What Are Conversational Agents? A Simple Guide

Your organization relies on integrations, automations, and apps to move tasks forward. By adding conversational agents to your team, you gain human-like additions that listen, interpret, contextualize, and answer your requests using information from company communications and resources.

In short, conversational agents are sophisticated, goal-oriented, AI-powered systems that maintain context while executing complex tasks. Think of conversational agents as highly evolved chatbots, a level up from simple chatbots that follow predefined rules and programmed responses to answer questions or perform basic tasks.

What is a conversational agent?

A conversational agent is an AI-powered dialogue system that uses natural language processing (NLP) and machine learning, along with other speech recognition and NLP tools, to understand the context and meaning of questions and queries and provide answers in a relaxed, human-like tone and cadence.

Conversational agents take the form of intelligent chatbots that exhibit goal-directed behavior and human-like conversational skills. These AI-powered assistants mirror the flow of human conversation, including pauses and even emotions. As they understand your conversations over time, they develop memory that informs their learning and communication style, boosting their effectiveness and the user experience.

Conversational agents also handle multi-turn conversations with ease. They follow changes in speakers and topics, carefully tracking attribution when called upon to provide meeting summaries or progress updates on a team project.

How conversational agents work

Conversational agents exchange answers, ideas, and other information with you by using sophisticated AI-powered technology. This advanced process allows deep understanding of topic context and insights, user emotions, and past communication behaviors, producing helpful dialogue. In contrast, basic chatbots simply select responses from a menu of pre-programmed answers.

A refined tech stack powers AI assistants with data. Although the technology varies from agent to agent, based on developer preferences and ingenuity, most conversational agents, including Slack AI features, rely on the following components.

• Automatic speech recognition. When you ask a conversational agent a question, automatic speech recognition turns your words into machine code recognized by your AI software.
• Natural language understanding (NLU). Next, the question is analyzed for meaning. Semantics and context are evaluated using NLU, NLP, and machine learning technologies. The agent learns, processes, and adapts based on past data from your team’s communications and documents.
• Dialogue management. Once the question is understood, it’s time to prepare an answer. Dialogue management, also known as the AI brain, determines how to respond to the question based on what it has learned so far. The dialogue management decides what to do next, such as scouring your knowledge base, and how to answer purposefully.
• Knowledge base. Most users allow conversational agents access to a company’s knowledge base, or central digital library of documents. Here, they source data such as meeting notes, articles, Slack channel conversations, sales scripts, training guides, employee handbooks, user manuals, and HR documents. This data further informs the answer your conversational agent will produce.
• Retrieval-augmented generation (RAG). To make sure the information gathered so far aligns with your question and provides accurate details, RAG compares potential answers against external resources to verify their relevance, validity, and timeliness. RAG also serves as a check and balance against hallucinations (inaccuracies) in the AI-driven response you receive.
• Response generation. Finally, just a few seconds after you ask a question, you get a well-worded generative AI response from your conversational agent. This multistep process produces complete sentences that directly answer your query. This feels more personable and collaborative than a basic search box result that lists links to click for more information.

Implementing conversational agents in your work operating system adds an intelligent, always-on member to your team. For example, conversational agents boost productivity by saving time in surfacing helpful information and recapping channel conversations or meetings.

Types of conversational agents

Choosing the most effective type of conversational agent for your workplace depends on your team’s needs and goals. Conversational AI tools can improve your company’s customer service response times and quality, simplify internal employee information gathering and processing, and connect internal systems so you’re never stuck working in a silo without access to data beyond your department.

Rule-based agents

These simple agents use predefined responses to answer questions. These effective, classic chatbots handle basic queries with set answers, such as price quotes, product features, or inventory statistics.

NLP-driven agents 

When information requires interpretation and nuance, NLP-driven agents get the job done thanks to their training on machine-learning models for intent recognition and basic dialogue. For example, when you ask an NLP agent to summarize what you missed while on vacation, it knows to provide meeting notes and highlights from Slack channel conversations.

LLM-powered agents

Thanks to large language model (LLM) technology, these agents offer complex reasoning and decision-making capabilities, as well as training to execute multistep plans, such as workflow automation with AI. Agents can take your post-vacation query further and suggest next steps (generative) for your projects based on what happened while you were gone (contextual), such as reviewing strategy shifts or newly assigned tasks.

Autonomous agents

This most advanced conversational agent works independently to achieve the goals you set for it. Autonomous agents can join your meetings, be called into channel conversations, and work with your connected software to offer advice, suggest next steps, or perform tasks without being asked, such as checking for fraud issues or sending a follow-up email after a customer submits a help request.

Chatbots vs. conversational agents vs. virtual assistants: a clear comparison

It’s easy to get confused when adding a new AI function to your workspace. While chatbots, conversational agents, and virtual assistants all aim to make your workday easier, each performs specific functions within set parameters.

Conversational agents offer greater intelligence and capabilities in contextual memory, task execution, and proactive behavior than chatbots, which have limited scope and performance. Chatbots don’t interpret context, but conversational agents and virtual assistants do.

Virtual assistants offer advanced functions, such as scheduling appointments based on conversational context or transferring data across platforms (for example, moving new client details from a Slack channel discussion to your CRM).

Benefits of conversational agents in the workplace

Conversational agents help you move through your workday with greater fluidity, providing easy access to information and insights along the way. Specifically, this AI technology delivers measurable improvements for your team, including:

• Faster information access. The technology driving conversational agents surfaces the data you need in seconds.
• Reduced manual work. There’s no need to open multiple documents and scan for the information you need when a conversational agent can parse the data for you.
• Better customer and employee support. When information can be accessed quickly and easily, your team and customers benefit.
• Increased workflow automation. Spending time on repetitive tasks isn’t the best use of your focus. Conversational agents add a layer of automation to your daily tasks and go a step further by suggesting next steps or offering helpful resources.
• Enhanced decision-making. You work best when you have all pertinent data in front of you. Conversational agents surface items you may not realize exist or have forgotten about the topic.
• Lower operational overhead. Conversational agents don’t require paychecks or time off. Simply set them up and let them work for you.

Conversational agent use cases and examples

Everyone in your organization — from front-line sales teams to back-office inventory managers, IT team members, and marketing professionals — can use conversational agents to enhance and expedite work tasks. Here’s how.

Knowledge retrieval

All employees benefit from access to your knowledge base through a simple search. Conversational agents will respond with detailed insights, sourcing information from documents, handbooks, discussions, guidelines, and meeting notes in seconds.

Automated task execution

Performing specific, set tasks is part of your workflow as you move through your day. A conversational agent learns these behaviors and automates your routines, such as scheduling check-in meetings with your direct reports on the first day of each month or sending a meeting summary after each weekly team stand-up.

Help desk workflows

Most help desks and customer support features use a multistep process. First, a customer submits an inquiry, then the ticket is routed to the right department for resolution. Helpful information is relayed to the customer (through live chat or email), documented, and then closed out in the system. IT, sales, or marketing might need to be informed of repair issues or next steps for a return or refund. Conversational agents, in the form of automated helpdesk bots, handle these transitions and notify the appropriate people to manage each step.

Onboarding and training

Each time you add a new staff member or a contractor to your team, they complete a standard onboarding checklist of tasks and training exercises. After they’ve received a welcome from their new colleagues, let a conversational agent guide them through the mandatory paperwork, training videos, and other online onboarding processes.

IT and HR ticketing

When something isn’t working right internally, from connectivity glitches to incorrect payroll deductions, your team members need a quick way to resolve issues. Conversational agents embedded in your work OS easily manage, sort, and route IT and HR tickets, providing faster answers to the team.

Workflow orchestration

Many processes follow a repetitive set of steps that could be automated with a conversational agent. For example, your marketing department likely brainstorms social media posts, then routes these ideas to strategists, writers, and designers. Eventually, the social content goes to the web team for scheduling and posting. An agent automates the workflow by sharing files and project updates with each person on the creative team.

Proactive monitoring and alerting

Think of conversational agents as alert, focused team members who don’t miss a thing. A conversational agent can monitor for workflow delays, missed deadlines, and connectivity issues. They can also alert you to upcoming meetings and project steps, keeping you prepared and productive.

How Slack uses conversational agents

Slack uses conversational agents to streamline work processes with fast, intelligent AI-driven task automation. Deploy agents using integrations in the Slack Marketplace, features such as Slack’s Workflow Builder, and compatible application programming interfaces (APIs) created by your organization’s software developers and engineers.

Slack offers various integrations featuring conversational agents. Or get started today with Slack’s integrated conversational agent, Slackbot.

What is Slackbot?

Slackbot is a natural language conversational agent designed to boost growth and productivity in your everyday Slack interactions. Slackbot is an enterprise AI assistant built into Slack’s agentic OS, where you already work.

Slackbot can:

• Reduce context and app switching by assisting in Slack
• Automate work routines (task management, workflow automation, daily check-ins)
• Retrieve department-specific data (HR, IT)
• Answer detailed questions with context
• Pull data from multiple sources (channel conversations, huddle notes, PDFs)
• Reduce meeting prep time by sharing calendars, notes, and agendas
• Summarize discussions so you can quickly learn about a topic
• Set reminders (task follow-ups, meetings, project deadlines)

In addition to sourcing your knowledge base, Slackbot can be customized to behave exactly as you wish in your workspace. Custom responses are triggered when specific words or phrases are posted in Slack. For example, if you work in healthcare data processing, the phrase “patient file” could trigger a workflow automation with AI to share a link to your HIPAA compliance guidelines, serving as a reminder for seasoned employees and a training tool for new staff.

Best practices for using conversational agents

Conversational agents work hard to maximize your time and focus each day so you can do deep, meaningful work. But as you weave AI tools for teams into your workflows, how you use them matters.

• Start with high-impact workflows. Maximize your conversational agents to automate workflows and tasks that consume the most time and energy, such as producing lengthy project update reports or drafting meeting agendas from conversations in a specific Slack channel.
• Use agents to reduce noise. Conversational agents can sort your emails, bundle your notifications, and send out automated responses while you’re in a meeting or in head-down, task-completion mode.
• Maintain clear governance and permissions. When you set up a conversational agent, you need to specify parameters and permissions, including where it can source data and where it can’t, such as private DMs or secure client files. Use enterprise key management for an additional layer of security with Slack Enterprise plans.
• Blend asynchronous and automated processes. When you’re deep into a creative task or strategy work, let an agent handle your basic communications, including automated email replies or status updates in channels.
• Educate teams on prompts and expectations. Team members may not understand the benefits, downfalls (such as hallucinations), or potential uses of AI technology. As with any new software, it’s a good idea to provide training and guidelines for using conversational agents.
• Establish clear data security and compliance protocols. If your organization handles sensitive data, such as medical records or banking details, configure your agent to allow only authorized management to view those documents. This data should not be included in the knowledge base and should not be accessible to everyone in the company.

Improve your workflows with conversational agents

As you search for new ways to boost team productivity, source information faster, and automate daily routines, consider adding a conversational agent to your team. This AI companion brings value to all departments, is customizable, and, over time, learns your habits and routines to become more helpful and accurate.

Explore how Slack AI agents source from your enterprise data on your connected platforms to provide always-on support for your team.

Conversational agents FAQs