AI in Customer Support: Benefits, Trends, Best Tools (2025)

In this guide, I’ll break down the benefits of AI in customer support, show what it really costs, compare the best AI tools for customer support, and give you a quick 60‑day plan to launch AI in your own help desk. 

Customers expect fast, helpful answers day and night. With the latest AI, think GPT‑4o, Claude, and Grok, support teams can solve most routine questions in seconds, cut costs, and keep agents free for tougher issues.

Read on to see how you can start small, measure results, and scale confidently.

What is AI in Customer Support? 

AI in Customer Support refers to the use of AI technologies to enhance and automate customer service processes. It involves tools like chatbots, virtual assistants, and automated ticketing systems that provide faster, more efficient, and personalized support to customers. 

By leveraging AI, businesses can improve customer satisfaction, reduce operational costs, and ensure 24/7 availability.

Where You’ll See  AI in Customer Support

AI in Customer Support: Key U.S. Stats You Should Know in 2025

If you’re wondering just how big AI in customer support has gotten this year, you're not alone. I’ve been digging into the latest 2025 data, and the shift is huge.

By 2025, over half of all U.S. businesses, 56%, are already using AI to handle customer service tasks. That includes everything from AI chatbots and auto-replies to intelligent ticket routing. 

What surprised me the most? 👇

Gartner even predicts that 80% of support teams will be using generative AI tools this year to boost agent productivity. 

What About Your Customers? They’re Ready

AI in support isn’t just a win for businesses, it’s something customers are now actively expecting.

• I found that almost 1.5 million people had at least one conversation with a chatbot within the past year.
• And when asked, 82% said they’d rather use a chatbot than wait around for a human to respond. 
• Even more telling: 96% think companies should prioritize AI-powered chat over traditional support.

That’s not just about speed either. Businesses using chatbots are also seeing around 24% higher customer satisfaction scores, which makes sense. We all appreciate quick, helpful responses when something goes wrong.

And the future? Gartner says that by next year, 20–30% of customer support agent roles could be automated entirely by generative AI.

So, companies using AI for support are cutting costs (some by as much as 25%), saving time, and delivering a faster, more consistent experience for their users.

How AI in Customer Support Works?

1. It Figures Out What the Customer Wants (Intent Detection)
When someone types or speaks to the support system (like “Where’s my order?” or “I need to change my address”), AI uses natural language processing (NLP) to understand what they mean and how they’re feeling, whether they’re calm, confused, or frustrated.

2. It Looks for the Right Answer (Knowledge Retrieval)
Once it knows the question, the AI searches all the resources your company has, including FAQs, previous support tickets, product info, or tools like Shopify and Salesforce, to find the best, most accurate response.

3. It Responds or Sends It to the Right Person (Response or Escalation)

Depending on how complex the question is, the AI does one of three things:

• Instant reply: It gives a helpful answer right away on the same chat, email, or app the customer is using.
• Agent support: It suggests an answer or next step for a human agent to review and send.
• Smart handoff: If it’s a tricky issue, the AI forwards the case to the right team member or department with all the context.

4. It Can Even Take Action (Action Execution)

The most advanced AI systems don’t just answer questions, they can do things. For example, they can:

• Refund a customer
• Reschedule a delivery
• Update someone’s contact or billing info

They do this by securely connecting to your internal systems, so the job gets done without back-and-forth or manual clicks.

According to Zendesk CEO Tom Eggemeier,

Key Benefits of AI in Customer Support

Using AI in customer support can be a real asset, making life easier not only for your business but also for your customers.

Here are some key benefits I've seen and believe you'll experience too:

1. Always-on, Instant Support (24/7 Availability)

One of the best things about AI chatbots and virtual assistants is that they’re always on. You don’t have to worry about customer queries piling up overnight or during weekends, AI is always there, instantly answering common questions like checking order status or FAQs.

From what I’ve seen, customers love instant help. In fact, research by Dashly shows that 80% of consumers will use a chatbot, as long as they can easily switch to a human agent when needed.

2. Saving Costs and Boosting Efficiency

If I’m being honest, automating customer inquiries is one of the smartest business moves you can make. AI handles repetitive tasks effortlessly, reducing the need for a large support team. This means big cost savings.

For example, Gartner predicts conversational AI solutions will reduce global agent labor costs by $80 billion by 2026.

In an actual OpenAI-backed use case, one company reduced its cost-per-ticket from $40 to $8, a huge 80% drop!

This lets your human agents focus on more complex, high-value issues, improving overall support team efficiency.

3. Happier Customers Through Better Experiences

Here’s something I really love about AI: it makes customers happier by resolving issues faster and providing personalized interactions.

AI chatbots can pull up customer information, like previous interactions or account details, to deliver custom responses.

IBM’s 2023 research shows that 65% of service leaders expect higher customer satisfaction thanks to generative AI.

Practically speaking, AI keeps context in mind and follows your brand guidelines, so every customer gets consistent, relevant support.

In one example, Octopus Energy saw an 18% increase in customer satisfaction just by using AI to draft email replies. If you're curious to try something similar, our Free AI Email Writer can help you craft fast, on-brand replies for your own support team.

Even banks like Spuerkeess found success: 85% of their customers engaged positively with AI-driven product suggestions, which is how much customers love personalized support.

4. Empowering Agents for Higher Productivity

AI doesn’t just make customers happy, it empowers your support agents too. By managing routine queries, AI frees your team to focus on more complex customer issues.

Instead of being bogged down by repetitive emails or basic questions, agents can focus on high-value interactions. 

Gianna Maderis, chief customer experience officer at Zendesk, mentioned that their Support team saves as much as 220 agent-hours per month just by using AI for ticket triage.

5. Personalizing Support and Gaining Deeper Insights

AI makes customer support feel more personal. It gives agents helpful details, like past orders or previous chats, right when they need them. Chatbots can also use this info to respond in a more relevant, human-like way.

If you're looking to improve this even further, here are 6 Ways to Make Your Chatbot Sound More Human.

In addition, many teams now use chatbot surveys to collect instant feedback after a conversation. These short, automated check-ins help measure customer satisfaction and reveal how well your support is performing.

AI also analyzes these responses, along with other support data, to identify common issues, sentiment patterns, and workflow bottlenecks. This means you can keep improving your strategy based on real customer insights.

Personally, I love this; having a clear understanding of customer needs helps you improve the support experience. Gartner even predicts that "agentic AI" will soon handle up to 80% of standard service requests entirely on its own.

How AI Works in Customer Support (With Examples)

AI is working behind the scenes in many parts of customer support today, making service faster, more personalized, and more efficient.

Here’s a simple breakdown of how it’s used and how it actually works:

1. AI Chatbots and Virtual Assistants

One of the most common uses of AI is through chatbots, those little chat windows you see on websites or in apps. These are powered by AI that can understand and respond to your questions in real time.

How It Works:

• The customer types or speaks a question like “Where’s my order?”
• AI uses natural language processing (NLP) to understand the message.
• It figures out the intent (e.g., "order tracking") and then:
  
  • Fetches an answer from a help center or knowledge base, or
  • Generates a fresh reply using a large language model (LLM) like GPT-4o.

Some advanced chatbots also use something called retrieval-augmented generation (RAG). This means the AI looks through a database of company documents, pulls out the most relevant ones, and summarizes the answer for the customer in its own words.

Even better? AI Chatbots like LiveChatAI can now take action, for example:

• Book a meeting,
• Reset a password,
• Cancel an order, just by connecting to your backend systems through APIs.

Here, you can see an example from LiveChatAI;

2. Ticket Triage and Workflow Automation

When a customer sends an email or submits a ticket, AI helps classify and route it to the right team, instantly.

How It Works:

• AI scans the message, figures out the topic (billing, technical issue, etc.).
• It assigns priority based on urgency and even detects emotional tone.
  
  • For example, angry complaints can be auto-escalated to a senior agent.
• It forwards the ticket to the right department or person, so no manual sorting is needed.

After conversations, AI can also:

• Summarizes the interaction,
• Highlights any unresolved issues,
• Suggests what to do next.

3. Real-Time Agent Assistance (AI Copilots)

AI doesn’t just help customers, it also supports your agents while they’re chatting or on a call.

How It Works:

• AI listens to the conversation in real-time.
• It suggests:
  
  • Articles to share,
  • Ready-to-send reply templates,
  • The next best action to take.

✳️ Example: Zendesk’s AI Copilot gives agents proactive guidance during live chats, improving speed and accuracy.

In voice calls, AI tools can:

• Transcribe the call as it happens,
• Highlight key points or customer preferences,
• Help agents mention the right products or policies at the right time.

4. Smart Search and Personalized Self-Service

When a customer visits your help center or FAQ page, AI makes the search smarter and more useful.

How It Works:

• Instead of keyword matching (“refund”), AI understands the full question (“How do I get my money back?”).
• It uses vector search and LLMs to find and display the most relevant article or answer.
• Some AI systems even write the answer themselves, on the fly.

Plus, AI can tailor support content and product recommendations based on:

• A user’s past activity,
• Location,
• Purchase history, and more.

5. How It All Works Together (The Workflow of AI in Customer Support)

Let’s put it all together. Here’s what a typical AI-powered support process looks like:

1. A customer reaches out via chat, email or phone.
2. AI analyzes the message to understand the topic, urgency and tone.
3. Based on that:
   
   • It answers automatically,
   • Suggests answers to a human agent or
   • Routes the ticket to the right team.
4. If connected to other tools (like your CRM or order system), the AI can:
   
   • Look up order history,
   • Update customer details,
   • Or trigger automated workflows.
5. After that the AI may:
   
   • Summarize the case,
   • Tag it with keywords,
   • Or recommend next steps.

➡️ Example: MavenAGI built an AI support agent using GPT-4. It was trained on the company’s help docs, connected to their CRM, and could answer 93% of customer questions on its own. It also reduced resolution times by 60% since it could take real action and not just answer questions.

How to Use AI to Improve Customer Support (Use Cases)

In practical terms, companies implement AI in support through specific applications. Here are some common use cases:

1. Automating FAQs and Chat Support

A common and effective way to implement AI in customer support is by using chatbots on your website or app to handle frequently asked questions. 

Think of it like this: customers often have similar, routine questions about orders, shipping, returns, or account management. AI chatbots can instantly answer these queries, making the whole experience seamless.

⚡ For instance, airlines like Delta use chatbots for quick responses on typical traveler questions, like checking flight statuses or baggage rules.

Similarly, fashion retailers such as H&M saw reply times improve by 70% just by integrating AI chatbots to answer questions about sizing and products. 

These bots can effortlessly handle thousands of chats simultaneously, ensuring your customers get swift assistance even during busy periods.

2. Enhancing Self-Service Knowledge Bases

Integrating AI into your help center or knowledge base means customers can simply type their question naturally (like, "How do I reset my password?") and instantly receive the right help article or even a short, generated response.

⚡ Expedia, for instance, uses ChatGPT in its mobile app to chat conversationally with customers about trip planning, suggesting hotels and activities effortlessly.

This approach feels friendly and interactive, giving your customers an easier path to find answers themselves.

3. Automating Email and Ticket Responses

Generative AI can be a fantastic helper when handling incoming customer emails or support tickets. It can read a customer's message, check relevant company data, and draft a personalized initial reply.

⚡ A great example here is Octopus Energy, which started using AI to draft support emails and quickly saw an 18% increase in customer satisfaction. 

This means your agents spend less time crafting repetitive replies and more time addressing complex, valuable issues.

4. Upgrading Voice Assistants and IVR Systems

Traditional voice systems can be frustrating (think endless button pressing!). AI-powered voice assistants use advanced speech recognition and language models to understand natural spoken questions, providing smoother phone interactions.

⚡ In banking, AI voice assistants are already helping customers with complex requests like "What was my last mortgage payment?" without human intervention. 

Similarly, industries like utilities and healthcare use AI voice bots for routine tasks like bill inquiries and appointment scheduling.

5. Improving Ticket Triage and Routing

AI can automatically analyze incoming support tickets and categorize them (like technical issues, billing queries, or sales questions), instantly routing them to the correct team or giving them the right priority.

This ensures urgent issues get immediate attention and stops problems from landing on the wrong desk. Agents spend less time sorting tickets and more time solving customer problems directly.

6. Empowering Your Agents with AI Assistance

AI can dramatically boost your agents’ productivity by assisting them behind the scenes. 

⚡ For example, it can summarize lengthy conversations for quick manager review, detect sentiment in customer emails to flag unhappy customers immediately, or suggest relevant knowledge base articles during an active chat session.

Some companies even build "AI co-pilots" for agents. Zendesk’s AI co-pilot, for example, listens in on conversations and instantly suggests helpful responses, turning agents into supervisors who oversee AI-driven recommendations rather than doing everything manually.

7. Providing Proactive Support

AI can keep an eye on how customers interact with your services and reach out before they even ask for help. Imagine a telecom company spotting network issues and letting customers know before they have to call in, or an online store suggesting similar items when a favorite product is out of stock.

Though still in the early stages, proactive support using AI is already being piloted and shows huge potential for anticipating and addressing customer needs before they become issues.

8. Gaining Deeper Analytics and Insights

Finally, AI helps behind the scenes by analyzing customer support data. It clusters tickets to find new patterns, forecasts future ticket volumes, and even identifies hidden issues your agents may have overlooked.

These insights are incredibly valuable, enabling continuous improvement in products and customer support processes far beyond individual interactions.

In practice, many companies combine multiple use cases. For example, LiveChatAI – an AI agent builder, handles both live chat and WhatsApp support. LiveChatAI reports that LCAI now automatically answers 70% of customer inquiries, helping clients manage large support volumes. 

Similarly, SK Telecom in Korea uses Claude on AWS to power both chat and voice support across millions of users, improving response quality by 34% compared to their old system.

In another case, Unity Technologies deployed an AI agent trained on its help articles; the agent deflected 8,000 tickets, saving $1.3 million in support costs. 

Real-world implementations show AI’s effectiveness in customer support:

• Sephora: 11% increase in conversion rates with AI recommendations, better shopping experience.
• Bank of America’s Erica: 2 billion interactions, 98% of queries resolved in 44 seconds, 56 million monthly engagements, scalability.
• Yum! Brands: 10-15% faster order processing, 20% less order mistakes, plans to expand to 500 locations by mid-2025, and operational efficiency.
• Deutsche Telekom: Unified customer service across 11 countries with 41,000 agents, 245 million customers, using AI for faster responses and predictive needs, and scalability.

✨ These examples from various industries show AI’s versatility and effectiveness in customer support.  If you’d like to explore more real-world use cases, check out our blog on 6 Best Examples of Conversational AI in Different Industries.

Which Industries Benefit the Most from AI in Customer Support?

If you’re wondering if your industry can benefit from AI in customer support, the answer is probably yes, especially if you have high customer volumes or complex queries. But from my experience, there are a few sectors where AI really shines:

🛍️ Retail & E-commerce

If you have an online store you know how repetitive product and order related questions can be. AI chatbots are a lifesaver here, quickly handling questions about stock availability, order tracking, returns and product specifics.

For example, global brands like H&M already use generative AI chatbots to accelerate responses dramatically.

E-commerce platforms also use AI for innovative features like virtual try-ons (think Google’s "AI try-on" for clothing), interactive shopping assistants, and personalized product recommendations.

Not only does AI help with peak shopping seasons but it also boosts sales and keeps your customers loyal.

✈️ Travel & Hospitality

If you’re in travel or hospitality, you probably deal with countless routine inquiries daily.

Airlines like Delta use chatbots to help customers check flights, baggage policies or check-in procedures.

Booking platforms like Priceline integrate conversational ChatGPT-style assistants (Penny) into their apps, offering friendly, natural travel planning experiences.

Cruise lines and hotels use chatbots to handle common tasks like reservations and FAQs. In short, AI can reduce the workload on your human agents so they can focus on more personalized support.

📱 Telecommunications

Telecom providers have massive customer bases so customers have to wait for ages. AI can make this scenario much better.

Take SK Telecom in Korea for example: they adopted an AI-powered customer support system specifically trained for the Korean language.

This AI solution improved their support quality by handling over a third more high-quality customer responses. AI chat and voice bots can handle routine questions (“How can I change my phone plan?”) and escalate complex issues to humans, so customers are happier and agents are less overwhelmed.

💳 Financial Services & Banking

If you’re in finance or banking, you know how important fast and reliable customer service is. Banks and insurance companies increasingly use AI assistants for account inquiries, transaction details, loan eligibility, or even personalized product recommendations.

A great example is Spuerkeess bank in Europe: their AI system analyzes a customer’s profile and recommends suitable financial products. 85% of their customers followed through on these personalized suggestions.

AI also handles basic queries, so your human agents can focus on deeper conversations. 

🏥 Healthcare & Insurance

AI can significantly simplify routine interactions within healthcare. Chatbots can quickly triage patient queries like symptoms or appointment scheduling, offering general guidance instantly.

Dental provider SmileDirectClub, for example, uses AI to automatically listen to and summarize patient calls, saving their agents valuable time.

AI can simplify routine interactions in healthcare. Healthcare chatbots can quickly triage patient queries like symptoms or appointment scheduling and offer general guidance instantly. 

Insurance providers similarly use AI to answer policy-related questions and help manage claims. While regulatory considerations (such as privacy and accuracy) make things a little more complicated here, the efficiency gains and cost savings from automating routine tasks remain significant. 

💻 SaaS & Technology Companies

In the tech and SaaS world, technical support questions about APIs, coding, configurations or troubleshooting can overwhelm your support team.

Thankfully, B2B chatbots can instantly reference extensive knowledge bases, suggest code snippets, or escalate genuinely complicated issues.

For example, in the image below, you can see Popupsmart's intelligent chatbot LiveChatAI answering product questions in seconds and escalating complex issues to experts when needed.

⚡ Utilities & Energy

Even traditional sectors like utilities, electricity, water and gas benefit from AI. AI chatbots can handle tasks like outage reporting, billing inquiries or meter-reading questions.

Voicebots are also useful; customers can report outages by simply speaking a few words (“Say ‘power cut’ to report an outage”). The large volume of routine interactions makes this industry particularly suited to AI solutions.

What is the Future of AI in Customer Support? 

If you’re still wondering if AI is worth investing in for customer support let me say this: not only is it already working across industries but it’s just getting started. From what I’ve seen and what experts are predicting the future of AI in support is exciting and inevitable.

Here’s what’s coming your way:

🚀 Near-Total AI Adoption Is Around the Corner

We’re moving toward a world where almost every support interaction involves AI in some form. In fact, Zendesk’s CEO recently suggested that all customer service will soon include AI touchpoints. Once AI matures further, up to 80% of support issues can be handled without any human stepping in.

If that sounds bold, consider this:

• A Zendesk survey found 70% of CX leaders plan to integrate generative AI across multiple support areas within just two years.
• 64% are increasing their AI budgets to make that happen.
• And the customer experience tech market itself is growing at ~16% annually through 2030, largely because of AI tools.

So if you're thinking about AI, now’s the time to explore, not later.

🧠 The Rise of Agentic (Autonomous) AI

The next leap is agentic AI, basically, fully autonomous AI agents that go beyond chatting. These systems will not only understand and answer questions but also take actions on your behalf.

Gartner believes that by 2029, these agents will autonomously resolve 80% of standard customer service queries, planning, scheduling, and problem-solving without human oversight.

As Gartner analyst Daniel O’Sullivan put it,

Harvard Business Review even imagines a future where AI can help plan your next trip, act as a virtual caregiver, or manage your inventory, all without you lifting a finger.

In short, support will shift from being reactive (answering questions) to proactive and predictive, where AI can anticipate needs before they’re even voiced.

📈 An Exploding Market, Open to All

The market for AI in support is booming. Just take chatbots: their market size is expected to triple from $15.6 billion in 2024 to $46.6 billion by 2029.

(image source)

At the same time, the cost of implementing AI tools is dropping, making them more accessible even for small and mid-sized businesses. And with nearly every major support platform adding some form of AI “copilot” by mid-2025, it’s clear the tech is going mainstream, fast.

🤖 AI That’s More Human (and Multimodal)

Future AI tools will be far more advanced than today’s systems. We're already seeing:

• Larger context windows (so AI remembers more of the conversation),
• Better accuracy and reasoning (like with Anthropic’s Claude 3.0),
• Multimodal capabilities, meaning AI can analyze images, text, and even voice in real-time.

That means support agents, or even your customers, could show a photo of a broken product, and the AI could instantly understand and respond. Voice-based bots will also become more natural, empathetic, and multilingual.

SK Telecom, for example, already emphasizes the importance of cultural nuance in AI conversations. And Zendesk found that half of customers now believe AI agents are capable of showing empathy. 

That’s a big shift, and one that will continue as AI becomes more conversational and emotionally aware.

🧑‍💼 Human + AI: A Powerful Partnership

Despite all the automation, I don’t believe AI will replace support agents entirely. Instead, it’s going to elevate them.  If you’re curious, our blog on How AI Chatbots Enhance Human Agents explains exactly why I believe that.

In the future, agents will supervise and collaborate with AI, stepping in for complex, emotional, or sensitive issues, while AI handles repetitive tasks and prep work. 

We’ll also need to rethink how we train support teams. It won’t just be about answering tickets, it’ll be about knowing how to work alongside bots effectively. To help with that shift, we’ve put together a list of essential live chat skills every agent should develop in an AI-powered support environment.

⚠️ Trust, Safety & Ethics Matter More Than Ever

Of course, with all this advancement comes new responsibility. Companies will need to ensure their AI doesn’t go off-script, share incorrect information, or mishandle sensitive data.

That’s why some, like Tidio, have chosen models like Claude specifically because of their built-in safety layers. And it's why regulations around transparency (e.g., letting users know they’re chatting with AI), data protection, and ethical AI use will continue to evolve.

🔮 A Smarter, More Supportive Future

To sum it up: the future of AI in customer support is one where almost every company, large or small, will rely on smart, human-like assistants to handle most customer needs. AI will take care of the routine, agents will evolve into experts and mentors, and support will become faster, more personalized, and more proactive than ever before.

AI Chatbots for Customer Support: How They’re Evolving into Full AI Agents

If you’ve used rule-based chatbots in the past, you know they weren’t always impressive. The earliest versions could only follow rigid, rule-based scripts, and if you asked anything outside the expected flow, you’d hit a dead end fast.

But today’s AI-powered chatbots? They’re on a completely different level. If you’re not sure how they compare, take a look at our breakdown of the key differences between rule-based and AI chatbots.

From Basic Scripts to Real Understanding

The first big upgrade came with machine learning (ML) and natural language processing (NLP), allowing chatbots to understand free-form text. That made them a lot more flexible, but even then, they still struggled with unfamiliar questions. This gap, often called the “last-mile problem,” limited how helpful they could really be.

That all changed with the rise of large language models (LLMs) like GPT-4o. According to OpenAI, these models offer “a better understanding of queries and reasoning capabilities,” helping solve the last-mile challenge that older bots couldn’t overcome.

What Makes Today’s AI Agents Different?

Modern AI chatbots are evolving into something more powerful: AI agents. These systems are built on real customer support interactions and trained to understand the full context of a conversation, not just keywords.

For example:

• Zendesk reports that its newest AI agents, trained on real support transcripts, can now automate up to 80% of support tickets.
• Tidio’s Claude-powered agent doesn’t just chat, it summarizes the conversation, triggers backend workflows, and handles tasks behind the scenes.
• LiveChatAI's GPT-4o powered AI agent is used not only for chat, but also for advanced AI actions to effortlessly retrieve real-time data from Shopify, Google Sheets or other external APIs.

Enter: Agentic AI

Gartner calls this new generation agentic AI, autonomous systems that don’t just respond, but actually perform service tasks end-to-end. And we’re not talking about the distant future: by 2029, Gartner predicts these agents will manage 80% of standard customer service queries without human help.

We’re already seeing it in action:

• Chatbase, for instance, uses GPT o3 to answer support questions and execute actions like issuing refunds directly through a company’s CRM.
• Lyro, an AI agent from Tidio powered by Anthropic’s Claude, automates 71% of all customer inquiries across both live chat and email.

That’s not just support automation, it’s intelligent task execution.

The Rise of Truly Human-Like Agents

These AI agents are also becoming more human, not just in how they speak, but in how they behave.

They can:

• Detect when a customer is frustrated and route the chat to a human agent.
• Proactively follow up after a conversation to ensure the issue is resolved.
• Learn from past interactions to personalize future support.

According to Harvard Business Review, AI agents will soon be able to take on tasks like trip planning, inventory management, and even acting as virtual assistants, and this same level of autonomy is making its way into customer support.

How LLMs Are Powering Customer Support in 2025

In 2025, large language models (LLMs) are at the heart of customer support transformation.

Whether you’re running an e-commerce business, managing a SaaS support team, or navigating customer queries in highly regulated industries, there’s a good chance you’re already using, or thinking about using, models like Claude, GPT-4o, or Grok.

These models don’t just respond to tickets; they automate resolution, assist agents live, and even take proactive actions. 

Let’s look at real-world examples of how these models are being used today 🔽

🤖 Claude by Anthropic: Enterprise-Grade Support at Scale

If you’re looking for consistency, safety, and high-quality automation, Claude is likely on your radar. Built with strong reasoning skills and a focus on aligned behavior, it’s become a go-to for companies in complex, high-volume environments.

Here are a few standout implementations:

✅ Intercom’s Fin chatbot (built on Claude)

– Started at 51% automation, now resolves up to 86% of support queries
– Works in 45+ languages
– Helped cut response times from 30 minutes to seconds

✅ Kodif’s Claude-powered agents
– Used by Dollar Shave Club (65% ticket resolution)
– Trust Wallet (90% automation)
– Halo Collar (75% resolution)
– Handles not just FAQs but cancellations and upsells too

✅ Assembled’s “Assist” copilot
– Used by Stripe, Robinhood, Warner Bros.
– Resolves 50%+ of support cases
– Boosts satisfaction by 20%, increases agent capacity by 30%
– Switched fully to Claude in under 20 minutes after another provider failed

✅ Coinbase
– Deploys Claude across 100+ countries
– Handles thousands of customer queries per hour
– Runs via AWS and Google Vertex AI to ensure high uptime

Claude doesn’t just answer questions, it helps teams scale fast, stay consistent, and deliver better customer experiences.

If you’re exploring Claude for your business, you can quickly estimate usage costs with our Claude pricing calculator to see what fits your needs.

🧠 GPT-4o by OpenAI

Released in April 2024, GPT-4o changed the game for AI in customer support. It's fast, supports text, vision, and voice, and now powers many of the most advanced support systems in 2025.

Here are some real-world examples:

✅ Nationwide (UK)
– Uses GPT-4o via Azure to draft customer letters
– Cut average response time from 45 minutes to 10–15 minutes
– AI handles formatting, tone, and personalization, agents just review and send

✅ Pegasus Airlines
– Built a virtual travel assistant with GPT-4o
– Doubled customer satisfaction scores
– Increased agent satisfaction by 20%
– Provides instant help with bookings, policies, and HR questions

✅ Meesho (India)
– Uses GPT-4o to support buyers and sellers at scale
– CSAT scores rose by 25%
– Support volume capacity increased by 40%
– Achieved this without expanding the team

✅ RepsMate (Contact Center Provider)
– Created a GPT-4o-powered assistant for support agents
– Reduced need for supervisor intervention by 50%
– Junior agents resolved queries faster, improving overall team performance

✅ Montgomery County (U.S.)
– Launched "Monty 2.0," a public service chatbot powered by GPT-4o
– Handles 20,000+ citizen conversations
– Covers 3,000+ topics in 140 languages
– Early results show a 50% satisfaction rate and growing

If your team needs speed, multilingual support, and creative, human-like responses across many topics, GPT-4o is one of the best models to consider. 

Curious about how much it costs to use GPT models? You can explore and compare prices with these free tools:

• Open AI GPT-4o Pricing Calculator
• GPT‑4.1 Pricing Calculator
• OpenAI o3 Pricing Calculator - and more.

🧪 Grok by xAI: A Promising Contender

Grok, the LLM developed by Elon Musk’s xAI, launched in late 2024 and is beginning to make its way into customer support in 2025. While it’s still early, the signs are promising.

• In a retail trial, a Grok-powered bot resolved 80% of support queries, helping the brand cut costs by 30% and increase sales by 25%. The bot handled tens of thousands of chats each month with a 90% satisfaction rate.
• xAI is now packaging Grok as a plug-and-play e-commerce chatbot, offering multilingual support, real-time answers, and easy web integration.

While Grok is mostly used on X.com (formerly Twitter), its API availability in 2025 means more businesses can start testing it. Its personality-driven tone and web browsing features could make it especially useful for real-time Q&A and dynamic support.

Best AI Tools for Customer Support (2025 Updated)

Below, I compare the best AI-powered customer support tools as of 2025, including advanced large language model (LLM) platforms and specialized support solutions.

These tools are characterized by their broad use cases (live chat, ticketing, agent assistance, triage, etc.), enterprise adoption, and latest capabilities (multilingual support, multimodal inputs, API integration, etc.). 

Use this up-to-date comparison to find the best solution for your customer support needs in 2025.

AI Support Implementation Roadmap: Your First 60 Days

I’ve found that the fastest wins come from a focused, two‑month sprint. 

Here’s the playbook I use with clients:

Conclusion: Why 2025 Is the Year to Act

AI in customer support is no longer a future trend, it’s a practical advantage you can act on today. The tools are ready, the impact is real, and teams across industries are already seeing faster service and better customer experiences.

Here’s how you can get started:

• Start small, move fast. Launch a focused pilot in your busiest channel. → LiveChatAI makes this easy, just upload your top 50 FAQs and test it with real users, no code needed.
• Connect the dots. Let your AI do more than chat by linking it to your CRM, order system, or booking tools. → LiveChatAI integrates directly with Shopify, Notion, and Zapier.
• Measure and improve. Watch how the bot performs, refine prompts, and adjust based on real feedback. → LiveChatAI shows you where answers need improvement so you can tweak as needed.
• Build with trust. Privacy and control matter from day one. → LiveChatAI comes with built-in security, GDPR readiness, and flexible access controls.

If you follow this 60-day roadmap, you can turn your support operation into a smarter, faster, more helpful experience for your customers.

Start your free LiveChatAI trial, load your FAQs, and let the results speak for themselves, no meetings, no code, just real answers in minutes.