A B2B SaaS Buyer’s Guide for 2026: Best AI Agents for Customer Support

Your support queue is growing faster than your headcount. Customers expect instant answers across every channel. Traditional chatbots break the moment a query goes off-script. Sound familiar? Today’s customer service landscape demands more autonomous agents and advanced AI systems that independently manage support tasks across multiple channels, and are transforming how companies handle support at scale.

This is the reality facing customer service departments in 2026, and it’s why AI agents have moved from nice-to-have to a survival strategy. Unlike chatbots that just answer questions, AI agents actually resolve tickets by processing refunds, updating accounts, and escalating when human judgment is needed.

Meeting customer expectations now means providing seamless support across all digital channels, chat, email, social, SMS, and voice, to deliver a unified, high-quality customer experience.

But not all AI agents are built the same. Some are powerful automation add-ons to legacy ticketing systems. Others are AI-first platforms designed from the ground up. AI agents enable self-service options, empowering customers to resolve issues on their own, and provide 24/7 availability so customers can get support at any time.

This guide breaks down the best AI agents for customer support, what each does well, where they fall short, and which one fits your team, whether you’re a large company, an ecommerce brand, or any organization with high support volumes.

What is AI customer support exactly?

AI customer support is transforming the way businesses serve customers by leveraging advanced AI agents to handle customer inquiries and deliver fast, accurate, and personalized support.

Unlike traditional customer service representatives who may be limited by volume and working hours, AI agents use natural language processing to understand and respond to customer questions around the clock. This not only boosts customer satisfaction by providing instant responses but also allows service representatives to focus on complex issues that require human empathy and judgment.

By automating routine support tasks, AI customer support increases operational efficiency and ensures that customers receive consistent, high-quality service. AI agents can resolve issues, answer questions, and even anticipate customer needs, all while learning from each interaction to deliver better customer experiences over time.

The result is a more efficient support operation where human agents and AI work together to deliver exceptional service and drive business growth.

What makes an AI agent different from a chatbot?

An AI agent in a customer service team is autonomous software that uses large language models and machine learning to understand customer inquiries, make decisions, and complete multi-step tasks like processing refunds, updating accounts, or escalating issues without waiting for human instructions.

Unlike basic chatbots, autonomous agents can independently execute tasks and manage support operations, automating routine processes and enhancing overall efficiency.

The key distinction: AI agents act. Chatbots just answer.

A chatbot might tell you where to find the return policy. An AI agent processes the return, generates the shipping label, and sends the confirmation email without human involvement.

By handling these routine tasks, AI agents make support operations more productive and enable human agents to focus on complex or sensitive customer issues, thereby improving efficiency and customer satisfaction.

Best AI agents for customer support: comparison

Note:
AI agents in 2026 fall into three main categories: (1) autonomous customer-facing agents that interact directly with users, (2) internal agent copilots that assist organization staff, and (3) workflow automation tools that streamline processes across departments.

Text App: the AI-first platform that turns support into revenue

Best for: Ecommerce, iGaming, and SaaS teams who want to upgrade support from a cost center to a profit driver.

Most AI agents focus on deflection to keep tickets out of the queue. Text takes a different approach: every support conversation is a revenue opportunity.

Text’s AI agents are powered by Text Intelligence and built into a unified workspace that combines live chat, ticketing, and CRM. They don’t just answer questions. They execute by processing refunds, updating accounts, recommending products, and identifying upsell opportunities mid-conversation. Text AI agents connect with third-party apps, such as CRMs, to streamline workflows and enhance existing systems.

What sets Text apart:

• Revenue built in: Product recommendations, cross-sell, upsell, and personalized discounts happen naturally during support conversations rather than as awkward afterthoughts. AI agents can provide personalized recommendations for additional products based on stored user preferences.
• AI-first architecture: Unlike platforms that bolted AI onto legacy ticketing systems, Text was built around AI from day one. Automation feels native, not forced.
• Transparent pricing: Per-seat pricing with no surprise per-resolution or per-ticket fees. You know what you’ll pay before you sign.
• Industry flexibility: Works across ecommerce platforms (not just Shopify), iGaming, and SaaS, unlike competitors locked to specific ecosystems.
• Fast setup: Most teams deploy in minutes by connecting their knowledge base. No weeks of configuration required.

According to Text’s homepage, smart teams resolve up to 89% of cases and turn them into revenue.

Why Text wins: The question isn’t just “how many tickets can we deflect?” It’s “how much revenue can be generated?” Text is built to answer the second question.

See how Text AI agents turn service into sales →

Intercom Fin

Best for: SaaS and digital-first brands already using Intercom.

Intercom’s Fin AI agent has become the benchmark for conversational AI in customer support. Powered by the proprietary Fin AI Engine, it handles complex multi-turn conversations, asks clarifying questions, and resolves issues end-to-end.

What Fin does well:

• Strong resolution rates: Intercom reports a 66% average resolution rate across 6,000+ customers, with over 20% achieving 80% or higher.
• Procedural reasoning: Fin 3 introduced Procedures, which enable the AI to follow multi-step workflows, such as processing refunds or verifying account changes.
• Personalized responses using previous interactions: Fin leverages prior interactions to tailor responses and handle complex customer inquiries more effectively, thereby improving service quality.
• Summarization for training: Fin can provide summaries of meetings, service calls, and other customer communications, which aids in training new customer service representatives.
• Multilingual: Supports 45+ languages with automatic translation.
• Ecosystem integration: If you’re already on Intercom, Fin plugs directly into your existing workflows.

Where Fin falls short:

• Per-resolution pricing adds up: At $0.99 per resolution, costs can scale unpredictably. A team resolving 2,000 tickets per month pays an additional $1,980 on top of the base subscription.
• Best value requires Intercom commitment: Fin works with other helpdesks, but the tightest integration is within Intercom’s ecosystem.
• Complex setup at scale: Enterprise deployments can take weeks to be properly configured.

Pricing: $0.99 per resolution, plus Intercom subscription fees ($29-132/seat/month depending on plan).

Zendesk AI

Best for: Large enterprises already invested in the Zendesk ecosystem.

Zendesk has processed over 18 billion service interactions, giving its AI a massive training advantage. For enterprises already running on Zendesk, the native AI agents offer familiar workflows with added automation.

What Zendesk AI does well:

• Massive scale: The platform handles enterprise-level volumes with proven reliability.
• Omnichannel coverage: AI agents work across email, chat, voice, and social.
• Strong compliance: Enterprise-grade security and audit trails for regulated industries.
• Intelligent triage: Automatically routes tickets by intent, sentiment, and language.
• Efficient management: Zendesk helps organizations manage support operations efficiently by overseeing AI agents, workflows, and user preferences through a unified interface.
• Enterprise-focused features: Zendesk AI is tailored for large enterprises, offering native agent assistance, intelligent ticket routing, and automated triage.

Where Zendesk AI falls short:

• Pricing complexity: According to Zendesk’s pricing page and third-party analysis, base plans range from $55 to $ 169/agent/month. Advanced AI is a $50/agent/month add-on. Automated resolutions cost $1.50-2.00 each. A 25-agent team can easily exceed $49,500 in annual costs before AI resolution fees.
• AI feels bolted on: Unlike AI-first platforms, Zendesk’s AI is layered on top of a legacy ticketing system.
• Interface feels dated: Users report that the experience is less intuitive than newer competitors.

Pricing: Suite plans $55-169/agent/month + $50/agent AI add-on + $1.50-2.00/resolution.

Forethought

Best for: High-volume enterprise teams with rich ticket history.

Forethought’s AI agents learn from your historical tickets and help center content to deliver personalized responses from day one. The platform emphasizes “agentic AI” with agents that reason, decide, and take action rather than just respond.

What Forethought does well:

• Learns from your data: Trains on past tickets to understand your specific products, policies, and customer language.
• Multi-agent system: Solve (customer-facing), Triage (routing), and Assist (agent copilot) work together.
• Knowledge gap detection: Identifies missing articles and suggests content improvements.
• Delivers actionable insights: Analyzes support data to generate insights that help optimize customer service operations and identify trends.
• High resolution claims: Forethought reports up to 98% resolution rates for customers with well-optimized setups. For comparison, Crescendo.ai offers multimodal capabilities, handling text, voice, and audio messages with human-like empathy, and achieves 99.8% resolution accuracy.

Where Forethought falls short:

• No transparent pricing: Custom quotes only, so you won’t know costs until after sales conversations.
• Requires substantial data: Best results require thousands of historical tickets for training.
• Complex implementation: Not ideal for SMBs or teams wanting quick deployment.

Pricing: Custom, based on deflection volume and ticket count.

Gorgias

Best for: Shopify-native ecommerce brands with predictable ticket volumes.

Gorgias is purpose-built for ecommerce, with deep integrations into Shopify, BigCommerce, and Magento. Its AI Agent handles order tracking, returns, and product recommendations while pulling real-time data from your store.

What Gorgias does well:

• Deep Shopify integration: Pull order data, process refunds, and update shipping all within conversations.
• Ecommerce-specific workflows: Built-in handling for common scenarios like “where’s my order” and returns.
• Shopping assistant: AI-powered product recommendations during support chats.
• Personalized customer care: Delivers efficient, proactive support through AI, improving customer engagement and troubleshooting.
• Trusted scale: Over 15,000 brands use Gorgias.

Where Gorgias falls short:

• Confusing pricing structure: Ticket-based billing ($10-900/month depending on volume) plus separate AI Agent fees ($0.90-1.00 per AI-resolved conversation).
• Double-billing: According to Gorgias billing documentation, when AI resolves without human handoff, you pay both the ticket fee AND the automation fee.
• Platform-limited: Heavy Shopify focus means limited value for non-Shopify stores, iGaming, or SaaS.
• Volume spikes hurt: Ticket-based pricing means seasonal surges can double costs unexpectedly.
• Escalation: Current AI systems ensure seamless handoff to human agents by transferring the full context and transcript when escalation is necessary.

Pricing: Helpdesk plans $10-900/month based on ticket volume. AI Agent adds $0.90- $ 1.00 per automated resolution.

Freshdesk Freddy AI

Best for: SMBs wanting to add AI without major investment.

Freshdesk’s Freddy AI offers a practical entry point for smaller teams. It handles ticket categorization, suggested responses, and basic automation without the enterprise price tag.

What Freddy does well:

• Affordable: Plans start lower than most competitors.
• Quick deployment: Less complex than enterprise options.
• Familiar interface: If you know Freshdesk, Freddy fits naturally.
• Efficient customer issue resolution: Freddy quickly identifies, troubleshoots, and escalates issues as needed.
• Routine task assistance: AI agents like Freddy can also support critical routine tasks, such as customer data management and project management.

Where Freddy falls short:

• Less sophisticated AI: Not as advanced as AI-first platforms for complex reasoning.
• Limited task execution: Better at assisting agents than fully resolving issues autonomously.
• Deflection over resolution: Stronger at routing tickets than completing actions.

Pricing: Included in Freshdesk plans, with advanced AI features in higher tiers.

Ada

Best for: Global teams needing multilingual automation without engineering resources.

Ada built its platform for non-technical teams to create sophisticated AI agents without writing code. For enterprises operating across languages and regions, it's a strong contender.

What Ada does well:

• No-code builder: Business teams can create and modify AI workflows without developers.
• Multilingual: Supports 50+ languages.
• Enterprise-ready: Strong compliance and security credentials.

Where Ada falls short:

• Custom pricing: No transparent pricing available.
• Less action-oriented: Stronger on conversation handling than task execution.

Pricing: Custom quotes only.

Implementation and integration

Successfully implementing AI agents in customer service departments requires a strategic approach that prioritizes seamless integration with existing systems and processes.

Businesses need to ensure that their AI agents have access to accurate data and robust knowledge management resources, enabling them to resolve issues efficiently and provide relevant responses to customers. Integration with CRM software, helpdesk platforms, and other essential tools is key to empowering AI agents with the context they need to handle customer interactions effectively.

It’s also important to establish clear workflows for managing complex inquiries and determining when to escalate issues to human agents. Regularly monitoring agent performance and refining processes ensures that both AI and human agents deliver consistent, high-quality support.

When focusing on data quality, knowledge management, and continuous improvement, organizations can maximize the value of AI agents and create a customer service environment where technology and people work in harmony.

AI agent platforms and security

Choosing the right AI agent platform is crucial for delivering secure and reliable customer support. Leading platforms such as Chatbase and Forethought offer comprehensive solutions for building, training, and deploying AI-powered support agents.

These platforms offer advanced tools for integrating with existing systems, managing support agents, and ensuring that customer data remains protected at every stage.

Security is a top priority for AI agent platforms, with features such as encryption, strict access controls, and regular security audits built in to safeguard sensitive information. Compliance with industry standards and regulations is also essential, ensuring that businesses can trust their AI agents to handle customer data responsibly.

When selecting a platform that prioritizes security and robust integration capabilities, companies can confidently deploy AI agents that enhance customer support while maintaining the highest standards of data protection.

Best practices for AI agents

To unlock the full potential of AI agents in customer support, businesses should follow proven best practices. Start by providing high-quality training data to ensure that AI agents understand your products, services, and customer needs.

Continuously monitor agent performance, using metrics like customer satisfaction, resolution rates, and response times to identify areas for improvement.

Seamless integration with existing systems is essential, allowing AI agents to access relevant data and deliver personalized, context-aware responses. Design your AI agents to recognize when a situation requires human intervention, ensuring that complex issues are escalated smoothly to human agents.

Focusing on operational efficiency, context, and continuous improvement allows businesses to create AI-powered support agents that deliver outstanding customer experiences and drive measurable results.

How to choose the right AI agent?

1. Define your outcome metric

What does success look like?

• Deflection rate? Most platforms optimize for this.
• Resolution rate? Fewer do this well.
• Revenue from support? Only a handful even try. Text is built for this.

Leveraging data analysis insights is crucial to effectively define and measure these success metrics. The use of AI agents can also lead to a significant increase in customer satisfaction scores.

2. Assess your tech stack

• Already on Zendesk or Intercom? Their native AI keeps you locked in but minimizes friction.
• Want flexibility? AI-first platforms like Text offer more portability.
• Shopify-only? Gorgias has the deepest integration, but you sacrifice flexibility.

When evaluating the best AI agents for customer support, it's crucial to consider how well the solution integrates with your existing tech stack, such as CRM or ERP systems, to streamline workflows and improve data access. Successful deployment of AI agents also requires careful planning and seamless integration with your current systems to maximize effectiveness.

3. Evaluate pricing transparency

• Per-seat pricing = predictable budget. Transparent pricing models like this contribute to more productive support operations by making costs clear and planning easier.
• Per-resolution pricing = scales with volume, can surprise you (Intercom Fin, Zendesk AI)
• Ticket-based + AI fees = most complex to forecast (Gorgias)
• Custom pricing = you won’t know until after sales calls (Forethought, Ada)

In 2026, AI agents can autonomously handle over 80% of routine interactions, reducing costs by up to 30% and further boosting operational efficiency.

4. Check what the AI can actually do

Not all “AI agents” are equal:

• Answer questions only? That’s chatbot territory.
• Execute tasks? Processing refunds, updating accounts, and triggering workflows is AI agent territory. AI agents also enable customer self-service by allowing users to resolve common issues and complete tasks independently, streamlining support and improving efficiency.
• Generate revenue? Product recommendations, upsells, and lead capture are where Text plays.

Leading AI agents for customer support in 2026 possess agentic capabilities, enabling them to autonomously execute multi-step workflows such as refunds, order tracking, and account updates.

5. Test escalation quality

The best AI agents know when to stop. Ask:

• Does it recognize when human judgment is needed?
• Does context transfer seamlessly to the human agent, using previous interactions to ensure the customer doesn't have to repeat themselves?
• Does the customer have to repeat themselves?

AI agents can operate 24/7, providing support to customers at any time, and use previous interactions to ensure seamless escalation to human agents when necessary.

Turn support into your growth engine

The best AI agents don’t just deflect tickets. They transform support operations into strategic assets by resolving issues, satisfying customers, and creating revenue opportunities. AI agents help organizations identify trends, optimize resources, and enhance service quality through data analysis. The question isn’t whether to adopt AI for support. It’s the platform that matches how you want to grow.

If you want support that pays for itself, Text is built for exactly that.

Future of AI Agents in Customer Support

The future of AI agents in customer support is bright, driven by rapid advancements in generative AI, natural language processing, and machine learning. As these technologies evolve, AI agents will become even more adept at understanding language, managing complex conversations, and delivering highly personalized support.

This will enable businesses to deliver better customer experiences, increase operational efficiency, and unlock new growth opportunities.

Looking ahead, AI agents will play a central role in shaping the future of customer support, working alongside human agents to create seamless, efficient, and engaging interactions. The rise of AI-powered support will also lead to the emergence of new roles, such as AI trainers and conversational designers, as organizations seek to harness the full potential of these technologies.

Ultimately, the ability to create and deploy sophisticated AI agents will be a key differentiator for businesses aiming to deliver exceptional service and build lasting customer relationships in the years to come.

FAQ

What is the best AI agent for customer support?

Text stands out for teams that want support to drive revenue, not just cut costs. Text App's AI agents recommend products, identify upsell opportunities, and process transactions during support conversations.

How do AI agents differ from customer service chatbots?

Chatbots follow scripts and answer questions. AI agents, especially autonomous agents, understand context, make decisions, and independently execute tasks beyond scripted responses.

Can AI agents handle complex customer inquiries?

Yes. Modern AI agents use multi-step reasoning to handle a wide range of customer issues, such as processing returns, verifying identity, or troubleshooting product problems.

What should I look for when evaluating AI agent pricing?

Look for transparency. Transparent pricing helps companies manage their support budgets more effectively. Per-seat pricing offers predictable costs. Per-resolution pricing scales with volume, but it can still surprise you.

How quickly can AI agents be deployed for customer support?

Deployment time varies dramatically. AI-first platforms like Text can be set up in minutes by connecting your knowledge base.

Do AI agents replace human customer service representatives?

No. AI agents handle routine interactions, allowing human agents to focus on complex, high-value conversations. Within an organization, AI agents fit into the broader organizational structure.