When it comes to AI tools, Claude has quickly become one of the most talked-about options. However, there are many other powerful alternatives that cater to different needs. 

Whether you’re looking for higher accuracy, faster responses, or better integration with your existing systems, there’s something for everyone. 

But what makes a good Claude alternative?

We evaluated several options based on key factors like ease of use, accuracy, responsiveness, and unique features that set them apart. 

How we assessed Claude AI alternatives

When evaluating alternatives to Claude AI, we kept several important factors in mind:

What makes a good Claude alternative?

When evaluating the best Claude AI alternatives, we focused on several key factors that define a great AI tool. 

First, ease of use: the interface must be intuitive and accessible for both new and experienced users. 

Next, accuracy and responsiveness are crucial—an AI tool should quickly generate relevant and precise responses. 

Versatility also played a role; the tool should be adaptable to various use cases, from content creation to customer support. 

Finally, cost-effectiveness was considered to ensure the value provided matches the pricing.

These factors help ensure that the alternatives listed are capable of delivering a high-quality, seamless experience.

12 Best Claude AI alternatives to try

AI tool nameBest forPricing
ChatsonicContent writers, marketers, and SEO teamsStarts at $16/month
ChatGPTHuman-like, conversational AI-generated resultsFree version, Plus at $20/month
Google GeminiProblem-solving and handling complex tasksFree, $19.99/month for premium
Perplexity AIResearchers, writers, and developersFree, Premium at $20/month
Microsoft CopilotTeams relying on Microsoft 365 suite$30/month
PoeWriters, content creators, and professionalsFree, Premium at $20/month
HuggingChatDevelopers and AI enthusiastsFree
TLDR ThisSummarizing articles and documents quicklyFree, Premium plans starting at $4/month
YouChatConversational search with real-time informationFree
GitHub CopilotDevelopers seeking AI-assisted codingFree, Paid at $4/month/user
Character.AICustomizable AI character interactionsFree, Premium at $9.99/month
GrokEdgy and witty AI interactions on X (Twitter)Premium+ X subscription at $16/month

1. Chatsonic

Chatsonic
Best for:
Content writers, marketers, and SEO teams looking for real-time, up-to-date information.

Overview:

Chatsonic, a Writesonic product, is perfect for content creators and marketers needing an AI tool beyond text generation. 

This intuitive ChatGPT alternative excels at day-to-day queries and creating blog content and articles. It also offers built-in advanced SEO features to ensure your content performs well in search rankings.

Chatsonic is built for high-volume content creators and marketers who need an edge in terms of SEO and creativity. 

Unlike other tools, Chatsonic integrates with tools like Google Search and Ahrefs to pull up the most relevant data, making its responses more contextually accurate. 

This can be a game-changer when you’re looking for fresh content ideas or need content that ranks well on search engines.

The best part is that Chatsonic doesn’t hallucinate content like most AI tools. The platform reproduces all content 100% fact-checked. 

This tool is designed to address ChatGPT’s limitations, providing real-time data, images, voice searches, and a plethora of content creation capabilities.

With real-time SEO and verified data, Chatsonic significantly reduces the time spent on content creation by eliminating manual cross-checking.

As an all-inclusive marketing solution that enables users to achieve end-to-end workflow, this tool provides the intelligence of a marketing expert–perfect for anyone in content or SEO

Key features:

Pricing:

G2 rating: 4.0/5

Reviews: Users highlight the strong editing and content generation capabilities of Chatsonic and how it provides a more humanized output than other AI tools. Some find the UI to be overwhelming. 

2. ChatGPT

Best for: Human-like, conversational AI-generated results. 

Overview:

ChatGPT, developed by OpenAI, is widely recognized for its ability to understand natural language and conversational abilities. 

It’s an excellent choice for those who need an AI tool capable of simulating human-like conversations, generating creative content, and even assisting with technical tasks like coding.

When comparing Claude AI vs ChatGPT, both AI models have their strengths, but ChatGPT stands out for its deep learning capabilities and ability to engage in multi-turn conversations.

The tool is optimized for a wide range of applications, from casual chats to more complex query handling. 

With its GPT-4o model, ChatGPT can generate highly accurate and context-aware responses, which makes it a popular choice for users who require detailed, coherent interactions.

Key features:

Pros:

Cons:

Pricing:

G2 rating: 4.7/5

Reviews: Users appreciate how ChatGPT can understand the context from previous prompts to enhance future outputs. The versatility and ease of use are also a highlight. A common downside is that the tool cannot effectively browse links, and pricing can be high. 

You might also like: 17 Best ChatGPT Alternatives

3. Google Gemini

Claude AI alternatives - Google Gemini

Best for: Problem-solving and handling complex tasks. 

Overview:

Google Gemini, formerly known as Bard, is an advanced conversational AI within the Google ecosystem.

The tool is designed for those who need an AI tool that excels in search-based tasks, complex data analysis, and content generation. 

It’s ideal for users who work in data-heavy industries or need precise, real-time information to power their projects.

In the debate of Claude AI vs Gemini, Google Gemini is a powerful alternative that focuses on integrating Google’s vast knowledge graph into its capabilities. 

Gemini’s strength lies in its ability to pull from a wide array of live data sources and generate contextually rich responses. 

It’s highly suited for users who require AI that can offer up-to-date insights and seamless integration with Google’s ecosystem of tools.

Key features:

Pros:

Cons:

Pricing:

G2 rating: 4.4/5

Reviews: Users highlight the ease of use and content generation abilities but find the tool to lack self-learning capabilities and hallucinate facts. 

4. Perplexity AI

Perplexity AI

Best for: Researchers, writers, and developers who require nuanced AI capabilities.

Overview:

Perplexity AI is an excellent choice for users needing a high-performance, accurate AI tool that understands complex language structures and produces human-like text. 

The tools excels in highly detailed, contextually aware, and complex content generation, making it perfect for those who need AI that understands intricate language structures, handles technical topics, and creates well-researched long-form content.

Unlike some AI tools that focus on generating quick answers, Perplexity AI takes a more meticulous approach, making it perfect for users who value depth and accuracy.

Compared to tools like Claude AI, it tends to perform better with intricate queries and longer-form content generation, offering more depth in its responses. 

It’s an AI tool designed for those who need to generate rich, well-researched content and technical documents.

Key features:

Pros:

Cons:

Pricing:

G2 rating: 4.6/5

Reviews: Users highlight the versatility of the tool for content creation, coding, and research. However, many point out how the tool tends to forget context after follow-up questions. 

Also read: Perplexity AI vs. ChatGPT: Which Is the Best Conversational AI Tool?

5. Microsoft Copilot

Microsoft Copilot

Best for: Teams who rely heavily on the Microsoft 365 suite

Overview:

Microsoft Copilot is designed for professionals looking to streamline their productivity and collaborate more effectively within Microsoft’s ecosystem. 

It’s ideal for teams and organizations that rely heavily on Microsoft Office tools (Word, Excel, PowerPoint) and need AI integration to enhance efficiency, automate repetitive tasks, and improve document workflows.

Microsoft Copilot is integrated directly into Microsoft 365 apps and uses AI to enhance user experience by assisting with tasks such as drafting content, summarizing documents, analyzing data, and even generating code. 

What sets Copilot apart from alternatives like Claude AI is its seamless integration with the Microsoft suite, allowing users to work directly within familiar applications while benefiting from powerful AI capabilities.

For example, Copilot in Word can help generate based on brief prompts, while in Excel, it can analyze trends and generate formulas. 

The tool leverages OpenAI’s models, giving it an edge in natural language understanding and the ability to interact with data in real-time.

Key features:

Pros:

Cons:

Pricing: 

G2 rating: 4.3/5

Reviews: User reviews highlight how the tool is great for day-to-day tasks like summarizing text and quick web searches. 

6. Poe

Poe AI Assistant

Best for: Writers, content creators, and professionals who want AI-enhanced writing.
Overview:

Poe (Product of OpenAI) is an AI chatbot platform designed for users who want access to multiple powerful AI models for various types of content generation. 

It’s geared towards users who want flexibility in their AI interactions. You can switch between different models for different purposes, such as generating creative writing, technical content, or even exploring new concepts.

Key features:

Pros:

Cons:

Pricing:

G2 rating: 4.5/5

Reviews: Poe is highly appreciated for its extensive collection of AI models that are available in one place, making it convenient for users to switch between different models for various use cases.

7. HuggingChat

HuggingChat

Best for: Developers and AI enthusiasts seeking an open-source alternative to ChatGPT for various conversational AI applications.

Overview:

Developed by Hugging Face, HuggingChat is an open-source AI chatbot designed to facilitate natural language conversations. 

This AI tool leverages models like Llama 2, CodeLlama, Falcon, and Mistral to generate human-like text, assist with coding tasks, and provide informative responses. 

Its open-source nature allows users to access and modify the source code, fostering customization and transparency.

Key features:

Pros:

Cons:

Pricing:

G2 rating: Not available. 

8. TLDR This

TLDR This

Best for: Students, educators, writers, and professionals needing quick summaries of lengthy articles or documents.

Overview:

TLDR This is an AI-powered tool that condenses extensive texts into concise summaries, enabling users to grasp key points swiftly. 

Whether you’re a student cramming for exams, a writer researching for your next piece, or a professional trying to stay updated, TLDR This ensures you get the essence of any document in just a click.

Available as a web application and browser extension, it facilitates seamless summarization of articles, blog posts, and documents.

With the ability to rewrite text in different styles and voices, TLDR This also serves as a versatile paraphrasing tool, helping you avoid plagiarism and cater content to various audiences.

Key features:

Pros:

Cons:

Pricing: Offers a freemium model and affordable pricing models for the business plan: $4/ month, $8.25/month, and $16.60/month. 

G2 rating: 4.5/5

Reviews: Users appreciate the summarization capabilities as it effectively scans text and provides only essential information. The ability to upload content as text, PDFs, or external files is also seen as a highlight.

Also read: 8 Paraphrasing Tools To Improve Content Quality

9. YouChat

YouChat by You.com

Best for: AI-powered conversational search with real-time information retrieval.

Overview:

YouChat, developed by You.com, is an AI conversational search assistant that provides detailed answers to complex questions. 

This Claude AI alternative is an AI chatbot embedded within You.com. It is designed to enhance your search experience by providing both AI-generated answers and conventional search results.

Whether you’re searching for general information, images, and videos or generating artwork and code, YouChat provides the tools and capabilities needed to meet diverse informational needs.

Key features:

Pros:

Cons:

Pricing:

G2 rating: 4.4/5

10. GitHub Copilot

Best for: Developers seeking AI-assisted coding to enhance productivity and streamline development.

Overview:

GitHub Copilot, developed by GitHub in collaboration with OpenAI, is an AI-powered code completion tool that assists developers by suggesting code snippets and entire functions in real time. 

This tool leverages the OpenAI Codex model, trained on a vast array of public code repositories, to provide context-aware code suggestions directly within the integrated development environment (IDE).

Whether you’re debugging, refactoring, or starting from scratch, Github is perfect for the coding journey. It makes development faster, more efficient, and more enjoyable.

Key features:

Pros:

Cons:

Pricing:

G2 rating: 4.4/5

Reviews: GitHub Copilot is praised for significantly boosting productivity by providing intelligent code suggestions and autocompletion within the IDE. However, it sometimes provides inaccurate or irrelevant code suggestions. 

You might also like: How to Use AIPRM for ChatGPT

11. Character.AI

Character.ai

Best for: Users interested in creating and interacting with customizable AI characters for entertainment, education, or companionship.

Overview:

Character.AI is a platform that allows users to create and engage with AI-generated characters, each possessing unique personalities and conversational styles. 

Founded in 2021, the platform enables interactions with fictional characters, historical figures, or user-designed personas, providing a diverse range of conversational experiences.

This innovative tool is designed to provide entertaining, educational, and emotionally supportive interactions. 

Whether you’re looking to role-play, story-tell, create social media content, or simply have fun, Character.AI offers the tools and flexibility needed to create compelling AI interactions.

Key features:

Pros:

Cons:

Pricing:

G2 rating: Not available. 

12. Grok

Grok by X

Best for: Tech enthusiasts, developers, and users seeking unconventional and edgy AI interactions integrated within the X platform (formerly Twitter).

Overview:

Developed by Elon Musk’s xAI, Grok is an AI chatbot designed to provide informative yet witty responses you may not find from most AI systems. 

Be it drafting emails, debugging code, or generating ideas, Grok has got you covered. It receives an input or command, applies knowledge via training data, and uses sophisticated neural networks to generate relevant output.

Grok is accessible to users with a Premium+ X subscription. It integrates seamlessly into the social media ecosystem for those willing to explore its unique capabilities.

Grok offers a unique conversational experience integrated into the X platform, blending practical information with a touch of humor.

Key features:

Pros:

Cons:

Pricing: 

G2 rating: Not available. 

Verdict: Why Chatsonic stands out as the best Claude AI alternative

Chatsonic dashboard

When evaluating Claude AI alternatives, we focused on critical factors like ease of use, accuracy, responsiveness, versatility, and cost-effectiveness. 

But we found that Chatsonic emerges as a clear leader among all the tools analyzed, offering a comprehensive, innovative, and user-friendly experience for marketing professionals and beyond.

Reasons why Chatsonic stands out over Claude AI

1. Built-in and data-backed SEO insights

Chatsonic is more than an AI chatbot. The intuitive tool acts as a virtual marketing consultant. 

It simplifies workflows by combining advanced SEO research, real-time data integration, and content creation in one platform.

For example, if you’re writing a blog, Chatsonic’s Marketing Mode can provide a comprehensive and detailed keyword analysis that will help you determine which terms to include and which pages to compete with.

Here’s how Chatsonic’s Marketing Mode looks in action:

When we asked Chatsonic to do keyword research on “best vegan chocolate cake recipe,” along with competitor page analysis, this is the output we received:

Chatsonic

If we look at this output more closely, you’ll see that Chatsonic has provided in-depth reports for topic clusters, keywords, and content insights with real-time data:

Chatsonic's Marketing Mode SEO report generation

With real-time results from Ahrefs and Google Search, you can easily get data-driven insights for SEO blogs. 

Again, Chatsonic is a clear winner among Claude AI alternatives if you want in-depth, fact-checked results for SEO tasks.  

2. Addresses common AI challenges

The growing abundance of fragmented AI tools has raised customer expectations. Chatsonic tackles this head-on by:

3. Features tailored for marketing professionals

If you’re in the field of marketing and content creation, Chatsonic is the best Claude AI alternative as it comes equipped with tools particularly for marketers, including:

Writesonic brand voice details

4. Tailored for diverse use cases

Whether you’re a solopreneur, freelancer, in-house marketing team, or digital agency, Chatsonic adapts to your needs:

5. Comprehensive marketing workflow

Chatsonic’s Marketing Mode integrates seamlessly into your workflow from SEO analysis to creation to publishing. 

Current tools include real-time SEO analysis, content creation, and publishing, with future expansions set to cover social media, email marketing, and paid ads.

Writesonic integrations

With Chatsonic, you’re not just getting an AI tool—you’re partnering with a marketing powerhouse designed to adapt to your needs, eliminate inefficiencies, and help you achieve your goals.

Whether you’re creating high-ranking SEO content, managing complex campaigns, or simply looking for a tool to reduce costs and save time, Chatsonic delivers unmatched value and intelligence.

FAQs

1. Is there anything better than Claude AI?

Yes, depending on your needs, tools like Chatsonic may be a better option. 

For marketers and content creators, Chatsonic offers a complete suite of features, including real-time data integration, SEO tools, and AI image generation, making it a more comprehensive alternative to Claude AI for many use cases.

2. What AI is better than ChatGPT?

If you’re looking for features like real-time data access and an all-in-one marketing solution, Chatsonic is an excellent choice. 

This tool addresses some of ChatGPT’s limitations by integrating with tools like Google Search and Ahrefs, providing accurate and timely insights, especially for SEO and marketing professionals.

3. What are the best alternatives to Claude AI?

Some of the best alternatives include Chatsonic, Google Gemini, and Perplexity AI. 

Among these, Chatsonic stands out for its advanced marketing features, such as keyword analysis, content creation, and future-ready email and ad optimization tools, making it ideal for businesses and marketers.

4. Is Claude free to use?

Claude AI offers a free version with limited features, making it accessible to casual users.

The premium features require a subscription, which may not offer the same comprehensive value as tools like Chatsonic, especially for advanced marketing and content creation needs.

Imagine asking an AI model for a simple fact, only to receive a plausible-sounding but entirely fabricated response. 

As surprising as this might sound for some, AI hallucination is something that is very real and often problematic. 

This isn’t just a minor hiccup. It can have serious consequences in fields like healthcare, finance, research, and even journalism. 

But why does this happen, and more importantly, how can we prevent it?

In this blog, we’ll explain what is AI hallucination, why this phenomena occurs, and explore actionable strategies for tackling it.  

What you’ll learn from this blog:

What are AI hallucinations?

An AI hallucination occurs when an AI model generates incorrect or misleading information that appears plausible. 

Think of it as an AI “making things up” without any basis in reality.

AI hallucinations are most common in natural language processing (NLP) chatbots like OpenAI’s ChatGPT or Google’s Bard. These models are trained to predict and generate text based on vast datasets. 

So when the data is incomplete, biased, or irrelevant to the prompt, the model may fabricate information to “fill the gaps.” 

This output may look convincing, but it can be dangerously inaccurate.

Recent analysis reveals that chatbots hallucinate approximately 27% of the time, and factual errors show up in 46% of their generated texts). 

This means almost half of all AI-generated content has some type of inaccuracy!

Example:

If you ask AI, “Who invented gravity?” you might get an answer like, “Isaac Newton in 1602.”

While Newton did study gravity, the year and details might be fictional. The AI isn’t lying—it simply doesn’t know the right answer and tries to generate one based on its training.

But why the name “hallucination”?

The term “hallucination” draws a parallel to human behavior. 

Just as people can perceive things that aren’t there, AI models can generate information without grounding it in reality. 

But unlike humans, AI lacks intent—it isn’t trying to deceive but simply lacks the capability to verify its own output.

Key characteristics of AI hallucinations:

AI hallucinations highlight a critical flaw in even the most advanced models: their inability to distinguish fact from fiction. 

As we delve deeper, you’ll see how this issue stems from their very design—and how to work around it effectively.

Types of AI hallucinations with examples

AI hallucinations manifest in several ways, depending on how the model processes inputs and generates outputs. 

Let’s break down the most common types, each with examples to help you understand their impact.

1. Factual inaccuracies: Generating incorrect data

Factual inaccuracies occur when AI provides information that seems believable but is fundamentally wrong. 

These errors often arise because the model generates content based on patterns in its training data rather than validated facts.

Example:
Google’s Bard chatbot once announced that the James Webb Space Telescope took the first-ever photo of an exoplanet. 

The claim sounded great, except the first exoplanet images came from 2004, long before Webb existed!

This type of hallucination is particularly problematic in critical applications like healthcare, where even a minor error can lead to serious consequences. 

Now, just imagine if AI chatbots were to provide incorrect drug dosage instructions. It could be life-threatening, to say the least!

2. Contextual misunderstandings: Misinterpreting intent or context

Sometimes, AI misunderstands the nuances of a question or the specific context, leading to responses that are irrelevant or nonsensical. 

This often happens when prompts are ambiguous or too broad.

AI can often struggle with:

Example:
For instance, when Microsoft’s Bing AI analyzed earnings statements from Gap and Lululemon, it produced a perfectly confident but completely incorrect summary of their financial figures. 

The AI understood the format but missed crucial contextual details about financial reporting.

These misunderstandings highlight the importance of clear and precise prompts when interacting with AI models.

3. Creative overreach: Unprompted elaborations by AI models

Here’s where things get interesting. 

Sometimes AI doesn’t just get facts wrong–it gets creative in ways you never asked for.

Creative overreach occurs when AI “makes up” information to complete a response, even if the input didn’t request it. 

While this can be useful in creative writing or brainstorming, it’s a red flag in factual or professional contexts.

Example:

We asked ChatGPT about a nonexistent term, “cycloidal inverted electromagnon.”

But the AI didn’t admit ignorance. 

Instead, it created an elaborate explanation that seemed so convincing that we had to double-check if “cycloidal inverted electromagnon” is actually a real phenomenon!

What makes these creative hallucinations particularly tricky is how AI can “double-down” on its mistakes. 

When questioned about potential errors, instead of admitting mistakes, AI systems sometimes generate even more elaborate but incorrect explanations.

Understanding these types of hallucinations is the first step toward mitigating their risks. 

💡 Pro tip: Want an AI article generator that actually gets its facts right? Try Writesonic’s AI Article Writer

It delivers real-time data on the latest topics, ensures every piece is fact-checked and cited, and uses in-depth web research for accuracy you can trust.

No made-up facts, just reliable, high-quality content in under 10 minutes. 

Check it out—you might just find your next favorite AI content tool. 😉

How can AI hallucinations be avoided when using language models?

AI hallucinations—when AI generates inaccurate but convincing information—can be frustrating, but they’re manageable with the right approach. 

Here are a few tried and tested approaches from the Writesonic team that can help you prevent AI hallucinations:

To go more in-depth about these techniques, here’s a more detailed overview:

1. Learn how to prompt AI and LLMs effectively

The quality of AI-generated content is heavily influenced by the clarity and specificity of user prompts. 

In short, your prompts work like a GPS for AI. The clearer your directions, the better your output will be.

While on the other hand, ambiguous or broad prompts can lead to AI generating inaccurate or fabricated information.

Strategies for effective prompting:

Example:

Instead of saying, “Describe renewable energy,” you can make your prompt for AI more detailed like this:

“Write a 200-word explanation about renewable energy adoption trends in 2023. 

The audience is small business owners exploring green initiatives. 

Use data from credible sources like the International Renewable Energy Agency (IRENA) or World Bank to highlight three specific benefits.”

This level of detail ensures the AI understands the purpose, audience, and sources to use, minimizing the risk of hallucinations and delivering more accurate results.

To make AI even more specific, direct your prompt with examples and reference documents or links.

And here’s the good news—tools like Chatsonic make this so much more easier.

With features like data ingestion and deep web research, Chatsonic delivers ensures accurate and fact-checked results. 

Need specific insights? You can upload PDFs, CRMs, or even PowerPoints and let the AI extract reliable information. 

Plus, you can customize the brand voice to match your unique tone, so everything feels like you.

And if you’re crafting articles, Writesonic also allows you to input brand voice configurations and custom guidelines, combined with factual accuracy with real-time research. 

Start creating content you can trust with Chatsonic!

2. Experiment with temperature

One of the most overlooked yet powerful tools for reducing AI hallucinations is adjusting the temperature setting. 

In AI language models, temperature controls the randomness of the outputs—essentially, how “creative” or “safe” the AI will be when generating responses.

Here’s how temperature settings work:

For example:
Let’s say you’re using an AI tool to generate a story introduction about an astronaut landing on a mysterious planet.

With a high temperature setting (e.g., 0.9), the AI might produce something highly imaginative but overly dramatic or nonsensica like:

“The planet shimmered with glowing rivers of molten gold, and the trees whispered ancient secrets in a language no human could understand. 

But suddenly, the ground dissolved beneath the astronaut’s feet, plunging them into a world of infinite mirrors.”

On the other hand, by lowering the temperature (e.g., 0.3), the AI generates a more grounded and coherent introduction:

“The astronaut stepped onto the surface of the red-tinged planet, their boots kicking up fine dust. 

In the distance, jagged mountains stretched toward the sky, and a faint hum echoed through the air, hinting at something extraordinary waiting to be discovered.”

💡Pro tip: When accuracy matters, start with a lower temperature (0.2-0.3) and gradually increase it if the outputs feel too rigid or lack depth. For creative tasks where accuracy is less critical, a higher temperature (0.7-0.8) can be more effective.

3. Leverage prompt engineering techniques

Prompt engineering is about more than just asking the AI a question. 

It’s a deliberate strategy to guide the AI’s behavior, improve accuracy, and minimize hallucinations. 

Here are some prompt engineering methods for optimizing your use of AI chatbots: 

A. Match the tool to the task

Not all AI models are designed for every purpose. 

Using a general-purpose AI for highly specific or niche tasks can lead to hallucinations because the model isn’t equipped for that level of expertise. 

For example, a tool like ChatGPT, built for conversational tasks, may struggle with legal citations or scientific accuracy.

What you can do:
Choose an AI tool designed for the specific task at hand. For instance:

💡Pro tip: When it comes to marketing-related tasks, Chatsonic is a perfect fit. 

It pulls real-time data from tools like Ahrefs, Hubspot, and Google Search Console, giving you everything you need for SEO, ads, and campaign planning—all in one place. 

Say goodbye to switching tabs and hello to streamlined, data-driven strategies.

B. Use role-based instructions

You can improve the AI’s performance by assigning it a specific role in the prompt. This technique helps narrow the AI’s focus and ensures outputs that align with your needs.

Example prompts:

Role-based instructions frame the task in a way that reduces ambiguity, steering the AI toward more precise and useful outputs.

Also read: 10 Best AI Chatbots for 2024

C. Apply chain-of-thought or least-to-most prompting

Complex tasks often trip up AI models, leading to hallucinated outputs. 

Using techniques like chain-of-thought or least-to-most prompting can help break down complex queries into manageable steps, improving accuracy and logic.

How it works:

These methods not only enhance accuracy but also allow you to verify the AI’s reasoning at each stage.

For example, if you want AI to create an article for you, instead of simply asking it to create content based on the topic and additional guidelines, ask the model to provide the blog section by section. 

D. Limit response formats

Providing specific instructions on how you want the AI to format its response can reduce errors and hallucinations. 

Structured outputs leave less room for the AI to deviate from your expectations.

Examples of structured prompts:

When the AI knows exactly what’s expected, it’s less likely to fabricate information or wander off-topic.

4. Establish human-in-the-loop systems

Human-in-the-loop (HITL) systems combine the efficiency of AI with the expertise of humans.

Think of it as a collaboration where humans step in to guide, correct, or enhance AI outputs.

They add human intuition to AI’s speed, ensuring outputs are accurate, ethical, and reliable.

A HITL system works in three simple steps:

  1. During training: Humans label and curate data to ensure the AI learns from accurate examples. This is like teaching a student the right answers before a test.
  2. Real-time corrections: When AI generates outputs, humans step in to review and fix errors. For example, in customer support, an agent can take over when a chatbot struggles with a complex query.
  3. Feedback loops: Every correction helps the AI improve. It learns from human edits and becomes better over time.

Where does a human-in-the-loop system shine?

  1. Fact-check AI-generated outputs thoroughly

When it comes to Your Money or Your Life (YMYL) topics like health, finance, or legal advice, inaccuracies can have serious consequences. 

Google’s E-E-A-T (Experience, Expertise, Authoritativeness, Trustworthiness) guidelines hold publishers accountable for delivering accurate content—even when it’s AI-generated. 

Here’s how to ensure thorough fact-checking:

  1. Verify with credible sources
    Always cross-check AI-generated information with authoritative organizations.

For health topics, use trusted sources like the World Health Organization (WHO) or CDC. For finance, consult IRS.gov, World Bank reports, or other official databases

Example: If AI generates a claim like “Investing in AI startups guarantees 40% returns,” validate this against industry data or financial reports to ensure accuracy.

  1. Collaborate with experts

Involve subject matter experts for sensitive or complex topics. Their input can refine AI outputs and avoid risky misinformation. As a bonus, it will also help your content rank better as it will align with Google’s E-E-A-T guidelines. 

Example: A licensed attorney reviewing AI-written legal content ensures compliance with local regulations, adding credibility to the final piece.

  1. Leverage verification tools

Tools like FactCheck.org, or Google Scholar are excellent for verifying claims. Remember to:

  1. Keep content updated

YMYL topics evolve rapidly, so regular audits are essential to ensure your content reflects the latest information. 

Outdated advice in healthcare or technology can mislead readers and damage trust.

Why do AI hallucinations happen?

AI hallucinations don’t appear out of thin air. 

They result from specific challenges and limitations in how AI models are designed, trained, and deployed. 

Let’s break down the major reasons why these errors in AI occur:

1. Insufficient or biased training data

AI models are only as good as the data they’re trained on. If the training data is incomplete, outdated, or biased, the AI will inevitably generate flawed or skewed responses.

Training datasets often lack diversity or accuracy, reflecting human biases or information gaps.

 For instance, research shows that facial recognition systems trained primarily on one ethnic group showed significantly reduced accuracy when identifying individuals from other ethnicities.

This means if you prompt AI to generate a list of renowned female scientists, the model might overlook key figures from Asia or Africa simply because the data on these individuals wasn’t adequately represented during training.

2. Overfitting issues

Overfitting happens when an AI model “memorizes” its training data instead of learning general patterns. 

While this might make the model perform well on specific tasks, it significantly reduces its ability to adapt to new inputs.

Overfitting makes AI overly reliant on the patterns it has seen before. As a result, AI models find patterns between input and output data without grasping the underlying logic. 

3. Algorithmic limitations

AI models like GPT or BERT are designed to predict and generate the next most likely word based on statistical probabilities. 

However, they don’t inherently “understand” context or verify the truthfulness of the outputs.

Instead, AI spots patterns between input and output data without learning the mechanisms. This basic limitation explains why AI systems often give confident but nonsensical answers.

Limitation typeImpact on output
Pattern matchingCreates false correlations
Context understandingMisses subtle nuances
Knowledge gapsGenerates fabricated details

4. Prompt ambiguity

Your choice of words matters more than you might think. When you provide vague or unclear prompts, AI systems might misinterpret your intent. 

Research indicates that prompt clarity significantly impacts response accuracy, with ambiguous prompts leading to increased hallucination rates.

For example, if you ask AI, “What are the key features of Mars?” without specifying whether you mean the planet or the chocolate bar, the model might produce a mixed response that includes scientific facts and nutritional values.

Also read: How To Write Better ChatGPT Prompts

5. Adversarial inputs

Questions phrased in certain ways can trick AI systems. 

These “adversarial inputs” force misclassifications based on the model’s training patterns. 

They work like loopholes in the AI’s logic, and bad actors can exploit these weaknesses to generate false information.

AI systems constantly balance between being too rigid (underfitting) and too specialized (overfitting). 

Models trained on limited or biased datasets often repeat errors from their training data. 

This explains why AI assistants might confidently mention fake sources or create believable but fictional content.

Why are AI hallucinations a problem?

The consequences of AI hallucinations aren’t just technical glitches. 

They lead to real-world problems that can impact your business, reputation, and bottom line.

Here’s why you need to take these AI mishaps seriously:

1. Impact on user trust

When your AI system starts spinning tales, your users’ confidence takes a hit. 

Studies show that AI hallucinations significantly diminish user trust and satisfaction levels. 

Think about it–If you can’t rely on an AI writing tool to give you accurate information, why would you keep using it?

The trust issue becomes even more critical in sectors like healthcare and finance, where accuracy is not only a nice to have but an absolute essential. 

When users discover that an AI system has been confidently presenting false information, they don’t just doubt that specific response. 

They question everything the system has ever told them.

2. Potential for misinformation

The spread of misinformation through AI systems isn’t just a minor inconvenience–it’s a serious concern that can snowball quickly. 

Here’s what makes it particularly dangerous:

Impact areaConsequence
HealthcareIncorrect diagnoses and treatment suggestions
FinanceFlawed credit assessments and stock predictions
Supply ChainInventory issues affecting revenue
ResearchWasted resources on false leads

3. Reputational damage for businesses

When AI systems hallucinate, your brand’s reputation is on the line. 

Consider this recent instance: 

When Google’s AI made a factual error in a demo, its stock price dropped 7.7%, resulting in a nearly $100 billion loss in market value. 

That’s not just a temporary setback—it’s a stark reminder of how AI hallucinations can impact your bottom line.

The damage doesn’t stop there. When AI chatbots provide incorrect information to customers, it can lead to:

This is particularly challenging because AI hallucinations can affect between 27% and 46% of generated content

That’s nearly half of all AI outputs potentially containing some form of inaccuracy. 

In regulated industries, these errors aren’t just embarrassing. They can lead to serious compliance violations and legal challenges.

You might also like: 6 Best AI Prompt Marketplaces to Know in 2024

Wrapping up

AI is a powerful tool, but it needs direction. By fact-checking outputs and refining your approach, you can make AI a reliable ally in creating content you can trust. It’s about working smarter, not just faster.

Looking for the most accurate AI tool for content creation?

Let’s face it—fact-checking AI outputs and tweaking responses can feel like a full-time job. 

But it doesn’t have to be. With tools like Writesonic and Chatsonic, creating reliable, high-quality content is simpler and smarter.

Writesonic’s AI Article Writer is like having a research assistant, and editor rolled into one. It doesn’t just churn out text—it delivers content you can trust. 

Imagine crafting a 2,000-word blog post in minutes, complete with accurate statistics and polished language. With Writesonic, it’s not just possible—it’s effortless!

For more interactive content needs, Chatsonic steps in. It’s not your average chatbot; it’s designed to dive deeper into your queries and deliver precise, actionable answers.

From long-form blogs to interactive brainstorming sessions, Writesonic ensures your outputs are accurate, relevant, and aligned with your goals. 

No guesswork. No wasted effort.

Sky-Rocket Your Organic Traffic with AI-Assisted SEO

  • Get SEO-Optimized Articles in Minutes
  • Cut down Research time in Half
  • Boost Your Topical Authority
Start Free Trial
No Credit Card Needed