What is AI-generated text? Examples and Detection

From relying on wordsmiths to embracing AI automation, content creation has evolved beyond conventions. With the recent wave of large language models (LLMs) and self-evolving AI reasoning, now AI writing assistants or text generators aren't just about stacking words and sentences together. They now encompass the ability to decipher human intent and deliver empathy via content.

With the progression of AI automation, more and more industries are deploying AI-generated text to analyze data, frame marketing copies, and contextualize social media marketing strategies to eliminate erstwhile challenges like low content production, inaccurate search intent alignment, or amassing content for various consumer profiles. 

But, when it comes to AI text generators, the sky is the limit. Here is a complete dissertation on how AI-generated text is currently being commercialized at large.

Given the sudden injection of AI into commercial and non-commercial domains, businesses are playing the AI card more than ever. AI copy is fueling the vision of emerging entrepreneurs as well as well-established brands. And with newly introduced generative AI tools like application programming interfaces (API), algorithms, and large datasets, computers are getting smarter. 

So far, AI tools like ChatGPT, Midjourney, or Bard have succeeded in coming the closest to understanding and simulating human intelligence. 

What is AI-generated content?

AI-generated content or synthetic media is the artificial production and manipulation of existing data into words and sentences. AI tools can quickly generate text, presentations, images, and even videos in a concise format. Marketers can take advantage of AI multimedia content for branding, emails, or newsletters.

With AI, writers can generate high-quality content much faster. Of course, it cannot replicate the capricious charm of human writing, but it can intelligently produce relevant work in seconds.

AI text generators work on a transformer-based architecture. The algorithm is trained on large input datasets created with words culled from the internet and other reliable sources. These datasets are fed to machine learning or deep learning models to extract, trigger, and decide on appropriate output.

What is an AI-generated image from the text?

AI-generated images are preprocessed images that you can download with a simple textual prompt. AI-based image generators convert the information within a text, categorize it, and search for the right visual for the output. 

They don’t just rip any image off the internet. AI generators build graphic illustrations, vectors, icons, and other parameters on the backend so you get a unique image. If the user types a text prompt and clicks "image generator," the algorithm calibrates tons of captivating images to pick one from.  

AI image generators can generate drawings, graphs, clip art, gifs, and multimedia content in seconds.

What is AI-generated art from the text?

AI-generated art is built by training machine learning or neural networks on a large dataset of existing work, producing synthetic images in response to textual queries. With AI art generators, users can replicate any art, abstract, drawing, song, or poetry.

Fast and efficient algorithms spot patterns and styles in the dataset and generate new art. With AI's sudden rise, people are using it to recreate virtual vocalists, caricatures, music concerts, and website art.

The AI-generated text has seeped into every crevice of business processes. Companies are testing AI for different verticals, from customer service to branding to investor-side content. Whether sending a newsletter, creating ad copies, or writing blogs focused on search engine optimization (SEO), AI-generated content is a welcome guest everywhere.

How do AI text generators work?

AI text generator is a large language model (LLM) that works on the simple rules of language and sentence building. It’s powered by a deep neural network and natural language processing (NLP) that work on large datasets containing published work, books, and articles. 

Based on the trained algorithm, AI text generators form a word in response to user queries. Based on the new word, they go on to produce a string of highly coherent and sensible words.

APIs, like GPT 3.5 or GPT 4o, are powered by NLP software, which teaches machines the primary language, grammar, and syntax rules. In addition to NLP, natural language understanding (NLU) software, reinforcement learning with human feedback (rlhf), and general adversarial networks create human-like content.

NLP mainly works on four broader categories of language identification.

• Tokenization means breaking sentences into small semantic tokens to make an algorithm understand them.
• Dialogue management involves inspecting dialogue-based patterns and styles in the training dataset.
• Stemming explores the origin of a particular word and includes that in the output.
• Part of speech tagging is concerned with describing words as nouns, articles, phrases, and so on. 

In NLP, machine learning algorithms consume large datasets to produce AI content. The algorithms' constant learning and feedback cycle generate the right output. Where machine learning becomes tricky is observing the newer queries and training for the exact content match. It relies on techniques like K-nearest neighbor to classify text and give a contextual output.

Applications of AI-generated text

Despite the initial aversion to AI, brands are now automating email responses, advanced data reasoning, and document collaboration with AI-generated text.

Let’s look at where all AI-generated text can fill in as a replacement:

• Diverse content ideas. Assemble quirky and creative ideas for your upcoming go-to-market launch with a little assistance from AI. While brainstorming about how to tap into your target audience, considering AI may narrow down your ideas and give you a headstart.
• AI Research. If you’re the kind of writer who loathes the thinking or research process that goes into article writing, AI can generate quick ideas, outlines, or keyword maps that will point you in the right direction.
• Website personalization. Given Google's current update about using Bard to optimize search, throwing AI into your landing page copy might be a good option. Create product-focused content with a few prompts and tailor your website to new trends.
  
• Language translation. Although tools like ChatGPT or Writesonic have leaned toward English-speaking audiences, the future of these tools has to be multilingual. In no time, we’ll be able to use AI to prompt queries and get answers in regional dialects.
• AI text-to-image. AI tools also accept prompts to generate creative images. It processes text, searches its dataset, scrapes an image of the internet, and recreates it using an in-built photo editor. The resultant image is something you’ve never seen.
  
• Audio or video descriptions. AI text generators, like ChatGPT Plus or ChatGPT 4.0, offer a voice recognition feature that interprets dictated prompts and turns them into a text response in seconds to support visually impaired audiences or other voice navigation-based tasks. 
• Presentations or decks. Use AI to create numerous slides of thought-provoking content on any topic. NLP-based technology used within image-based AI tools can also build data-driven graphs and charts.
  
• Captioning. Selecting the right social media caption takes hours of pondering. Reaching out to the correct audience with hashtags, links, and calls to action is hard, but AI can curate social media captions, improve your CTAs, and make you sound like a pro.
  
• Template creation. AI is handy for handling constant business emails. It creates email templates, personalizes banner images, and generates quirky and creative subject lines. 

Different companies use open-source APIs like GPT-2 or GPT-3 to develop their versions of AI text generators. Adding a simple user interface over an open-source API can help you automate document creation and sell the new software.

Methods of detecting AI-generated text

Because it’s in the research stage, open-source large language models are free for everyone to use. This is great, but the accessible nature of such tools and APIs makes them prone to malicious activities.

AI-generated text can give way to anti-nationalist manifestos, terrorist activities, or disturbing movie scripts. Researchers have ideated a few methods to create a line of demarcation between AI-generated text and human text.

Watermark method

Tom Goldstein, a computer science professor at the University of Maryland, first proposed the Watermark method. Embedding digital watermark signals in large language models helps detect AI text.

The watermark won’t harm the algorithm or the API, nor will it be visible to the human eye. The embedded signals can also be classified as green tokens, which means you can break them down to detect the text's origin.

As AI tools generate new words based on past patterns and inputs, every time the model uses an AI-generated word, a watermark gets activated and executed. If the word is taken “as is,” the token is not executed. These tokens or watermarks can be analyzed to decipher who banged out the masterpiece: AI or a human.

However, if not scrutinized properly, users might leverage the non-watermarked versions for malicious purposes.

Data poisoning or radioactive data

To spot artificial text, you don’t have to go to the app developer. Instead, sprinkle a few drops of outliers or poison into your online data. A large language model will scrape this raw data as a part of the refined dataset. These refined datasets can then be used to train algorithms safely.

Once the algorithm has learned the input dataset, look for traces of poison. If the machine learning model trained on this dataset produces an output, the traces of artificial text will be visible.

It’s all a matter of the randomness and homogeneity of the text put forth at the reader’s disposal. The more random the text is, the higher the probability that AI generates it.

AI can't emulate humans' natural writing process. Each dendrite of the human nervous system works in unison to put together a perfectly chiseled writing piece. Unfortunately, AI still has a long way to go.

What are AI-detection tools?

AI-detection tools split the difference between human and artificial content. Although these classifiers aren’t 100%, they might prove beneficial in some cases.

• Undetectable AI checkers look for the possibility of AI-generated content by superimposing batch-fed documents over input content. The tool returns the likelihood of AI-written content based on eight detection variations.
• Originality.ai is mainly used for spotting artificial content from professional documents. It works on GPT-4 API and generates a “low” or “high” likelihood of AI writing. It spots semantic differences in writing and marks the areas that look bot-written.

• Content at Scale is an AI-based plagiarism and content detection tool. It also breaks down your content line by line to show you what parts have been flagged as AI.

• Copyleaks AI is a recently launched, accurate AI detection tool. After pasting your text in the box, hover over sections you feel suspicious about, and it generates a detection score.
• Giant Language Tester Model  (GLTR) was founded in 2019 by researchers at MIT and IBM’s Watson Labs.  Based on the GPT-2 mechanism, it detects the “randomness” and “variance” of the next word in a sentence to affirm whether a human being wrote it.  

What is Open AI’s new AI detection classifier?

Open AI’s trained classifier analyzes whether a piece of content is “likely written by AI” or a human being. Although the classifier doesn’t guarantee 100% accuracy, spotting the presence of AI text would prevent the misuse of AI in critical matters – automated email campaigns, academic dishonesty, and educational web content, for example.

The classifier works on a simple principle. It’s a large language model trained on pairs of human- and AI-generated text. The data is sourced from various channels like pre-training data, human demonstrations, and prompts from forums. The data is then divided into “prompt” and “response.” For the prompts, responses were generated through different language models. For their web version, the “false positive rate” is low, meaning the classifier would only categorize text as “likely AI-written” if it strongly feels so.

Benefits of AI-generated text

We have been aware of the benefits of written content for both personal and professional scenarios. In a personal setting, it helps you manage budgets and create household to-do lists. In a professional environment, content use cases are endless.

With the advent of AI-generated text, most of the tedium of content writers and editors has been eliminated. Rather than spending countless hours writing, proofreading, and getting feedback or approval, they can draft fine-tuned content in a fraction of the time.  

This is how AI-generated content simplifies the lives of daily content hustlers.

• Proofreading: AI-generated text is grammatically correct and free of spelling errors. The tools have a built-in editing feature that checks flow, style tone, and the nature of content before presenting the output.
• Overcoming writer’s block. AI-generated text can help overcome writer’s block and give you a headstart for the next project. Beginning with a quick AI intro can make the rest of the writing process better. 
• Varied voice.  AI tools offer scientific, informative, didactic, persuasive, informal, casual, or negative tone content. Set your tone of voice beforehand to generate perfect content pieces.
• Readability and flow. AI content is super-readable and doesn’t seem generic. The algorithm also explains a topic well and ensures smooth transitions between sections.
• Faster content creation. For every new content project, you can employ AI-generated text. Write emails, business letters, AI-generated blog posts, or AI-generated articles.  A mountain of documents can be built from the ground up with articulate content, facts, and discoveries.
• SEO compatibility. As these tools crawl every nook and cranny of the internet, they can help you optimize your article as per relevant search queries. From generating keyword maps to optimizing content, AI text generators can be your friendly SEO companion.
• Expert content. People like to hear from the horse’s mouth. AI facilitates best-in-class language, keywords, and style to create flawless content.
  
• Better efficiency and productivity. The AI-generated text helps mitigate the stress that comes with overflowing content queues. It’s an easy ticket to maintaining your work rhythm.

Limitations of AI-generated text 

AI can shoulder most writing responsibilities, and it’s also changing how brands view content. Previously, brands preferred writers' “creative ideas.” But now, as AI tools process information on a large scale, brands are becoming more “basic.”

Although this might not be a dealbreaker, this and a few other aspects warrant caveats for the upcoming generation of content marketers and writers.

• Homogeneity. AI text generators might produce one output twice for two reader personas or topics. Even if you prompt the engine by giving more details about the second topic, there won’t be much to work with.
• Code building and quality. Don’t use AI text generators to code complex, feature-based plugins. Although AI generators can code and debug, they won’t be able to understand feature implementation.
• Plagiarism. Some AI tools have resulted in an increase in plagiarism percentage of  10-15%. Plagiarized content could tarnish your brand reputation and cause you to lose online visitors.
• Lack of data-driven thinking. AI focuses on being clear and to the point. No amount of data can infuse “emotional” or “self-aware” capabilities in AI tools to create inferences and implicit transitions in content.

Best AI writing assistants for 2025

AI writing assistants use self-evolving technologies like NLP to simplify the writing process. Users can query the assistant about keyword search, grammar, tone checking, article outline, and article samples to align it with the relevant topics. Natural language processing does all the legwork for writers so that they can finish more writing tasks in the nick of time. 

To be included in the AI writing assistant category, the software must:

• Use machine learning algorithms to capture, classify, and repurpose data 
• Produce artificial intelligence-generated content at some part of the writing process
• Provide “improvement ideas” to writers to better the current written work
• Offer additional, appropriate sources to build the writer’s knowledge
• Continue giving more and more options in case the writer isn’t satisfied with the output
• Check for spelling, voice narration, grammar, and homonyms in the final result
  

*The following data was collected from the G2 Winter 2025 Grid Report on February 2025. Some reviews might be edited for clarity. 

1. Grammarly 

Grammarly provides comprehensive AI-based comprehension assistance, vocabulary analysis, proofreading and spell-checking, and plagiarism detection services for businesses and educational institutions to improve the writing and editing workflows and maintain robust digital security and encryption. The AI-based Grammarly extension easily integrates with over 50,000 web applications and several operating systems, thus making it simple to point out and eliminate grammar and spelling inconsistencies, check tone and style, and rewrite sections of content to enhance quality. 

What users like best:

"Grammarly really works. It runs in the background, and as I am writing, it gives suggestions on how to make things better, clearer, and more concise. It is so easy to use. I am an attorney, and I write for a living, and Grammarly is really helpful, to give a new spin or alternatives to the way I phrase things. I was doubtful at the beginning, but I would highly recommend it."

- Grammarly Review, Harry F. 

What users dislike:

"My only issue has been with their customer service, not because they haven't been responsive. Sometimes, I can't tell if a chatbot or a human is responding because my questions and issues aren't always understood and responded to as I ask them to (e.g., their pricing and trying to settle my account)."

- Grammarly Review, David D. 

2. Notion

Notion is an AI-powered task management platform that automates note-taking, project workflows, and doc creation and editing, all in a unified platform. With Notion.AI, you can set pre-determined checks and alerts, monitor and optimize reviews, and speed up writing and content creation workflows with a reduced error margin to intelligently scale content production and make your projects more inclusive and diverse.

What users like best:

"I've found Notion AI to be truly remarkable in my daily use. Its ability to assist me with writing and content creation is impressive. It's like having a ready assistant who understands exactly what I want to do. What I appreciate most is how intuitive it is to generate text, create document structures, and offer relevant suggestions while I work. The support it provides during use is constant and valuable, making the writing process much more fluid and efficient." 

- Notion Review, Luca R. 

What users dislike:

"My learning curve was steep. I would really love a weekly email giving me a new way to incorporate features or explain features I don't understand especially the AI. I currently use a separate AI (actually 2!) and would love not to need those apps."

- Notion Review, Jessica S. 

3. Simplified 

Simplified offers a complete AI-based marketing suite that lets you auto-create social media captions, ad copies, newsletters, landing pages, and other marketing collaterals with the integration of natural language processing (NLP) and generative AI models. It is an all-in-one task management and AI writing platform that scales your sales and marketing workflows and optimizes your content production to help you reach your goals.

What users like best:

"What I like best about Simplified is how it makes creative processes more accessible. Whether it's graphic design, video editing, or social media management, it streamlines everything, allowing users to focus on their ideas rather than getting bogged down by complicated tools. The user-friendly interface and collaborative features really enhance teamwork, making it easier for everyone to contribute. It’s all about empowering creativity without the hassle!"

- Simplified Review, Ashish C.

What users dislike

"The negative aspects are first the language selection, as the video was edited in English at first, then we manually changed it to another language, and secondly, not making a long video except after subscribing, and thirdly, there were linguistic errors while editing the video."

- Simplified Review, Rehab Z.

4. Apollo.io 

Apollo.io offers various business intelligence and campaign tracking features to automate your go-to-market (GTM) strategies, draft product launch workflows, curate ai-generated enablement resources or content assets to initiate a successful campaign, nurture inquiries into MQLs, and drive conversion. It helps you run a high-stake and high-quality marketing pipeline and offers several intrinsic sales and marketing features so that you can operationalize marketing with AI.

What users like best:

"I love Apollo's suite of features and integrations. I love workflows, sequences, custom fields, etc. I like the Chrome extension, especially for task automation. I am extremely grateful that they offer a startup plan. I love their AI FAQs and support team - 90% of my questions can be answered with FAQs that are actually good because AI searches through them for you. For the other 10%, the support team has always gotten back to me very fast and resolved my blockers."

- Apollo.io Review, Perry P.

What users dislike:

"The only issue I have run into so far is with getting my email connected and them not going into spam. I wish there were someone to actually walk you through the onboarding/set-up phase as opposed to relying completely on the pre-recorded videos"

- Apollo.io Review, Erica F.

5. Writesonic

Writesonic is a text-to-image generator and AI detection platform that automates content creation through AI functionality and detects the presence of AI-generated text. Its quick and efficient engine helps curate long-form and short-form content, images, and multimedia. Writesonic is one of the oldest and strongest AI text generators, trained on user reviews, feedback, and prompts.

What users like best:

"Being able to produce quality, SEO-saturated blog articles my audience will actually find by simply copying and pasting my chaotic brain dumps into WriteSonic has been the biggest game changer, giving me so much more time to create quality content and products for all the new traffic and growing audience of mine!"

- Writesonic Review, Mandi

What users dislike:

"Not specific to Writesonic, this is an issue for all AI content writers, in that the content needs fact checking, proofreading, and editing to ensure that it meets the required standard before putting life onsite."

- Writesonic Review, Tom A.

Authoring your way into success 

For writers, AI-generated text is a hard pill to swallow. Gripped with the fear of AI replacing them, some are simply trying to ignore it.  However, reality changes with time, and writers who embrace the new technology revolution will remain and thrive. 

In this current age of innovation, pressing on the thought of automating your content creation tasks with an AI text generator is the only way forward, as it will maintain your relevance in the market and help you be on the cusp of new and innovative growth opportunities.

Learn how DeepSeek is making ripples in the sales and marketing sector and getting ahead of the mainstream AI-text generation in 2025.

This article was originally published in 2023. The content has been updated with new information.