7 Top AI Agents for Customer Service in 2025 | AI in Customer Service Examples

Is your enterprise losing customers, not due to your product, but to slow and inconsistent support?
The reality is that every single customer is invaluable to you, but a lack of proper empathy and responses can cost you thousands of dollars!

We’ll you're in the right place. In this guide, we dive deep into the top AI agents for customer service. We’ll compare their features, pricing, and ideal use cases to solve this using the best AI agents for customer service for your business.

What Are AI Agents for Customer Service?

AI agents for customer service use sophisticated technology, like artificial intelligence, to manage customer interactions. Today’s AI agents are built with powerful Large Language Models, known as LLMs.

This is different from old-school chatbots that followed rigid scripts. They can engage in personalized, human-like conversations to solve problems on their own.

This is a big improvement from the frustrating, rule-based systems of the past. One example is early IVR menus that trapped customers in endless loops. This shift from simple automation to intelligent, agentic AI is reshaping how businesses connect with their customers.

How AI Agents Work in Customer Support

AI agents in customer service and support operate on a spectrum. Their functions range from tools that assist humans to platforms that run fully on their own.

• Human-Centric AI Assistance: At one end, AI acts as a copilot for your support team. Its main purpose is to make human agents faster and more knowledgeable. It helps with tasks like drafting replies, summarizing long conversations, and finding information instantly. The AI augments your team rather than replacing it.
  
• Hybrid Omnichannel Suites: In the middle are platforms that blend a traditional helpdesk with powerful AI. These systems aim to automate a large number of interactions. They still have a sturdy workspace for human agents to handle the more complex issues.
  
• AI-First Automation: At the far end are platforms built from the ground up to be AI-native. Their primary goal is to resolve as many customer issues as possible without any human help. Here, human agents are mainly an escalation point for the most difficult cases. These AI agents are designed to be the first, and often the only, point of contact for the customer.

7 Real-World Examples of AI Agents for Customer Service.

Navigating the crowded market of top AI agents for customer service can be a challenge. Based on our analysis, here are seven of the top AI agents that stand out in 2025 for their unique capabilities and strategic direction.

1. Thunai

Thunai's mission is to take a company's scattered knowledge and turn it into a fleet of smart AI agents for customer service and sales. 

This knowledge can come from documents, videos, and CRM data. These agents can then act and automate instantly. The platform is primarily geared towards large enterprise clients and Fortune 500 companies.

On the whole, Thunai is one of the top AI agents for customer service in terms of automating workflows, follow-ups, and even the creation of tickets. Aside from this, this Customer service AI agent also comes at an affordable price and requires little to no level of technical experience to deploy.

Key Features of Thunai:

• The Thunai Brain: This is the platform's center, a multimodal learning system. It ingests and connects knowledge from various sources like PDFs, videos, and websites to power its AI agents.
  
• Specialized Agent Ecosystem: Instead of a single chatbot, Thunai has a suite of agents for different channels. These include a Voice Agent for human-like phone conversations and a Chat Agent for websites. It also has an Email Agent for automating inbox management and an Application Agent for social networks like LinkedIn.
  
• Extensive Multilingual Support: A key strength is its support for over 150 regional languages. It has a deep specialization in over 20 Indian languages, making it ideal for global operations.
  
• Workflow Automation & Sentiment Analysis: The AI can automate ticket routing, set priorities, and draft responses. It also analyzes the emotional tone of messages to escalate urgent issues to human managers.

Pros:

• Highly versatile for both sales and customer support teams.
• Capable of powerfully automating a wide range of tasks.
• Allows businesses to restrict access to sensitive data.

Cons:

• Carries a risk of AI bias based on its training data.
• A notable lack of independent user reviews on major platforms, such as G2 or Capterra. This presents a risk for buyers who rely on social proof.

2. Help Scout

Help Scout stands out by deliberately taking a human-centric path to customer service. Founded in 2011, this AI agent for customer service positions itself as an alternative for businesses that prioritize high-quality human interactions over aggressive automation.
This makes it one of the top AI agents for customer service for small to mid-sized businesses and growing companies. This AI agent suits those who want a powerful yet simple tool that their teams will enjoy using.

Key Features of Help Scout:

• Shared Inbox: The platform's foundation is a collaborative shared inbox. It feels like a familiar email client, avoiding the impersonal nature of traditional ticketing systems.
  
• Built-in AI Assistant: AI is included in all plans at no extra cost. It assists human agents by generating high-quality draft replies, summarizing long conversations, and giving instant translation.
  
• Beacon Widget: This is an embeddable website widget. It gives customers 24/7 self-service access to the knowledge base, powered by AI to give instant answers.
  
• Contact-Based Pricing: In a major strategic shift, Help Scout charges based on the number of unique contacts helped each month, not per user. This predictable model encourages collaboration by allowing unlimited users.

Pros:

• Exceptionally easy to use, with a clean and intuitive interface that shortens onboarding time.
• Its own customer support is frequently praised as being fast, responsive, and genuinely helpful.
• The pricing model is affordable and transparent, which is advantageous for growing teams.

Cons:

• Reporting and automation capabilities are less advanced compared to enterprise-level competitors.
• The platform is fundamentally centered around email and lacks any native phone or voice functions.

3. Zendesk

Zendesk is the enterprise-grade omnichannel behemoth. This is one of the top AI agents for customer service that evolved from a simple helpdesk into a complete customer service solution. Founded in a Copenhagen loft in 2007, it has grown into a massive customer service platform.
This top AI agent for customer service is designed to manage the entire customer experience at scale. Its target audience is primarily mid-market and large enterprise businesses. These companies often have complex global operations and a need for highly detailed reporting and analytics.

Key Features of Zendesk:

• Zendesk Suite: An all-in-one platform that bundles a powerful ticketing system, messaging, voice, a help center, and analytics into a unified agent workspace.
  
• AI Agents and Copilot: It has a blended workforce where AI Agents resolve conversations autonomously. A Copilot feature assists human agents with suggestions and context.
  
• Advanced Add-Ons: Much of its power comes from enterprise-grade add-ons. These include AI-driven Workforce Management for forecasting and scheduling, and Quality Assurance for automatically scoring all conversations.
  
• Extensive Marketplace: A major strength is its marketplace of over 1,200 apps and connections. This allows it to link with almost any other business tool.

Pros:

• A feature-rich one-stop shop capable of handling any customer service scenario.
• Highly scalable, making it a good choice for rapidly growing businesses.
• Presents deep, customizable reporting and analytics capabilities.

Cons:

• Its immense power comes with a steep learning curve; users consistently report that it is complex and overwhelming to set up.
• The pricing is expensive and complicated. It has a high Total Cost of Ownership once necessary add-ons are included.
• Ironically, one of the most common complaints is about the poor quality of Zendesk's own customer support.

4. Cognigy

Cognigy is an industrial-strength Al workforce platform. It is designed exclusively for large, global enterprises and their high-volume contact centers. Founded in Germany in 2016, Cognigy supplies a foundational technology toolkit.
This top AI agent for customer service is ideal for businesses to build, manage, and deploy their own highly customized and secure AI agents. On the whole, this AI tool has a client list that includes major brands like Toyota, Lufthansa, and Nestle.

Key Features of Cognigy:

• LLM Orchestration: A key strength is its ability to act as an orchestration layer. This allows businesses to use and switch between different LLMs from vendors like OpenAI and Google to find the best model for a specific task.
  
• Deployment Flexibility: Cognigy has unparalleled deployment options. These include standard SaaS, private cloud, or fully on-premises within a company's own data center, which is important for regulated industries.
  
• Developer-Centric Platform: This AI agent for customer service is built for technical teams. It has an open API, a full-featured Command Line Interface, and a flexible connection framework for deep customization.
  
• Low-Code Visual Builder: Despite its technical depth, it features an intuitive visual flow builder. This allows non-technical users to build and deploy basic bots.

Pros:

• A highly advanced, powerful, and flexible platform for solving complex enterprise problems.
• Enterprise-ready security and compliance with standards like GDPR, SOC2, and HIPAA.
• The Cognigy team receives high marks for being collaborative and supportive partners.

Cons:

• Mastering the platform's advanced features requires significant technical skills, including JavaScript and API knowledge.
• Voice capabilities were added as a connection, not a native feature. This can lead to higher latency and an unnatural conversational experience.
• The pricing is prohibitively high for anyone outside of large enterprises. Annual contracts frequently exceed $100,000.

5. Gorgias

Gorgias is the e-commerce revenue engine. It is a helpdesk purpose-built from the ground up to serve online merchants. Founded in 2015, Gorgias strategically shifted to customer support agents.
This is one of the AI customer service companies that has since become a dominant force in the Shopify ecosystem.

This AI agent for customer service fundamental philosophy is to turn the helpdesk from a cost center into a revenue generator. It does this by using customer conversations to increase sales and build loyalty.

Key Features of Gorgias:

• Deep Shopify Connection: This is its most celebrated feature. Agents can view customer data, access order history, and perform actions like issuing refunds directly within Gorgias. This creates massive efficiency gains.
  
• E-commerce Automation: This is one of the top AI agents for customer service for automating responses to the most common e-commerce questions. These include Where is my order?, returns, and product inquiries.
  
• Revenue Generation Tools: Through its AI Agent and proactive chat campaigns, Gorgias can suggest products and give timely discounts. This helps to lower cart abandonment and raise conversion rates.
  
• Ticket-Based Billing: Pricing is based on the number of billable tickets handled each month, rather than per agent. This matches cost with support volume.

Pros:

• The smooth Shopify connection is consistently described as a game changer for e-commerce teams.
• Effectively consolidates all key e-commerce communication channels into a single inbox. This includes email, chat, and social media DMs.
• Generally regarded as intuitive and easy to learn for users in the e-commerce space.

Cons:

• The ticket-based pricing, especially the high overage fees, can become very expensive and unpredictable.
• Its deep specialization in e-commerce makes it a poor fit for other business models like B2B SaaS.

6. Ada 

Ada is an Al-native automation specialist. In terms of AI customer service companies, Ada is a pure-play platform designed to autonomously resolve the highest possible percentage of customer interactions.

One of the top AI agents for customer service, Ada acts as an AI layer that connects with and hands off to a separate human helpdesk system like Zendesk. Its clients include major enterprises like Meta, Verizon, and Shopify.

Key Features of Ada:

• Reasoning Engine: The platform's brain is a proprietary system. It combines multiple AI models, knowledge retrieval, and safety guardrails. This allows it to understand complex inquiries and dynamically create a plan to solve them.
  
• No-Code Builder: Despite its technical power, Ada is designed to be managed by non-technical business teams via a user-friendly, drag-and-drop interface.
  
• Action-Oriented Connections: The AI agent for customer service does not just give information. It connects to business systems to perform tasks and execute processes, truly resolving issues from start to finish.
  
• Usage-Based Pricing: The cost model is driven by the Automated Resolution. This is defined as an interaction fully resolved by the AI without a human handoff.

Pros:

• Highly effective at handling large volumes of inquiries and freeing up human agents.
• The no-code builder is consistently praised as being intuitive and easy for business users to manage.
• The Ada team is often described as a supportive and collaborative strategic partner.

Cons:

• The most common complaint revolves around buggy or limited connections with other systems, particularly the live chat handoff to helpdesks.
• It is an expensive, enterprise-grade tool. Businesses must also purchase and maintain a separate helpdesk for human agents, adding to the total cost.

7. Yuma AI

Yuma Al is the e-commerce automation upstart. It is a new challenger born in the modern generative AI era. Founded in late 2022, just before the public release of ChatGPT, its architecture is built around more advanced, agentic AI from day one.
This top AI agent for customer service positions itself as a direct and formidable competitor to Gorgias. This AI tool aims to have a more powerful and true automation engine for e-commerce merchants on platforms like Shopify.

Key Features of Yuma AI:

• Agentic AI for E-commerce: Yuma's key differentiator is that its AI agents are designed to take action, not just answer questions. This includes processing refunds, modifying orders, and changing subscriptions directly via backend connections.
  
• Pre-built E-commerce Playbooks: It comes with a library of pre-built automations. These are designed to handle the most common e-commerce support tickets, like order status, returns, and order changes.
  
• Brand Voice Alignment: The AI can be trained to respond in a brand's specific tone of voice. It can also adapt its tone based on the customer's sentiment.
  
• Smooth Connection: It has a simple, one-click installation for Shopify. It also connects with major helpdesks like Gorgias and Zendesk.

Pros:

• Praised as one top AI agents for customer service to automate a majority of inbound support volume with high accuracy.
• Case studies boast impressive results, such as achieving 40 to 50 percent automation within months.
• The support team receives outstanding reviews for being fast, effective, and phenomenal.

Cons:

• Official pricing is not transparent. This requires engagement with a sales team to find out the Total Cost of Ownership.
• Some users find the initial setup process to be complex and frustrating.
• Like any generative AI, it is not immune to occasional hallucinations or making incorrect statements.

Why Businesses Are Adopting AI Customer Service Agents

The push towards AI agents in customer service is driven by a fundamental business need. Businesses want to break the traditional trade-off between cost and quality.
Historically, companies relied on automation like IVR systems to deflect inquiries and lower congestion. However, this often created rigid and frustrating experiences for customers.

However, by automating repetitive tasks, businesses can free up their human agents to work on the most complex and high-value customer interactions. Using AI agents for customer service can lead to better outcomes for everyone.

Key Benefits of Using AI Agents for Customer Service

• Increased Efficiency and Cost Savings: AI customer service agents dramatically lessen the workload on human teams, leading to significant operational cost savings. Platforms like Yuma AI have shown they can automate 40 to 50 percent of support volume in months.
  
• Improved Customer Experience: Advanced AI can generate personalized responses based on customer history. It can even adapt its tone of voice to match the customer's sentiment, creating a more delightful interaction.
  
• Augmented Human Agent Performance: By supplying instant conversation summaries, drafting high-quality replies, and finding information in the knowledge base, AI frees up human experts to handle the most challenging issues.
  
• Revenue Generation: By suggesting intelligent product recommendations and proactive assistance to shoppers, platforms like Gorgias can raise conversion rates and decrease cart abandonment.

Common Challenges When Setting up AI Service Agents

• Connection Complexity: Buggy or limited connections, such as a handoff that fails to pass customer data, can lead to broken experiences and major operational headaches.
  
• High Total Cost of Ownership (TCO): Costs can include unpredictable overage fees, as with Gorgias, or the cost of a separate helpdesk license, as with Ada. For platforms like Cognigy, the TCO must also include the salaries of the dedicated developer team needed to operate it.
  
• AI Hallucinations and Bias: They can hallucinate and give incorrect information. They can also develop biases based on the data they were trained on. This requires continuous monitoring and coaching to maintain accuracy and fairness.
  
• Steep Learning Curve: Powerful enterprise-grade platforms are often complex. Mastering their advanced capabilities can require a significant investment in time and training. Sometimes, specialized technical skills like JavaScript are needed.
  

How to Get Started with AI Customer Service

Choosing the right AI customer service agent is a major strategic decision. To get started, you need to assess your own business needs first. Here is a simple framework:

1. Identify Your Business Model: Are you an e-commerce store? Your search should start with specialists like Gorgias or Yuma Al. If you're a B2B SaaS or finance company, you'll need a more horizontal platform like Zendesk, Help Scout, or Thunai.
   
2. Define Your Primary Goal: Do you want to assist your existing human team? Help Scout is a clear choice. Is your goal maximum automation? Then look to AI-first platforms like Ada, Yuma AI, or Cognigy.
   
3. Assess Your Team's Technical Skills: Do you have a dedicated team of developers, AI trainers, and engineers? The immense power and customizability of Cognigy would be fully available to you. You would have the resources to manage its foundation-like nature.
   
4. Consider Your Budget: If you need predictable, transparent, and affordable pricing for a large, collaborative team, then Help Scout's unique per-contact model is the ideal financial fit. It removes the penalty for having more team members involved in support. If you have a substantial enterprise budget and require maximum power and scalability, then Zendesk, with its necessary add-ons, and Cognigy are the primary options to review. 

Why Choose Thunai for AI Customer Service Agents

While we've explored several top-tier AI agents for customer service, you need one that automates workflows and responds to customers with context and empathy.

Thunai’s unique strength is its ability to synthesize all of a company's siloed knowledge and make it actionable in a way that’s humanized. 

With its deep specialization in over 150 languages, including regional dialects, Thunai comes at on top in terms of communication.

Moreover, Thunai is exceptionally well-suited for global enterprises looking for AI customer service agents.

Want to see how Thunai works? Sign up for a free trial!

FAQs for AI Agents for Customer Service

Who is the best AI customer service agent?

There is no single best agent, as the ideal choice depends on your business needs. For e-commerce, Gorgias and Yuma AI are strong choices, while Thunai, Zendesk, and Cognigy serve large enterprises. Thunai and Help Scout are the top choices for businesses that want to assist their human team.

How are AI agents used in customer service?

AI agents act as co-pilots to help human agents work faster and provide 24/7 self-service to customers. They can also act as autonomous agents that handle entire interactions from start to finish. This includes performing tasks like processing refunds or scheduling meetings on their own.

Can AI take over customer service?

AI is not taking over customer service entirely, but it is fundamentally changing the field. Most businesses use AI to automate repetitive tasks, allowing human agents to focus on high-value interactions. This creates a new balance where companies can choose between AI-first automation and human-centric assistance

How much does an AI call center agent cost?

The cost varies dramatically based on the platform and its capabilities. Some tools include AI features in plans starting at around $50 per month. Enterprise-grade platforms are much more expensive and can cost over $70,000 annually.

Which is the best AI chatbot for customer service in 2025?

The term chatbot is becoming outdated as technology shifts to more capable AI agents. For e-commerce, Yuma AI is a top contender, while Ada is a proven leader for general-purpose automation. Help Scout's built-in AI is the best choice for assisting a human team rather than replacing them.

What are the disadvantages of AI in customer service?

The main disadvantages are high costs and a complex total cost of ownership. There are also significant technical challenges involved in the implementation. Ensuring reliable connections between the AI and other business systems can be particularly difficult.

‍