AI agents in action: 5 real-world examples

Customers today expect fast, personalized support on any channel, at any time. Businesses can’t meet these demands with traditional systems alone. That’s why many are turning to autonomous AI agents like Freshdesk’s Freddy to boost speed, cut support costs, and improve satisfaction.

According to McKinsey, over 72% of companies have already deployedsome form of AI in customer operations.⁽¹⁾ But not all solutions are equal. There’s plenty of noise in the market, and it’s easy to confuse basic bots with true AI agents that solve real problems.

We’ll show you five real-world examples of AI agents in action, across industries like healthcare, travel, and e-commerce. These aren’t hypotheticals. They’re live deployments showing how intelligent automation delivers results when done right.

Understanding AI agents

AI agents go far beyond traditional chatbots. Unlike basic bots that follow decision trees, AI agents understand user intent, learn from context, and independently take actions across your business systems.

Here’s what sets them apart:

• Understand natural language, even if phrased differently

• Retrieve answers from multiple internal systems

• Make decisions using business logic

• Complete tasks like processing refunds or updating records

• Learn continuously from every interaction

The defining trait of an AI agent is autonomy. It answers, but more importantly, it acts. Whether that’s checking shipment status or resolving a billing issue, AI agents work like digital co-workers that get things done.

How do AI Agents work?

AI agents operate by combining multiple technologies: natural language processing (NLP), business rule engines, workflow automation, and real-time integrations.

When a customer reaches out, the agent:

• Understands the query using natural language understanding

• Pulls data from your knowledge base, CRM, or backend systems

• Takes action—like modifying an order, sending a form, or raising a ticket

• Escalates to a human agent if needed

• Learns from past interactions to improve future responses

The result? Support that feels human, but responds with machine speed and scale.

Types of AI agents

AI agents are often specialized for different roles within a support team. The most effective setups combine these types to cover a wide range of customer needs.

These roles often overlap. A mature AI deployment uses multiple agent types to build a seamless, scalable support system.

AI agents in action: 5 real-world examples

Here's how companies are using AI agents to get work done:

1. E-commerce: Wayfair's Order Lifecycle Assistant

Wayfair introduced an AI agent called Agent Co-Pilot to enhance post-purchase support.

It works alongside digital sales reps and helps customers by:

• Suggesting add-on items

• Providing product specifications instantly

• Explaining return and refund policies

• Clarifying shipping timelines

• Generating personalized replies based on past chats

With this setup, Wayfair reduced handling time by 10%. This is a clear example of AI agents improving customer experience in e-commerce.

2. Healthcare: Cleveland Clinic's Patient Support Agent

Cleveland Clinic launched a patient-facing AI agent in early 2025 to streamline non-urgent communication.

The agent helps patients:

• Schedule appointments based on specialty and insurance

• Manage prescriptions and send refill reminders

• Handle bill payments and insurance queries

• Collect pre-visit forms and medical data

The initiative aims to free up staff time while enhancing patient engagement outside clinic visits.

3. Travel: KLM's Disruption Management Agent

KLM’s AI agent handles high-stress disruption scenarios like delays and cancellations.

It automatically:

• Rebooks affected passengers

• Books hotel stays and sends vouchers

• Notifies customers about new flight times

• Responds to questions about layovers and destination rules

• Processes compensation claims based on eligibility

This has helped KLM scale rebooking during weather events while reducing costs and improving loyalty.

4. Software: Adobe's Product Support Specialist

Adobe embedded an AI assistant into its Experience Platform to reduce reliance on human agents.

Its features include:

• Real-time diagnostics using internal documentation

• Step-by-step product tutorials

• Contextual ticket submission with insights

• Live status updates for ongoing cases

• Linking users to forums and help docs

The goal: lower ticket volume, faster resolution, and increased product adoption.

5. Banking: Bank of America's AI Virtual Assistant

Erica is an AI agent serving 42 million users with over 2 billion interactions.

Erica helps customers:

• View balances and make transfers

• Pay bills quickly

• Track spending habits

• Set savings goals

• Book appointments

• Understand complex financial products

It’s one of the longest-standing examples of scalable, customer-friendly AI in banking.

Potential challenges in deploying AI agents

AI agents can be helpful, no doubt. But there are some natural bumps in the road. Here's what to watch for:

• Disorganized knowledge bases: AI agents rely on well-structured help docs. Many companies need to clean and organize content before seeing meaningful results.

• Overestimated expectations: AI agents won’t replace all human support. Stakeholders must be educated about realistic outcomes.

• Poor handoffs: If AI agents escalate to humans without passing context, customers may need to repeat themselves, hurting customer satisfaction.

• Outdated metrics: Traditional KPIs like call volume don’t reflect AI performance. New metrics like containment rate and escalation quality are essential.

Despite these challenges, businesses that take a phased, data-driven approach often see strong returns. The key is choosing an AI solution built for real-world support, not just scripted automation.

That’s where Freddy AI Agent from Freshdesk comes in. Built for speed, context, and scale, Freddy helps support teams deliver 24/7 personalized assistance while keeping operations efficient.

How Freddy AI Agent helps you scale support without compromise

Freddy AI Agent is Freshdesk’s autonomous support assistant built to handle repetitive tasks, 24/7.

With Freddy, you get:

• Instant configuration and deployment (in minutes, not weeks)

• Accurate responses backed by your knowledge base

• Multilingual support with context-aware conversations

• Seamless integrations with your backend tools

• Continuous learning from customer interactions

• Rich analytics to track performance and find gaps

Freshdesk customers have seen:

• 93% reduction in resolution time

• 10x more tickets handled without extra agents

Amanda Pope from Bchex says, “The best part of the Freddy AI Agent is how quickly it can be deployed. If you have your FAQs and data ready, you can have a new AI agent live within minutes.” -Source

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Business benefits of AI agents

Successful AI agent adoption starts with clearly defined use cases and expands gradually based on real outcomes. The most effective teams blend automation with human support: using AI agents to reduce workload, speed up resolution, and drive measurable cost efficiency without compromising on service quality.

When implemented thoughtfully, AI agents offer:

• Lower costs with higher service quality

• Round-the-clock support without hiring more staff

• Flexible scaling during demand spikes

• More meaningful work for human agents

• Deeper insights from AI-analyzed interactions

The most successful implementations are those that treat AI agents as evolving systems, continuously refining them based on performance metrics and customer feedback.

Transform your customer experience with AI agents

If you're looking to improve customer experience while keeping operations efficient, AI agents are a practical way forward. Freddy AI Agent from Freshdesk helps your team respond faster, resolve issues accurately, and stay consistent across every channel.

Want to see how it works?

Schedule your personalized demo today!