy.

Some consider it pseudoscience, at best — and at worst, a fraudulent and ineffective approach that mainly exists to make money.

A therapist trained in NLP might use the approach's techniques as part of a combined approach to therapy, though.

Interested in learning more? Below, we'll unpack NLP theory and principles, explain key techniques and how they're used, and explore what research says about its suggested benefits.

Neuro- refers to the mental, emotional, and physical aspects of your neurology.

-linguistic refers to the language and communication patterns you use with yourself and others.

Programming refers to the impact your emotions, thoughts, and life experiences have on your present life.

According to NLP theory, the approach can help you improve communication with your unconscious mind and modify your mental "programs," or the models guiding your interactions.

Clearly expressing conscious needs and desires to your unconscious mind makes it possible for your mind to "get" those things for you.

The preferred representational system (PRS)

Where do you start learning the language of your own mind?

Well, you might begin by exploring your preferred representational system (PRS), or your preferred mode of sensory input.

According to NLP's creators, everyone has a personal map, or view, of the world that guides their choices and behavior. You create this "map" with the sensory input you receive as you go about your life:

visual (things you see)

auditory (things you hear)

kinaesthetic (things you feel or sense)

olfactory (things you smell)

gustatory (things you taste)

According to NLP theory, you'll likely find yourself using one of these more often than the others. That's your PRS. You can recognize the dominant PRS in two key ways.

The first is your language. A tendency to say:

"This looks…" or "I see what…" would suggest a visual PRS.

"I feel that…" would suggest a kinaesthetic PRS.

"I hear you" or "I'm hearing that…" would suggest an auditory PRS.

Another way to identify your PRS relates to your eye movements:

Visual involves upward movements to either side.

Auditory involves horizontal movements to either side, or downward movements to the left.

Kinaesthetic involves downward movement to the right.

NLP practitioners aim to identify your PRS to better understand your personal experiences and worldview. This insight can guide them toward the techniques best suited to your needs.

Of course, learning your own language isn't the only aspect of NLP. Understanding how other people perceive the world through their own PRS can increase your awareness of their experiences and improve your communication.

NLP practitioners use a number of techniques and exercises.

The official NLP website doesn't list specific techniques or clarify how many exist. But various online sources claim there are more than 100 techniques.

There's a general lack of knowledge about these techniques, as some experts have pointed out. Not only is there no official list or definition, but there also appears to be little set guidance on how they work. What's more, many of these exercises closely resemble techniques used in other approaches, such as:

Some techniques you might come across in NLP:

Matching

NLP theory suggests that matching or mirroring another person's body language, including gestures, eye movements, posture shifts, and tone of voice, can help you:

improve rapport and communication

sidestep conflict

become better liked

influence the outcome of a situation

Maybe a discussion with your roommate has quickly started to approach "argument" status. Their tone has become heated, and they're leaning back against the wall with their arms crossed over their chest.

While you wouldn't want to use a heated tone yourself, you might try matching their posture, along with the pitch, speed, and volume of their voice. This helps strengthen your connection and show your understanding for their perspective.

Another aspect of matching involves their PRS. If they say something like, "All I hear from you is…" you could respond by saying, "I hear what you're saying."

Fast phobia cure

The phobia "cure," in brief, is a visualization exercise where you watch a mental "movie" of your phobia, replaying it:

in gray instead of full color

while imagining music that generates positive and peaceful emotions

backward at a more rapid speed

Mentally replaying the phobia "movie" a few times is said to banish your discomfort to the point where you no longer feel afraid of the object of your phobia.

Swish

This technique exists to help you replace an unwanted habit, thought, or behavior with one you actually want.

To use this technique to break a habit of sleeping past your alarm, you might:

Create a mental image of yourself lying in bed, sleeping soundly, as your alarm trills on the bedside.

Create a second mental image of yourself doing what you'd prefer to do. In other words, waking up to your alarm, turning it off, then sitting up and getting out of bed.

Mentally "enlarging" the image of yourself sleeping in and "shrinking" the image of yourself waking up to your alarm.

Mentally "throwing" the image of yourself sleeping past your alarm as far as you can. As it disappears, note how small it gets, how it fades until you can't see it any longer.

Yank the image of yourself waking up on time back rapidly. As it comes to you, imagine it growing in size and brightening in color until it feels very vivid and real.

Repeat as needed.

Luck

NLP theory suggests it's possible to improve your luck through a few steps:

Pay attention to gut feelings and follow those instincts.

Expect that positive things will happen to you.

Find and create your own opportunities by taking chances and trying new things.

Challenge yourself to learn from unwanted or negative experiences instead of letting them get you down. In this way, you transform your "unluckiness" into a better experience.

Dissolving bad memories

This exercise aims to help you get rid of unpleasant or unwanted memories. Here's how it works:

Think about the memory you want to "dissolve" — a recent breakup fight, for example.

Take a moment to fully fixate on the memory, noting everything you can see and hear in it. These sensory details might include things like colors and light, voices, other people around you, the room you're in, or your clothing.

Begin to "wash away" the sensory details. Dim the colors, mute or muffle the voices and sounds, darken the room, push everything away into the distance.

Ask yourself what you learned from the experience. You'll want to hold on to those things you learned, so if it helps, you might imagine yourself tucking that knowledge into a drawer for safekeeping.

Visualize yourself taking a deep breath, or calling up a gust of wind, to send the memory sailing away into the distance.

Of course, it's not actually possible to completely erase an unpleasant memory. Rather, you might use this technique to push away the memory whenever it pops up, until it naturally dulls with time.

Six logical levels

This exercise aims to help you create change across six different levels of thought and behavior.

An NLP practitioner might offer guidance to help you better understand your actions at these levels and work through any places where you tend to get stuck.

If you'd like to make more friends, you might explore the six levels to determine where you could make changes:

Environment. When you have free time, you like to stay home or ride your bike to the beach.

Behavior. You have a hard time talking with people you don't know, so you tend to stay quiet in social situations.

Capabilities. You always feel uncertain of what you should say to others and consider yourself bad at small talk.

Values and beliefs. You believe you should have more friends and find social interactions easier.

Identity. You think not having many friends suggests you're somehow flawed as a person.

Life purpose. Strong, close friendships make your life more meaningful.

You might already know changing your environment or behavior might help, so you might consider other levels.

Maybe you explore the (false) notion that your lack of friends means you're flawed or unlikeable, or challenge the belief that you need a lot of friends.

Once you realize the number of friends you have doesn't say anything about you as a person, you might feel less driven to make friends simply because you feel you should. As this pressure eases, you might find yourself opening up to new people more comfortably and naturally venturing toward new habits.

In short, making changes at one level often leads to additional changes at the other levels.

Proponents of NLP claim the approach can help improve:

But does it actually work?

Support for NLP's benefits remains largely anecdotal. Plus, many of these anecdotes come from NLP coaches and practitioners, who have a financial interest in promoting the approach.

After nearly 50 years of research, unbiased experts — in other words, people not making any money from the approach — have yet to find empirical support for NLP:

In a 2012 review of 10 experimental studies, researchers determined there wasn't enough evidence supporting NLP's benefits to recommend its use for any mental or physical health concern.

A 2014 review of NLP's benefits for treating PTSD, general anxiety disorder, and depression found "no clinical evidence" to support NLP as a treatment for these conditions. The review authors also note that other reviews have consistently failed to find any support for NLP as a treatment for anxiety conditions and PTSD.

Research from 2018 notes that the only publication supporting the benefits of NLP, a "review" article published in 2010, did not follow the most basic elements of review protocol. What's more, the publication included articles that hadn't been peer-reviewed — but it didn't refer to any actual scientific findings.

Research has alsodebunked NLP practitioners' claims that eye movements can reveal when someone is lying.

Some limited evidence does support a few benefits of NLP:

A 2021 study compared the effectiveness of guided imagery with an unnamed NLP behavior technique for relieving pain and discomfort after open-heart surgery. The 44 people who used the NLP technique reported less pain after surgery, while the 44 people who used guided imagery reported greater comfort.

A 2021 study involving 180 nurses suggests NLP techniques appeared to help promote organizational citizenship behavior among nurses. According to the study authors, these techniques also appear to help promote conscientiousness, job satisfaction, and quality of care.

A small 2021 study of 41 nurses and nurse managers suggests that NLP techniques may help promote flexibility, a more positive mood, motivation, and improved planning abilities. Study authors also note that NLP training appears beneficial for boosting conflict resolution and problem-solving skills.

Experts have found plenty to question about NLP's supposed effectiveness.

The truth is, anyone can create an approach and claim it treats just about anything. But those claims aren't the same as proof, of course.

To gather support for an approach's effectiveness, unbiased researchers conduct randomized controlled trials and other scientific studies. When it comes to NLP, this support simply doesn't exist.

Take the preferred representational system (PRS), for one. This system appears to form the backbone of the approach, but no research supports its existence.

Researchers have also called into question the lack of requirements necessary to become trained as an NLP practitioner or coach. You don't actually need to have a mental health background, or any credentials whatsoever, to earn an Integrative NLP Practitioner Certification — a training process that only takes 4 days.

To contrast, it takes several years to become a licensed mental health professional, not to mention hundreds of hours of practical experience.

True change typically requires time and dedicated effort

NLP supposedly works very quickly. According to some coaches, you'll notice improvement in just a session or two.

It's always wise to use caution with approaches that offer a quick fix for mental health concerns and behavioral changes. Most evidence-backed therapy approaches require several weeks of treatment, at the very least.

If NLP techniques seem like a helpful way to improve communication, self-image, and emotional well-being, it may not hurt to give them a try.

Just know this approach will likely have little benefit for any mental health concerns. If you have symptoms of any mental health condition, it may be more helpful to seek support from a licensed therapist.

A trained therapist can help you take steps to practice new communication patterns, challenge unhelpful and unwanted thoughts, and improve overall emotional health. But they'll typically use approaches backed by scientific evidence and rigorous research.

Crystal Raypole writes for Healthline and Psych Central. Her fields of interest include Japanese translation, cooking, natural sciences, sex positivity, and mental health, along with books, books, and more books. In particular, she's committed to helping decrease stigma around mental health issues. She lives in Washington with her son and a lovably recalcitrant cat.

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