5 Emerging AI Customer Service Agents to Watch in 2026

Customer service automation is changing quickly. For years, businesses relied on rule-based chatbots that could answer a limited number of predefined questions. Today, a new generation of AI customer service agents is capable of understanding natural conversations, learning from company knowledge, interacting with customers across multiple channels, connecting with business systems, and deciding when a conversation should be passed to a human.

The difference is important. A traditional chatbot primarily responds. An AI agent can increasingly act. Depending on the platform, this may mean retrieving customer information, checking an order, creating a support ticket, scheduling an appointment, updating another business system, or escalating a complicated conversation to the appropriate employee.

Adoption is moving quickly as well. Salesforce reported in May 2026 that the share of surveyed customer-service organizations using AI agents had risen from 39% in 2025 to 66% in 2026.

This growth is not only about reducing costs. Businesses are looking for ways to make support faster, keep service available outside normal working hours, and allow customer-service teams to spend less time answering the same repetitive questions.

How AI Customer Service Agents Reduce the Human Workload

One of the clearest benefits of AI-powered customer service is its ability to absorb repetitive work.

Questions such as “Where is my order?”, “What does this plan include?”, “Do you ship to my country?”, “How do I reset my account?” or “What time are you open?” may individually take only a few minutes to answer. At scale, however, they can consume a significant part of a support team’s day.

AI agents can handle many of these interactions immediately. Human agents can then concentrate on situations that require judgment, negotiation, empathy, or deeper product knowledge.

Research reflects that shift. Freshworks’ 2026 Customer Service Benchmark Report says 69.4% of surveyed teams identified reducing agent workload as AI’s biggest impact. Capgemini, meanwhile, reports that 70% of customer-service agents surveyed experienced a reduction in overall workload from generative and agentic AI, while 31% of organizations reported faster response times.

The result can be a useful combination: AI provides speed and availability, while people remain available for conversations where human involvement matters.

That second part should not be overlooked. Gartner found that while half of surveyed customers said generative AI had made customer-service interactions easier, 87% considered having the option to reach a human agent essential.

Which Industries Are Using AI Customer Service?

AI customer service is appearing across industries because repetitive customer questions exist almost everywhere.

E-commerce and retail businesses can use AI for product questions, delivery updates, order information, returns, and refunds.

SaaS and technology companies can automate FAQs, product guidance, account questions, basic troubleshooting, and subscription-related inquiries.

Travel and hospitality businesses can use agents to answer booking questions, provide service information, assist customers in multiple languages, and handle large volumes of requests.

Financial services are increasingly exploring AI for customer servicing and other repetitive operational processes, although these applications generally require stronger controls because of the sensitivity of the information involved.

Home-service businesses are another practical example. A plumber, HVAC business, electrician, or similar company may receive calls while employees are already working with customers. Platforms such as Housecall Pro are incorporating AI-powered customer service for home-service businesses that can respond to incoming customer communications and connect those conversations with operational processes such as job scheduling.

These examples also show why there is unlikely to be one universal AI agent for every company. Some platforms are broad and omnichannel. Others sit inside an existing helpdesk. Some specialize in e-commerce, while others focus heavily on call centers.

Here are five emerging AI customer service solutions taking different approaches to the market.

1. WellyOn — Omnichannel AI Customer Service Agent

WellyOn is designed around a simple idea: instead of having customer conversations scattered between a website chat, email, WhatsApp, Telegram and other communication tools, businesses can connect those interactions to one AI-powered customer-service environment.

The platform’s AI agent, Welly, can be trained using a company’s own website and materials such as documents, PDFs, FAQs and screenshots. Once that knowledge is added, the agent uses it to answer customer questions in real time rather than relying only on a fixed list of scripted chatbot responses.

This makes the platform particularly relevant to businesses whose customer-service teams repeatedly answer questions about their products, policies, services or processes.

Omnichannel Customer Conversations

One of WellyOn’s central features is its omnichannel inbox.

The platform currently presents integrations or communication options including web chat, WhatsApp, Telegram, Viber, email, SMS, Instagram, Messenger, LinkedIn, Slack, Jira and ClickUp, among others. Instead of treating each customer channel as an entirely separate environment, WellyOn is built to make the AI agent available wherever customers are communicating.

This becomes increasingly useful as a business grows.

A small company may initially receive most support requests through its website. Later, customers may start writing through WhatsApp, email, Instagram or several other inboxes. Managing each separately can create additional work for the same small support team.

An omnichannel approach gives businesses a way to centralize those interactions while still allowing customers to contact the company through the channel they prefer.

AI First, Human When Needed

WellyOn does not position the AI agent as a complete replacement for a customer-service team.

When Welly cannot appropriately handle a conversation, it can hand the interaction to a human team member. Importantly, the transfer includes the conversation history and customer profile, so the employee taking over can see what has already happened instead of asking the customer to explain the issue again.

This AI-to-human model is particularly useful for support operations because not every request requires the same level of attention. A question about opening hours can be automated. A complicated billing dispute may be better handled by a person.

The platform also includes monitoring capabilities for conversations, customers and agents, along with analytics, delivery information and alerts.

Another differentiating feature is incident communication. When a business records an incident, WellyOn can connect the information with a public status page, customer notifications and the AI agent’s own knowledge so customers asking about an active problem can receive relevant information.

Companies can also customize the agent’s name, logo, colors and tone of voice rather than presenting it only as a third-party chatbot.

Best Suited For

WellyOn is particularly well suited to SMBs and growing businesses that want to automate support without building a complicated customer-service technology stack from scratch.

For smaller businesses, its appeal comes from training an agent on existing business information and making it available without a large development team. A small support team can use AI to cover routine conversations around the clock while still stepping in when human attention is necessary.

Overall, WellyOn’s strongest use case is not simply adding a chatbot to a website. It is creating an AI-assisted customer-service layer across the channels where customers already communicate, while keeping human agents available as backup.

2. My AskAI — AI Customer Service Inside Your Existing Helpdesk

While WellyOn takes an omnichannel-platform approach, My AskAI takes a different route: it is designed primarily to add an AI customer service agent to the helpdesk a company is already using.

That distinction is important.

Many organizations have spent years building their customer-service processes around platforms such as Zendesk, Intercom, Freshdesk, Gorgias or HubSpot. Replacing those systems simply to introduce AI can create unnecessary migration work.

My AskAI instead integrates directly into them. The company currently supports integrations with Intercom, Zendesk, Gorgias, Freshdesk and HubSpot and says setup does not require developers.

The AI therefore operates more like another support agent working inside the existing environment.

Learning From Existing Support Knowledge

An AI customer-service agent is only useful if it understands the business it represents.

My AskAI can learn from existing help-center articles and websites, previous support tickets, internal policies, standard operating procedures, Google Drive and Notion content. Its knowledge can also be kept synchronized as information changes.

Training on previous tickets is particularly useful because documentation does not always contain every practical detail a support team knows.

Past conversations can reveal how employees actually explain confusing features, handle unusual situations or interpret company policies. Using this information can help an AI agent respond in a way that is closer to the company’s existing support operation.

My AskAI also supports answers in more than 95 languages, making multilingual support another meaningful part of its offering.

From Answering Questions to Taking Actions

Modern customer support increasingly requires more than generating text.

A customer might ask for information about an order, account or subscription and then expect something to actually happen.

My AskAI includes tools and actions that allow the AI to connect with business data and perform certain tasks rather than limiting it to FAQ responses. Its current feature set includes user-data connections, tasks, tools, actions, insights and self-learning capabilities.

It also includes intelligent escalation.

If the AI cannot confidently resolve a request, customers can be moved to a human agent inside the company’s existing support platform instead of being trapped in an automated conversation.

That is especially important as companies give AI responsibility for more support interactions. Automation is useful when it resolves a problem faster. It becomes frustrating when customers cannot reach anyone after automation fails.

Pricing and Scalability

My AskAI currently advertises usage-based pricing averaging around $0.10 per support ticket and a Pro plan starting at $199 per month. Its Pro offering includes 1,000 tickets per month, website and document knowledge sources, historical-ticket training, user-data connections, AI tasks, analytics and multilingual support.

Best Suited For

My AskAI is particularly suitable for companies that already have an established customer-service helpdesk and want to introduce AI without replacing it.

That can include SMBs running Zendesk or Intercom as well as larger support organizations handling substantial ticket volumes.

3. Jotform AI Agents — No-Code AI Agents for Customer Interactions

Jotform AI Agents takes perhaps the broadest approach of the products on this list.

Rather than focusing exclusively on traditional customer-support tickets, Jotform allows businesses to create AI agents that can interact with users, collect information, answer questions, assist with forms, schedule appointments and support other customer-facing workflows.

That broader approach reflects Jotform’s existing position as a no-code platform.

The goal is to make creating an AI agent accessible to organizations that do not have AI developers or engineering teams available to build one from scratch.

Build and Train an Agent Without Coding

Businesses can train a Jotform AI Agent using websites, documents, reference information, FAQs and other knowledge sources. It also supports importing knowledge from systems such as Zendesk and Freshdesk.

Companies can then adjust how the agent communicates, including its personality and tone.

This can be particularly useful for customer-facing automation because the same factual answer can sound very different depending on the business. A legal-services company may require a more formal voice, while an online retailer may prefer something conversational and informal.

Once trained, the agent can be embedded on a website without requiring a custom software implementation.

Multiple Customer-Service Channels

Jotform’s AI customer-service offering extends beyond website chat.

The platform currently supports customer interactions through options including phone agents, chatbots, voice agents and WhatsApp. Its broader AI Agent feature set also references channels including Instagram, Gmail, Salesforce and SMS.

That gives organizations flexibility in how they deploy an agent.

A business may begin with a simple website chatbot and later use AI for phone conversations or messaging channels.

Jotform also supports multilingual conversations and centralized management of agent interactions.

Automating More Than Answers

Jotform’s background in forms gives its AI agents an interesting advantage when customer conversations need to turn into structured actions.

Its AI Agents can work with forms, collect information from users and perform predefined actions. Jotform’s action system can also trigger specific behavior depending on what a user says and send information to connected third-party applications.

Available integrations include tools such as Slack and Google Calendar, while additional connections cover cloud storage, e-commerce and other business applications.

For example, instead of simply telling someone how to make an appointment, an agent connected to a calendar can participate in the scheduling process.

For support conversations that cannot be handled automatically, Jotform also supports switching an AI-driven live chat to a human agent.

This helps keep automation from becoming a dead end.

Best Suited For

Jotform AI Agents are particularly well suited to SMBs, service businesses and organizations that want to experiment with AI agents without developing their own customer-service system.

4. Minimal AI — AI Customer Support Built for E-Commerce

Many AI customer-service products try to work across almost every industry. Minimal AI is taking the opposite approach.

The Y Combinator-backed company focuses specifically on e-commerce customer support. It was part of Y Combinator’s Summer 2025 batch, making it one of the newer companies on this list.

That specialization matters because e-commerce support has a very specific set of repetitive—but operationally connected—questions.

Customers do not just ask what a product costs. They ask where an order is, whether an item can be returned, whether their refund has been processed, whether an address can be changed, why a shipment is delayed, or whether a subscription can be modified.

Answering those questions properly often requires access to several different systems.

Designed Around the E-Commerce Technology Stack

Minimal AI connects with a wide range of helpdesk, e-commerce, shipping, returns, fulfillment, subscription and payment systems.

Its current integrations include Zendesk, Gorgias, Intercom, Freshdesk and Front on the helpdesk side, alongside commerce platforms such as Shopify, WooCommerce and Magento. It also integrates with shipping and fulfillment systems, return-management products, subscription tools, payment platforms and knowledge sources.

The significance of those connections is that an AI agent can work with real operational information instead of only answering from a static FAQ page.

If a customer asks where a package is, for example, useful support requires current shipping information. If they ask to cancel an order, the system needs to know whether the order has already entered fulfillment.

AI Agents That Can Take Actions

Minimal AI emphasizes end-to-end resolution rather than response generation alone.

Its agents can be configured to perform actions across connected business tools—for example, cancelling an order, blocking a shipment, creating an invoice, generating a return form or modifying a subscription.

This is an important direction in AI customer service.

The more AI agents can securely interact with the systems behind a business, the less often a conversation has to stop with something like, “A team member will look into this.”

Minimal also provides an AI Manager through which teams can teach and update the behavior of their AI agents using natural language.

According to the company, agents continuously learn from support interactions and present suggested improvements for approval. Minimal says its platform can automate up to 90% of tickets; as with any vendor-reported performance figure, actual results will depend on the business, ticket complexity, data quality and implementation.

The company publishes customer examples reporting automation rates above 80% for several e-commerce businesses.

Why Industry Specialization Matters

Minimal demonstrates one of the most interesting trends in AI customer service: vertical specialization.

Instead of trying to understand every possible business workflow, a specialized agent can concentrate on the systems and problems common to one industry.

For e-commerce, that means products, orders, shipping, fulfillment, returns, payments and subscriptions.

This can reduce the amount of customization needed before the AI becomes useful because many of the core workflows are already familiar territory for the platform.

Best Suited For

Minimal AI is best suited to e-commerce businesses with enough support volume to benefit from deeper automation, particularly companies already operating several commerce, logistics and support tools.

A small online store handling a handful of weekly inquiries may not need extensive AI workflow automation.

A growing retailer receiving hundreds or thousands of recurring questions about orders, shipping, returns and products has a much clearer use case.

For such businesses, Minimal represents a move from an AI chatbot that talks about an order to an AI agent that can potentially work with the systems managing that order.

5. Calltree — AI Customer Support for Complex Contact Centers

Calltree represents another specialized direction in the emerging AI customer-service market: AI built around complex contact-center operations.

Founded in 2025 and part of Y Combinator’s Winter 2025 batch, Calltree describes its product as enterprise-grade AI support representatives for call centers.

While many AI customer-service products begin with website chat or email, Calltree is particularly focused on environments where voice interactions remain central.

Its AI support reps can handle voice calls and chats and, importantly, connect with internal enterprise tools such as proprietary CRMs and internal dashboards.

That last capability matters because large contact centers rarely operate from a single clean software platform.

Designed for Complicated Support Work

Enterprise customer-service employees frequently have to move between several systems during a single conversation.

A representative may need to identify the customer in one system, retrieve account information from another, check an internal policy, perform an action somewhere else and then record the result.

Calltree’s focus is on enabling AI to participate in these more complicated operational environments rather than answering only basic FAQs.

The company has also focused on analyzing contact-center workflows.

Its technology can analyze call and screen-recording data to identify repetitive manual tasks and workflow inefficiencies. For example, it may identify how much time employees spend switching between applications or manually collecting information and quantify the operational impact.

That makes Calltree different from many lightweight customer-support bots.

The question is not simply, “Can AI answer this customer’s question?”

It is also, “What makes resolving this type of customer issue unnecessarily slow, and what parts of the process can be improved?”

AI With Human Supervision

Complex customer-service interactions also highlight why human oversight remains important.

Current Calltree roles describe human supervisors monitoring live AI-customer conversations, evaluating quality and stepping in when necessary. The company also says its technology is being used for complex technical troubleshooting interactions, including lengthy calls.

This hybrid approach is likely to remain important in contact centers.

Simple requests can increasingly be automated from beginning to end. Complex troubleshooting, emotionally sensitive interactions and unusual situations may require human judgment even when AI handles much of the surrounding work.

AI can still provide value in these cases by collecting information, using internal systems, suggesting next steps or reducing repetitive manual actions.

Best Suited For

Calltree is most relevant to larger businesses, enterprise contact centers and support operations with substantial voice volume or complicated internal workflows.

What Should You Look for in an AI Customer Service Agent?

The platforms above are quite different, but they also reveal several capabilities that are becoming increasingly important.

Knowledge Training

An AI agent needs reliable company information.

Look at whether the platform can learn from websites, documents, FAQs, help centers, previous tickets, internal policies and other relevant sources—and how easily that information can be updated.

Human Handoff

The goal should not be to prevent customers from reaching people.

A useful AI agent should understand when it cannot confidently resolve an issue and make escalation simple. Ideally, the human agent should receive the conversation history and relevant context as part of the transfer.

Omnichannel Support

Customers may communicate through web chat, email, WhatsApp, social platforms, SMS or phone.

If a company operates across several of these channels, it is worth considering whether the AI can work across them and whether conversations can be managed centrally.

Business Actions and Integrations

There is a significant difference between an AI agent that can explain how to cancel an order and one that can securely cancel it after verifying that the request meets the company’s rules.

Connections with CRMs, helpdesks, e-commerce platforms, calendars, project-management systems and internal tools can turn AI from an answering tool into a working part of the customer-service process.

Control

Businesses also need control over what their AI can access and what it can do.

An agent may need access to product or order information but not sensitive payment data. Companies should therefore consider permissions, escalation rules, monitoring, testing and oversight alongside automation capabilities.

The Future Is Likely AI + Human, Not AI Versus Human

The emerging AI customer-service market is not developing in one single direction.

WellyOn is moving toward an omnichannel environment where AI and human representatives can manage customer conversations across multiple platforms.

My AskAI brings AI directly into helpdesks companies already use.

Jotform AI Agents makes customizable no-code agents accessible across a broad range of workflows.

Minimal AI demonstrates how deeply an agent can specialize around e-commerce systems and operations.

Calltree shows how AI is beginning to address more complicated contact-center and enterprise-support workflows.

What these approaches share is a shift away from viewing AI as simply a chatbot at the bottom of a website.

The more useful question for businesses in 2026 is becoming: Which parts of our customer-service workload can AI handle effectively, which business systems should it be able to work with, and when should a human take over?

Businesses that answer those questions well can use AI not just to respond faster, but to give their customer-service teams more time for the conversations where people provide the greatest value.

Photo by Mohamed Nohassi on Unsplash