AI Agents vs. AI Digital Assistants vs. LLMs: Understanding the Differences for Business Impact

If you log onto LinkedIn on any given day, you’re likely to see a flood of buzzwords and bold claims about technology that's "going to change everything." Sometimes those predictions are right—but often, they fizzle. With AI evolving at breakneck speed, even the most tech-savvy professionals can get tripped up by a rapidly expanding vocabulary. Terms like AI Agents, Digital Assistants, and LLMs (Large Language Models, such as GPTs) are often used interchangeably, but they represent distinct tools with very different capabilities—and very real implications for how businesses operate today.

In this post, we’ll break down the differences between these concepts, define where they fit into modern revenue operations, and help you understand which to use—and when.

Table of Contents:

• What are LLMs, Digital Assistants, and AI Agents 
• Real Life Use Cases for RevOps, Marketing, & Sales
• When to Use a LLM, Digital Assistant or AI Agent
• How to Make the Most of These Tools

Defining the Tools: LLMs, Digital Assistants, and AI Agents 

Let's break down the layers of AI functionality from the core tech (LLMs) to tools that act (agents).

LLMs (Large Language Models)

What They Are:
LLMs—like GPT-4, Claude, and Gemini—are predictive text engines trained on huge datasets. They don’t do anything on their own. Instead, they generate responses based on what you type. They're like the "brain" of the operation.

How They Work:
You ask a question or give a prompt, they return a response based on language patterns—not memory, intention, or goals.

Example Use:

• Typing a question into ChatGPT and getting a paragraph answer

• Asking Claude to summarize a long report

Key Traits:

• Stateless (unless wrapped with memory)

• Zero autonomy

• General-purpose and flexible

Think of them as:
A super-smart calculator for language. You input, it outputs. No follow-up unless you prompt again.

AI Digital Assistants

What They Are:
Digital Assistants are applications built on top of models like GPT. They give those models a face, a voice, and often access to tools or workflows. They're designed to help you with tasks, but they wait for you to tell them what to do.

How They Work:
They leverage an LLM’s capabilities but add:

• Interfaces

• Prompts/presets

• Light workflow memory

• Task support (like scheduling or writing emails)

Example Use:

• ChatGPT (with memory & tools)

• HubSpot’s Breeze Copilot (formerly ChatSpot) pulling CRM data

• Google Assistant responding to voice commands

Key Traits:

• Initiated by a human

• Task-specific or domain-aware

• May handle multiple steps—but still needs direction

Think of them as:
An executive assistant with great tools—but they won’t take initiative unless you ask them to.

AI Agents

What They Are:
AI Agents are autonomous systems that can operate independently toward a goal. They might use an LLM for language understanding, but they add reasoning, planning, and action-taking. Often, they work across tools, APIs, or even with other agents.

How They Work:

• You give a goal

• The agent breaks it into tasks

• It executes (with or without human oversight)

Example Use:

• A content creation agent that:

  1. Audits existing blog content

  2. Identifies gaps

  3. Creates drafts

  4. Submits them to your CMS

• A sales agent that:

  1. Monitors pipeline status

  2. Sends reminders or follow-ups

  3. Updates CRM automatically

Key Traits:

• Autonomy: can act and iterate

• Multi-step execution

• Integrates across tools/systems

Think of them as:
A freelance specialist who gets the brief and runs with it. You check in, but they make decisions and deliver without needing constant instruction.

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Real Use Cases for Marketing, Sales, and RevOps

The AI landscape isn’t just academic—these tools are already transforming how revenue teams operate. But to put them to work effectively, it’s essential to understand their operational boundaries.

Let’s explore how each type of AI shows up in real workflows across Marketing, Sales, and RevOps:

• LLMs are ideal for generating ideas, drafting messaging, or quickly interpreting complex information—think of them as high-powered assistants for individual contributors.
  
  
• Digital Assistants are your task copilots, helping you execute workflows faster, often within the tools you’re already using.
  
  
• AI Agents, meanwhile, are the next step in evolution: systems that take tasks off your plate entirely and deliver outcomes with minimal to no human input.

Below is a breakdown of how each role can use these tools—and what level of support to expect:

When to Use Each - and Why 

Choosing between an LLM, a Digital Assistant, or an AI Agent isn’t just about tech preference—it’s about task complexity, risk tolerance, and desired autonomy.

• If you need creative support or help interpreting data, an LLM is perfect—it gives you power and flexibility without letting go of control.
  
  
• If you want to speed up execution while staying in the loop, a Digital Assistant offers guided help without taking the reins.
  
  
• If you're ready to delegate entire processes, and trust the system to make decisions along the way, AI Agents are your go-to.
  
  

Here's how to decide which to use depending on your situation:

How to Choose the Right Tool

Start with Your Problem

• Do you need to create something? → Use an LLM
• Do you need help executing a task with context? → Try a Digital Assistant
• Do you want the task off your plate entirely? → Deploy an Agent

Tool Recommendations

Understanding the difference between LLMs, Digital Assistants, and AI Agents helps you build the right AI stack for your business goals. It’s not about one replacing the others—it’s about matching autonomy, context, and control to your needs.

Whether you’re a marketer trying to scale content, a RevOps leader streamlining data workflows, or a sales pro aiming to automate follow-ups, knowing which AI tool to use—and when—will give you a strategic edge.

Discover if your organization is ready to leverage HubSpot's AI capabilities with our free AI Readiness Scorecard—get your personalized assessment today.