AI Chatbots vs AI Assistants vs AI Agents

AI chatbots, AI assistants, and AI agents: What exactly is the difference? If you’ve ever wondered where one ends and another begins (or how to explain it to C-Suite execs), here’s what you need to know about complexity, capabilities, and use cases.

 While all versions offer conversational capabilities, they differ in their level of complexity. AI chatbots are relatively simplistic and follow pre-defined scripts, while AI assistants are more complex, allowing users to engage in two-way interactions using prompts and training. AI agents are highly complex, using generational AI to make autonomous, contextual decisions with minimal human intervention.

Here, we break down the differences between AI chatbots, AI assistants and AI agents — so you can find the right tool for the right task.

What’s an AI chatbot?

AI chatbots aren’t new — they’ve been around for years, often used in customer service applications. They follow scripted conversations (which are built manually) and answer questions within a predefined scope. So, if you ask a question outside of that predefined scope, the chatbot can’t help you.

Consider when you call a customer support hotline and ‘talk’ to an AI chatbot. It may be able to resolve a simple query, but can’t ‘understand’ anything more than it’s programmed to. For more complex queries (where it doesn’t have a predefined answer), it needs to funnel your request to a human for assistance. 

What’s an AI assistant?

AI assistants take this up a notch by using machine learning (ML) and natural language processing (NLP) to better ‘understand’ user commands. Using large language models (LLMs) like Gemini, they predict text-based answers rather than relying on scripted conversations.

They can also integrate with other applications, allowing users to automate various workflows. That means an AI assistant can act like a human assistant, helping to perform tasks such as summarizing documents, scheduling meetings and generating reports.

However, AI assistants are reactive, retrieving information or performing tasks based on user commands. Since they use LLMs and NLP to communicate, typically through a chatbot interface, they require user input and training. They need prompts in order to perform specific tasks or take specific actions, but can’t independently take action without a specific prompt.

What’s an AI agent?

AI agents (sometimes called intelligent agents) take this to another level with their ability to interact with their environment. AI agents use generative AI along with LLMs and NLP to understand, respond to, and take action on customer queries. They also integrate with various applications and data sources to provide a unified experience.

AI agents don’t require constant human intervention since they can ‘understand’ the context of queries, problem-solve and make decisions autonomously, which means they can handle more complex tasks on their own. They also have persistent memory (unlike AI assistants), which means they store previous interactions, which allows them to ‘learn’ and refine their approach over time.

Whether in sales and marketing, human resources, IT, or another function, AI agents can automate tasks and streamline workflows, taking manual, time-consuming tasks off their plate so they can focus on more high-value work.

How Agentspace is using AI agents

Google Cloud Agentspace combines Google’s search expertise, Gemini’s advanced reasoning, and enterprise data to create AI-powered agents that help employees interact with business data in a natural way.

Some of the benefits of AI-powered search and Agentspace include:

• Connects data across siloed applications, regardless of where they’re stored, including internal and external tools.
• Uses intent-based search instead of keyword-based search to provide relevant and contextual search results.
• Unlocks productivity by integrating into enterprise workflows through agents that can be set up out of the box or via custom development agents.
• Provides results grounded in enterprise and web data, using conversational mode for follow-up questions so users can dig deeper into the data.

Despite their many benefits, some business leaders aren’t clear on the differences between AI chatbots, AI assistants, and AI agents — or why they may want to evolve their use of AI from chatbots to agents.

That’s where Pythian can lend a helping hand. In just four weeks, we can build a business case, pilot a priority use case, onboard users, and drive adoption with Pythian’s Agentspace QuickStart.

Beyond the Agentspace QuickStart program, Pythian can also create custom AI agents tailored to your specific business needs, as well as a unified search interface for your business. Pythian’s Google Cloud offerings all include change management consulting through our Google Workspace Center of Excellence team.

Learn more about how you can improve productivity with AI agents.