In general, customer service teams won’t struggle with difficult queries, but they will struggle with high volumes of simple ones, such as order tracking, password resets, appointment changes and billing questions.

AI agents can be used to ease this problem. Unlike old chatbots with strict decision trees, modern AI agents can understand what the customer is asking for, access live data from your CRM or ordering system and perform an action. From there, if they’re unable to resolve the query, they’ll pass it on to a human.

The difficulty is deciding which agent to go for. Different agents are built for answering calls, chats and emails, and some focus on the work that happens after the customer has interacted. This guide outlines 10 different options, what each one is good for and where it might not be the right fit.

What an AI agent for customer service actually does

The AI agent sits between the customer and your support systems. It reads or hears the request, understands the intent, looks up the correct data and either resolves the query or passes it on with full context.

Compared to basic bots, AI agents offer far more functionality. While a chatbot might tell your customer where to find the returns policy, an AI agent will confirm their identity, check if the order is eligible to be returned, create the return label and update the CRM, all within the same conversation.

Most customer service teams use AI agents to provide support at three levels:

The tools below cover all three levels. It’s useful to know which area of your workflow is causing you the most friction before deciding which tool to go for.

How we evaluated these AI agents

We’ve evaluated each tool from the perspective of a support or operations leader who will be living with the decision for years, not just running a demo. We focused on:

All pricing and performance figures below are taken from each vendor’s public materials at the time of writing, so it’s worth double-checking current pricing before you buy.

Quick comparison

The 10 best AI agents to automate customer service workflows

1. Natterbox — best for Salesforce-first contact centers

Natterbox is an AI contact center platform built for companies that use Salesforce to run their customer operations. Its AI agents sit inside the telephony flow itself rather than on top of a separate phone system, so every call can be answered instantly, with live data pulled from Salesforce while the conversation is happening.

That native design matters most for voice, which is still the channel where customers bring their most urgent and sensitive issues. With Natterbox agentic AI for customer service, an AI agent can handle FAQs, identity checks and repeat tasks such as appointment scheduling, then pass anything it cannot resolve to a human agent who receives the call and the full context at the same moment.

Natterbox also takes a lot of the setup out of your hands. The team analyzes your call data to find out which queries are driving the most volume, then builds and tests the flows inside your own CRM objects and logic, so teams can be up and running in weeks. One case study shows that tool wholesaler Sutton Tools automated 77% of its calls within a month, with each query resolved by the AI in about 90 seconds on average.

As all voice data, transcripts and call outcomes are logged directly in Salesforce, managers have one reliable source of truth for every interaction. The platform also puts a strong focus on compliance, data protection and security, including PCI-compliant payment handling for teams that take card payments over the phone.

What we like

Where it falls short

2. Workast — best for turning support requests into owned tasks

A lot of customer service work happens after the call ends. Refunds need approving, bugs need raising with engineering and account changes need double-checking, and this is often where requests go quiet.

Workast is an AI-driven task management platform that handles exactly that follow-through. Its AI Workflows pick up requests from a variety of sources, including Slack, email, forms and calendars, sort each one by priority, type or project, and pass it to the right teammate. The AI can also split a request into subtasks, set deadlines and ask for missing details, such as an order number or a screenshot, before anyone has to chase them.

For teams that run their support in Slack, this is a great way to make sure every escalation has an owner and a deadline. A task can be created from a Slack message, moved to the correct list, tagged and assigned in seconds, with reminders triggered automatically until it’s closed. Workflows are built with a no-code builder using simple, plain-language rules, so operations leads can set them up without waiting on engineering.

What we like

Where it falls short

3. Intercom Fin — best for chat-led support teams

Fin is the AI agent built into Intercom’s help desk. It answers front-line questions across chat, email, phone and messaging apps, and because Fin and the human team share the same inbox, customer records and knowledge base, every conversation the team has can be used to improve Fin’s responses.

Intercom reports an average resolution rate of 76% across more than 12,000 customers. Fin can be trained on help articles, internal content and policies, and you can simulate complex, multi-step conversations before going live.

Pricing combines a per-seat help desk plan, starting at $29 per seat per month, with a fee of $0.99 for each outcome Fin resolves. This is easy to understand, although teams with high volumes should calculate their monthly costs carefully.

What we like

Where it falls short

4. Ada — best for regulated, high-volume enterprises

Ada is an enterprise platform for building and managing AI customer service agents across voice, chat, email, SMS, social and in-app channels. Its Reasoning Engine works as one intelligence layer, so the agent can follow a single set of instructions and policies on every channel instead of running separate bots for each one.

The platform is aimed at industries where accuracy and compliance are critical, including financial services, travel, insurance and gaming. Ada lists SOC 2, HIPAA, GDPR and PCI DSS compliance, and its Playbooks feature lets the AI follow multi-step processes, such as rebooking a flight or handling a return, using live data.

Ada reports an 84% automated resolution rate. Most customers pay per conversation, which keeps costs predictable, although the platform is priced for enterprise budgets.

What we like

Where it falls short

5. Decagon — best for complex workflows owned by CX teams

Decagon provides AI agents for chat, email and voice, and its main selling point is Agent Operating Procedures, or AOPs. These are natural-language instructions, written much like an SOP for a new employee, that turn into structured logic the agent can follow reliably.

CX teams can create and adjust complex processes, such as refunds or account changes, without needing engineering, while technical teams can still version the logic in Git. Decagon also offers testing, QA and reporting tools that show why the agent made each decision.

Its customers include large consumer brands such as Duolingo and Chime, which shows where the platform is focused: high-volume support operations with complicated policies.

What we like

Where it falls short

6. HubSpot Customer Agent — best for teams already running on HubSpot

HubSpot’s Customer Agent answers questions, takes action inside the HubSpot CRM and passes conversations to human reps with full context. Because it sits in the same system as contact, company and ticket data, it can personalize responses using each customer’s history.

The agent works across chat, email, forms, WhatsApp, Facebook Messenger and voice. HubSpot reports an average resolution rate of 70%, and the agent costs $0.50 per resolved messaging conversation, with voice billed at $0.50 per minute.

It’s only available on HubSpot’s Professional and Enterprise editions and runs on HubSpot Credits, so it makes the most sense if HubSpot is already your main CRM and help desk.

What we like

Where it falls short

7. Forethought — best for multi-agent help desk automation

Forethought offers several agents, each automating a different part of customer service. Solve fully resolves customer issues, Triage classifies and routes tickets by intent, sentiment and urgency, Assist works as a copilot for human agents, Discover finds gaps in the knowledge base, and Agent QA scores conversations handled by people.

This setup suits support teams that want to automate the whole ticket process, not just the first reply. Forethought integrates with help desks such as Salesforce, Zendesk and Intercom, and its browser agent can complete tasks in legacy systems that have no API.

Zendesk acquired Forethought in 2026, and it is now available both as a Zendesk add-on and as a standalone product.

What we like

Where it falls short

8. Gorgias AI Agent — best for Shopify stores

Gorgias is a conversational commerce platform for Shopify brands. Its AI Agent works as a Shopping Assistant that answers product questions and makes recommendations before purchase, and as a Support Agent that tracks orders, processes returns and refunds, and edits orders afterward.

Thanks to its deep two-way Shopify integration, the agent can take action based on real order data. Gorgias says the AI Agent can resolve up to 60% of conversations across email, chat and SMS.

Pricing is based on resolved conversations, at $0.90 per AI resolution on annual plans or $1.00 on monthly billing. There is no charge when a conversation is passed to a human.

What we like

Where it falls short

9. Tidio Lyro — best for small and mid-sized businesses

Lyro is Tidio’s AI agent, and it’s one of the easiest ways for a small business to automate customer conversations. It learns from your existing support content and answers only from that content, which reduces made-up answers. If a question falls outside its knowledge, it passes it on to a human.

Lyro works across live chat, email, Instagram, Messenger and WhatsApp, and its Smart Actions can check order status, update a shipping address or start a return using your own systems. Tidio reports an average resolution rate of 75%, and every account comes with 50 free Lyro conversations.

After the trial, you’re charged per conversation Lyro replies to, starting from about $0.50 per conversation. If you use another help desk, you can add Lyro through Lyro Connect on Tidio’s higher plans.

What we like

Where it falls short

10. Zapier Agents — best for custom cross-app support workflows

Zapier Agents lets you create your own AI agents that work across more than 9,000 connected apps. For customer service, you can build a support agent that queues messages, answers common questions using your help documentation and routes tickets to the right team in tools such as Zendesk, Jira or Outlook.

Agents are created in plain language, with a prompt assistant and templates to speed things up. They can call other agents, search the web for context and log everything in an activity dashboard, where you can also see what needs your input.

Zapier recommends using agents for processes where some flexibility is acceptable and classic Zaps for processes that need to run exactly the same way every time, which is a good rule of thumb for support teams.

What we like

Where it falls short

Which AI agent fits which workflow

Generally, the right option for you will depend on where your support volume comes from and where your customer data is stored.

Many teams combine two tools, for example a customer-facing agent for calls or chat and a task management layer for the internal follow-up. Mapping your customer journey touchpoints first makes it easier to see where each tool should sit.

What to look for before you choose

Depth of integration

An AI agent is only as good as the data it can access. Make sure it can read and write to your CRM, help desk or ordering system in real time, rather than relying on syncs that can leave records out of date.

Handoff experience

No AI agent will resolve everything, and some queries will be passed on to a human. Make sure whoever picks them up can see who the customer is, what the AI has already tried and what the customer needs, so no question gets asked twice.

Compliance and data privacy

If you deal with payments, health or financial data, check what certifications the vendor holds, what its data retention policies are and how it uses customer data within any AI models.

Testing and control

Look for tools with simulation or sandbox features, clear escalation rules and the ability to roll out gradually by channel or topic. These matter more over time than a polished demo.

Pricing at your real volume

Per-resolution, per-conversation and per-seat models behave very differently at scale. Calculate what you’d actually pay each month based on your real contact volumes, not the vendor’s example.

Common mistakes when automating customer service workflows

Final thoughts

AI agents have come a long way from the scripted chatbots of a few years ago, and the best options now resolve real queries using live customer data. The right choice for your team will depend on your main channels, your CRM and how much control you want over the agent.

For Salesforce-first contact centers, Natterbox stands out for its native integration, reliability and ease of use on the phone channel. For the internal follow-up side, Workast makes sure every escalation has an owner. By combining the right front-line agent with a clear follow-up process, your team can focus on the conversations that truly need a human.