AI Chatbots: What They Actually Do vs What Marketing Claims

Disclaimer: This article provides an honest assessment of AI chatbot capabilities as of November 2025. Pricing information is approximate and based on current Australian rates but may vary due to exchange rates and vendor updates. Please check vendor websites for the most current pricing and features. This information is provided for educational purposes to help businesses make informed decisions about AI investments.

Introduction

The AI chatbot market has experienced remarkable growth since late 2022, with major technology companies investing heavily in their own solutions. Marketing materials frequently use terms such as "automation," "agents," and "autonomous AI" to describe these products. This article provides a factual examination of what each major chatbot platform can and cannot do, helping businesses understand the practical capabilities versus the marketing messaging.

The Fundamental Truth

All consumer AI chatbots are fundamentally conversation interfaces. They respond to your messages, generate text and code suggestions, provide explanations, and can use certain tools when explicitly asked. However, they all require human intervention to execute any real-world actions. Despite what some marketing materials might suggest, none of these systems run autonomously in the background, execute code in production environments, access your systems without you facilitating it, or continue working when you close the window.

This distinction is crucial to understand. When we discuss what AI chatbots can do, we're really talking about what they can help you do. They're assistants that suggest solutions, not systems that implement those solutions on your behalf. This doesn't diminish their value - understanding their actual capabilities allows you to use them effectively and set appropriate expectations.

Major AI Chatbots Compared

ChatGPT (OpenAI)

Pricing (approximate AUD): ChatGPT offers a free tier with GPT-3.5 and limited features. ChatGPT Plus costs approximately $33 per month (including GST) and includes GPT-4, web search, image generation, and file uploads. ChatGPT Team is approximately $37 per user per month, and Enterprise pricing is custom.

ChatGPT is a conversational AI that can discuss virtually any topic, write content, and provide code suggestions. It can answer questions based on its training data, which has a cutoff of October 2023 for GPT-4. The system excels at generating text including essays, emails, and creative content. For coding, it can suggest code snippets, explain programming concepts, and help with debugging - but it provides suggestions and explanations, not complete production-ready software.

With ChatGPT Plus or Team subscriptions, users gain access to web search capabilities, image analysis, and image generation via DALL-E. Custom GPTs allow for pre-configured instructions tailored to specific tasks, making the tool more immediately useful for repeated workflows.

However, ChatGPT cannot execute any code it suggests. It cannot access your files unless you explicitly upload them, and it cannot connect to your APIs or databases automatically. It doesn't run background tasks, cannot deploy anything to production, and cannot authenticate with external services on its own. The code suggestions it provides are snippets and examples that require human review, testing, integration, and significant development work to become production software. Most importantly, it stops working the moment you close the conversation window.

ChatGPT is highly effective at generating content, explaining concepts, and providing code snippets to help with debugging and development. However, it's important to understand it as a conversational assistant that helps you write code faster, not a system that creates complete, production-ready software for you.

Claude (Anthropic)

Pricing (approximate AUD): Claude offers a free tier with limited usage. Claude Pro costs approximately $30 per month (USD $20, varies with exchange rates) with higher usage limits and priority access. Claude Team is approximately $45 per user per month. API access is available separately on a pay-per-token basis.

Claude is a conversational AI focused on providing helpful, accurate responses with notably longer context windows than competitors. Its capabilities are similar to ChatGPT for conversation and content generation, but with a more recent knowledge cutoff of January 2025. Claude can search the web when needed and create "artifacts" - standalone content pieces like code or documents that persist within the conversation.

One of Claude's distinguishing features is its 200,000 token context window, which allows it to handle entire codebases in a single conversation. This makes it particularly useful for understanding complex, interconnected systems. It can analyse documents and images you provide, offering detailed interpretations and explanations.

Like ChatGPT, Claude cannot execute the code it generates. It cannot access your systems directly, run autonomous background processes, deploy code to production, or authenticate with services independently. It requires active human engagement throughout any workflow and stops functioning when you're not actively using it.

Claude is effective at understanding complex contexts and providing thorough, nuanced explanations. However, it remains fundamentally a chat interface rather than an execution environment. It helps you think through problems and understand solutions, whilst you remain responsible for all implementation.

Microsoft Copilot

Pricing (approximate AUD): Microsoft Copilot has a free tier with basic access. Copilot Pro costs approximately $33 per month and provides priority access plus integration with Microsoft 365 apps. Microsoft 365 Copilot for businesses costs approximately $44-50 per user per month (requires existing Microsoft 365 subscription). GitHub Copilot is approximately $15 per month or $150 per year for code completion in your IDE, whilst GitHub Copilot Business is approximately $29 per user per month.

Microsoft Copilot is their AI assistant integrated across their product ecosystem. It can chat about topics and generate content using OpenAI models. Within Microsoft 365, it can summarise emails, generate document drafts, and create PowerPoint presentations. In Windows, it can search your PC and adjust settings via voice commands. In the Edge browser, it summarises webpages and assists with shopping. In development environments, GitHub Copilot provides code completion suggestions as you type - small snippets and autocomplete functions, not entire applications.

Microsoft's marketing materials emphasise workflow automation and AI agents. However, in practice, Copilot functions primarily as an assistant that makes suggestions which you then implement. It cannot execute code automatically in production environments, cannot run background automation without extensive human configuration, and cannot access APIs without you writing and running the necessary code. It cannot deploy applications by itself, cannot authenticate with external services autonomously, and cannot work independently of your active involvement. The code suggestions require human review, testing, and substantial development work.

Copilot functions as an assistant layer across Microsoft products. In most cases, it suggests actions that you must then execute yourself. GitHub Copilot provides autocomplete as you write code, which can speed up typing, but you still write, architect, test, debug, and deploy everything manually. Understanding Copilot as a productivity enhancement tool that helps with suggestions and drafts rather than a system that builds complete software helps set appropriate expectations.

Google Gemini (formerly Bard)

Pricing (approximate AUD): Google Gemini has a free tier with basic access. Gemini Advanced costs approximately $33 per month and includes 2TB of Google One storage plus access to their better model. Google Workspace users can add Gemini functionality at additional cost per user for business features.

Google Gemini is their conversational AI integrated with Google services. It can answer questions, generate content, and access real-time information via Google Search. For users with Gemini for Workspace, it works directly with Gmail, Docs, and Drive to summarise emails, draft documents, and analyse spreadsheet data. It can generate images using Google's Imagen technology and analyse both images and videos you provide.

The integration with Google's ecosystem makes Gemini particularly convenient for organisations already using Google Workspace. It can pull information from across your Google environment, making it feel more contextually aware than standalone chatbots. However, this integration is still fundamentally about information retrieval and suggestion rather than autonomous action.

Gemini cannot execute code in production environments, cannot automatically access your systems or APIs beyond the Google services you've explicitly connected, cannot run autonomous background processes, and cannot deploy applications. It cannot continue working when you're not actively using it and cannot take actions without your explicit instruction and manual execution.

Gemini is best understood as a conversational layer over Google's services. It's an interface that helps you work with Google's ecosystem more efficiently, whilst remaining fundamentally a chat interface that suggests actions you must complete yourself.

Perplexity AI

Pricing (approximate AUD): Perplexity AI offers a free tier with limited searches per day. Perplexity Pro costs approximately $30 per month or $300 per year and provides unlimited searches, file uploads, and API access.

Perplexity AI positions itself differently from other chatbots by focusing specifically on research and information synthesis. It searches the web and synthesises information from multiple sources, providing citations for claims made in its responses. This makes it particularly valuable for research tasks where source verification is important. It can generate research summaries with proper references and conduct follow-up research based on conversation context.

The Pro version adds file uploads, image generation capabilities, and API access for developers who want to integrate Perplexity's research capabilities into their own applications. However, like all other consumer chatbots, Perplexity cannot execute any automation, cannot access your private systems, cannot run code or deploy applications, cannot work autonomously in the background, and cannot interact with your databases or APIs directly.

Perplexity excels at research and sourcing information quickly. It's essentially a search tool enhanced with conversational AI that helps you find and understand information more efficiently. However, it's important to understand that it's not an automation platform and cannot take actions on your behalf.

The "Agents" Confusion

Many AI companies now market "agents" or "agentic AI," suggesting systems that work independently to complete complex tasks. This terminology creates understandable confusion about what these systems actually do versus what autonomous agents would theoretically be capable of.

Current systems marketed as "agents" are chatbots with enhanced capabilities. They can break down your request into multiple steps, use multiple tools in sequence such as search engines and calculators, and remember context within a conversation. These are genuinely useful capabilities that make the chatbots more powerful and versatile.

However, these systems still require you to initiate every workflow, provide access to any systems they need to reference, execute any real-world actions they suggest, and maintain active involvement throughout the process. The chatbot doesn't continue working in the background whilst you handle other tasks. It doesn't monitor systems for changes and respond autonomously. It doesn't maintain persistent state between sessions unless you explicitly save and reload context.

True autonomous agents, as the term is understood in computer science and AI research, would be systems that work independently with minimal human oversight. They would monitor situations, make decisions based on changing conditions, take actions without explicit human instruction for each step, and persist across sessions maintaining their own state and context. These capabilities don't currently exist in consumer chatbot products.

The gap between what "agents" suggests and what current products deliver can lead to misaligned expectations. Understanding this distinction helps set realistic expectations for what these tools can do for you.

What About Automation?

Understanding the difference between real automation and what AI chatbots offer is important for making informed decisions about technology investments and setting realistic expectations.

Real automation involves systems that run without ongoing human intervention. A serverless function deployed to AWS Lambda, Vercel, or Cloudflare Workers can run on a schedule, executing code at predetermined times without anyone clicking a button. A webhook can trigger a backend API automatically when data changes in a system, causing downstream updates across your infrastructure. A cron job can run a script every night, processing data and generating reports whilst you sleep. GitHub Actions can deploy code to production automatically when you push changes to specific branches. Firebase Cloud Functions can respond to database events in real-time, updating related records and triggering notifications without human involvement.

These are examples of genuine automation. The systems run independently, responding to triggers and executing defined workflows without requiring human intervention for each step.

When AI chatbots claim to offer "automation," they mean something different. They can explain how to set up a serverless function, but you still have to write the code, configure the environment, and deploy it. They can write a cron job script for you, but you still have to set up the server, install dependencies, configure the scheduler, and ensure it runs correctly. They can generate Lambda function code, but you still have to create the Lambda function in AWS, configure permissions, set up triggers, and test the deployment. They can suggest GitHub Actions YAML configuration, but you still have to commit it to your repository, debug any issues, and verify the workflow executes correctly. They can write webhook handler code, but you still have to host it somewhere, configure the webhook source, handle authentication, and ensure reliability.

The key difference is that real automation runs without you, whilst AI chatbot assistance requires you to implement everything. The chatbot helps you figure out how to build the automation, which can be extremely valuable for saving time and learning, but it's not the same as the chatbot actually automating anything on your behalf.

The Honest Capabilities Matrix

What They're Actually Good For

Despite the limitations outlined above, AI chatbots are genuinely valuable tools when used appropriately and with realistic expectations. They excel at helping you learn new concepts by explaining them in accessible language tailored to your level of understanding. When you're debugging code and can't identify the issue, explaining your problem to a chatbot often helps you find the solution, and the chatbot can suggest code snippets or approaches you might not have considered.

These tools are excellent for drafting emails, documents, and other content. They can generate strong first drafts that you can then refine, saving significant time on initial composition. For brainstorming ideas, chatbots provide a useful sounding board that can suggest alternatives and variations you might not have thought of independently.

AI chatbots are particularly effective at explaining complex topics in accessible terms. They can generate analogies, provide examples, and adjust their explanations based on your feedback. For generating boilerplate code snippets and small functions, they can save time on repetitive typing. They excel at research and information synthesis, pulling together information from multiple sources and presenting it coherently.

When you're working on a technical problem, chatbots can suggest different approaches and explain the trade-offs between them. They're useful for exploring solution options and understanding the implications of different decisions. However, the code they provide is starting-point material that requires substantial human work - architecture design, proper error handling, security implementation, testing, integration, and deployment are all your responsibility.

These tools are not designed to replace software developers or create complete applications. They cannot build production software, which requires proper architecture, security implementation, error handling, testing, and deployment. They're not suitable for unsupervised system administration, which requires real-time monitoring, immediate response to issues, and the authority to make critical decisions. They cannot manage autonomous business processes that need to run continuously without human oversight.

Chatbots cannot perform real-time system monitoring and response, which requires persistent operation and the ability to take immediate action when issues arise. They cannot handle independent API integrations that need to run continuously, authenticate automatically, and handle errors without human intervention. Most importantly, they cannot replace the architectural thinking, security awareness, and system design expertise that professional developers bring to software projects.

The Future vs The Present

It's important to distinguish between what companies are working towards and what actually exists today. Understanding this distinction helps set realistic expectations and make informed decisions.

Companies are genuinely working towards true autonomous agents that can work independently, setting their own goals and determining how to achieve them. They're developing systems for persistent background operation that would continue working even when you're not actively interacting with them. Research focuses on direct system integration without human mediation, where AI systems could authenticate themselves and interact with other services autonomously. Self-authenticating services that can securely identify themselves and access resources without storing credentials in accessible locations are under development. The goal includes autonomous debugging and deployment where systems could identify issues in production, develop fixes, test them, and deploy without human involvement.

These are legitimate research directions with serious work happening across the industry. However, they represent future capabilities rather than present reality.

What actually exists today are sophisticated chat interfaces that can understand complex queries and generate helpful responses. Current systems have tool-use capabilities within conversations, allowing them to search the web, perform calculations, and access specific integrated services when you ask them to. They provide code suggestions and snippets that can speed up development, but building complete applications still requires professional developers. Integration with specific ecosystems like Microsoft 365 and Google Workspace makes them more immediately useful within those environments. They enable assisted workflows that still require human execution but can make that execution faster and more informed.

The gap between future aspirations and present capabilities is significant. Current systems are sophisticated assistants that help developers work faster by providing code snippets and suggestions, but they don't replace the need for professional software developers who understand architecture, security, testing, and deployment.

Specialised Tools

GitHub Copilot

GitHub Copilot, priced at approximately $15 AUD per month or $150 AUD per year for individuals and approximately $29 AUD per user per month for business, represents a somewhat different category of AI tool. Rather than being a conversational interface, it integrates directly into your development environment and provides autocomplete suggestions as you type. This context-aware autocomplete can speed up typing by suggesting the next few lines of code, completing function names, or generating small code snippets based on comments.

However, it's critical to understand that GitHub Copilot is a coding assistant that helps with autocomplete and small snippets, not a system that builds software for you. You still write, design, and architect all the code yourself, with Copilot making suggestions for the next few lines that you accept, reject, or modify. You remain responsible for all software architecture decisions, security implementation, testing everything thoroughly, debugging any issues, ensuring code quality, and deploying to production. Copilot doesn't design applications, doesn't understand your business requirements, doesn't execute code, doesn't deploy applications, and doesn't manage your development workflow. It helps you type faster, but all the actual software development work - the thinking, designing, architecting, securing, testing, and deploying - remains entirely your responsibility.

Alternative Code Completion Tools

Similar tools include Cursor at approximately $30 AUD per month, Codeium with a free tier and Pro from approximately $15 AUD per month, and Tabnine with a free tier and Pro from approximately $18 AUD per month. These are all autocomplete and code suggestion tools integrated into development environments. They assist developers by suggesting the next few lines of code or completing repetitive patterns, but they don't write complete applications or replace the need for professional developers who understand software architecture, security, testing, and deployment.

ChatGPT Plugins and Custom GPTs

ChatGPT Plus subscribers gain access to plugins and custom GPTs that allow ChatGPT to interface with specific services. These can pull data from external sources, trigger certain actions, and integrate with various platforms. However, they still require your authentication to access services, need your approval for actions they take, and are not autonomous systems. They extend what ChatGPT can do within a conversation, but they don't enable it to work independently or take actions without your involvement.

Conclusion: Understanding Capabilities and Limitations

There is often a gap between marketing messaging and actual capabilities across the AI chatbot industry. Marketing materials frequently use terms like "AI automation," "autonomous agents," "workflow automation," and "AI that works for you." These phrases can suggest systems that can take over tasks, work independently, and deliver results without ongoing human involvement.

The actual reality is that these are highly capable conversational assistants that help you understand problems and suggest solutions, whilst requiring you to execute every actual action. They're tools that augment human capability rather than replacing human involvement.

These AI chatbots are genuinely impressive and useful tools. They can save you substantial time researching solutions by quickly synthesising information from multiple sources. They help you learn new skills faster by providing immediate, contextual explanations. They generate decent first drafts of content that you can refine, eliminating the blank page problem. They explain complex problems clearly, making difficult concepts more accessible. They suggest code snippets and approaches that can help you solve problems more efficiently.

However, it's important to understand their limitations. They are not designed to replace professional software developers or create complete applications. They provide code snippets and suggestions that require substantial development work - you still need to design the architecture, implement security properly, write comprehensive tests, integrate components, and deploy to production. They cannot work autonomously without your ongoing involvement. They cannot run production systems, which require robust infrastructure, monitoring, and response capabilities. They cannot operate in the background whilst you work on other things.

If someone asks whether AI chatbots can automate their business processes or build their software, an honest answer would be that they cannot directly automate processes or create complete software systems, but they can help professional developers and IT staff work more quickly and effectively by providing suggestions, snippets, and explanations. They're assistants that can improve productivity when used appropriately by qualified professionals.

Understanding this distinction helps you use these tools effectively and set appropriate expectations about what they can deliver. Used with realistic understanding of their capabilities, they can be valuable productivity tools that help you work more efficiently.

Practical Advice

Use AI chatbots when you need to understand something quickly and want immediate access to synthesised information. They're excellent when you're working through a problem and need a fresh perspective or alternative approach. They're valuable when you want to draft content or code faster, generating initial versions that you can then refine. They excel when you need research synthesised from multiple sources into a coherent overview.

Consider their limitations when you need something to run continuously without human supervision. They're not designed for genuine automation without human intervention. Don't rely on them for production-ready code without thorough review and testing. Don't expect them to provide autonomous system management, which requires capabilities they don't currently have.

Remember that every AI chatbot is a tool that helps you work more productively. They help you work faster, understand problems better, and develop solutions more efficiently. However, they don't eliminate your involvement. They augment your capabilities whilst you maintain responsibility for implementation and execution. Understanding this distinction allows you to use them effectively whilst maintaining appropriate expectations about what they can deliver.

Last updated: November 2025. Pricing is approximate and based on current exchange rates. Please check vendor websites for the most current pricing and features.