AI Agents in Customer Service: Smarter Support with Virtual Assistants

by Lavenda Morin Atieno
Updated on : August 26, 2025

How AI Agents Deliver Smarter Customer Service Experiences in 2025

Remember when customer service meant waiting on hold or sending emails into the void? Times have changed; thanks to AI agents for customer service.

While the early automated systems successfully reduced costs and handled basic queries, their rigid, rule-based design couldn’t manage complex, context-rich conversations.

Today, AI-powered support agents are stepping in to offer faster, smarter, and more personalized support. When comparing AI agents vs chatbots, unlike old-school chatbots, these advanced AI tools learn from interactions, think, make independent decisions, and adapt to successfully meet customer needs.

With capabilities like context awareness and continuous learning, AI agents go beyond answering simple questions, they instantly solve problems and elevate the customer experience.

In this article, we’ll explore what AI agents are, how they’re changing customer service, and what’s next for these powerful tools.

What are AI agents?

AI agents are virtual assistants designed to autonomously perform tasks, make decisions, and take actions to achieve specific goals without constant human input.

AI agents are powered by AI technologies like machine learning, natural language processing (NLP), and large language models (LLMs), all trained on customer experience data.

The artificial intelligence agents range from simple rule-based bots to advanced models that learn and adapt, making them essential tools in modern digital transformation strategies.

In AI-powered customer support, these AI tools help the agents understand customer queries and respond more accurately over time. The AI agents use data from your website, documentation, and past answers to deliver real-time, accurate, and personalized support.

How do AI customer service agents work?

Ever wondered how AI agents actually perform tasks in customer service? It all comes down to two powerful components working together: AI actions and APIs.

AI actions define what the agent can do, such as summarizing text, extracting data, sending messages, or translating content. These actions drive intelligent decision-making and task execution.
APIs (Application Programming Interfaces) connect the agent to external systems like calendars, email platforms, help desk software, and databases. APIs enable seamless integration with existing tools and workflows.

Together, AI actions guide the agent’s decisions, while APIs enable it to interact with other systems and complete tasks efficiently.

This combination allows AI agents to streamline operations, speed up response times, and personalize interactions at scale, making them essential in modern intelligent systems and smart workflows.

For example:

If you give the virtual assistant agent a goal: “Schedule a meeting with the team.”

The agent uses AI actions to: Understand your request, find available time slots and draft a meeting invite.
It uses APIs to: Check your calendar and send the invite through your email or calendar app

You get a response: “Meeting scheduled for Tuesday at 10 AM.”

Why are AI agents for customer service important?

Customer expectations are rising and fast. To keep up, businesses are turning to AI-powered support agents that bring speed, intelligence, and automation to everyday customer interactions.

These smart AI tools don’t just improve service they transform how support teams work, and customers feel. Let’s explore how AI-powered customer support can take your business to the next level.

Here are some of the key benefits AI in customer service:

Offer 24/7 support availability: Operate around the clock with zero downtime to ensure customers get instant support anytime, regardless of time zone or business hours.
Adaptive, faster issue resolution: AI agents can resolve customer inquiries twice as fast as traditional methods through advanced natural language processing and intelligent automation.
Ensures consistency in responses: Deliver uniform, high-quality answers so every customer receives the same level of service.
End-to-end task execution: The AI agent can call external APIs to perform tasks like cancelling orders, checking account balances, or scheduling appointments without human input.
Higher customer service automation coverage: These virtual assistant agents can automate most routine inquiries, up-to 80%, with minimal human involvement, allowing support agents to focus on complex issues that need human empathy and problem-solving.
Reduces escalations: AI virtual assistants autonomously manage common queries, contributing to a relatively high decrease in issue escalations to human agents.
Improves support agent productivity and morale: Agents are less burdened with repetitive tasks, which helps reduce customer service burnout and turnover, and boosts overall team morale.
Compliance and accuracy: Automated handling of sensitive information minimizes human error, helping maintain regulatory compliance and data integrity.

How are artificial intelligence agents used in customer service?

AI agents can handle anything from simple tasks to complex workflows, depending on how they’re built and what tools or resources they can access.

Many work together in a system called an agentic system, where each agent handles a specific task and passes it along to the next.

Let’s explore some common use cases where virtual assistant agents are making a measurable impact.

Real-time issue resolution at all times

Waiting for help is one of the biggest frustrations for customers, and delays often lead to dissatisfaction. AI agents eliminate this pain point by offering immediate, intelligent responses around the clock.

They don’t just answer questions or track orders, they actively solve issues without needing human assistance in the following ways:

Instantly understand customer queries: AI Agents use natural language processing to detect the issue and urgency
Access live customer data: These intelligent systems have direct access to information from CRM and AI help desk tools, enabling them to provide accurate, personalized responses.
Automatically resolve common issues: AI customer service agents can autonomously resolve issues like password resets, billing inquiries, and order tracking without human intervention
Continuously learn from interactions: Every customer communication is a learning opportunity for AI agents, enabling it to adapt and improve speed, accuracy, and handling of future real-time issues.

For example, when a customer requests to cancel a subscription, the AI-powered support agents instantly checks the account status, calculates a partial refund, and completes the cancellation; all within the same chat.

This kind of real-time resolution eliminates delays and ensures the customer’s issue is handled quickly and efficiently, without human involvement.

Personalizing every customer interaction

Customers value support that feels tailored to their needs, and AI agents make this possible by delivering intelligent, context-aware experiences across every touchpoint.

They don’t just respond, they personalize every step of the journey in the following ways:

Remember past interactions: These intelligent systems learn from previous conversations and customer behavior to offer more relevant and personalized support.
Build detailed customer profiles: By analyzing purchase history, preferences, and demographics, they create rich profiles that enable proactive and targeted assistance.
Anticipate customer needs: Using predictive analytics, virtual assistant agents can adjust their tone, suggest helpful actions, and even solve problems before the customer asks.
Maintain context across channels: Whether it’s chat, email, or phone, AI-powered support agents ensure a consistent and personalized experience throughout the customer journey.

For example, Bank of America’s virtual assistant, Erica, helps users track spending habits, provides tailored banking tips, and sends proactive alerts, making financial management more customer-centric.

AI agents Bank of America — Bank of America home page

Automates repetitive and manual tasks

Handling support tickets manually can be time-consuming and prone to delays. AI agents simplify this by automatically reviewing incoming customer queries, identifying the issue type, and routing them to the correct department or team.

With customer service automation becoming central to modern support, AI virtual assistants are set to resolve 80% of customer service issues by 2029 eliminating manual sorting and speeding up resolutions.

By taking over repetitive tasks like tagging, categorizing, and prioritizing tickets, these intelligent systems free up human agents to focus on complex cases, boosting both efficiency and customer satisfaction.

Providing a smooth multilingual support

AI agents deliver seamless, real-time support across multiple languages by automatically detecting a customer’s preferred language and adapting mid-conversation.

These AI customer service agents can:

Maintain consistent brand tone across languages
Access localized knowledge bases with region-specific policies
Offer both voice and text support simultaneously

When complex issues arise, customers are either guided through real-time translation or intelligently routed to multilingual specialists for further assistance.

This multilingual customer support enables businesses to serve a global audience without requiring separate teams for each language.

For example, KLM Royal Dutch Airlines’ AI-powered platform helps customers book flights, check flight status, and receive travel advice in their native language, enhancing global engagement.

Connecting support teams to the tools they use every day

AI agents act as smart bridges between customer service and core business systems like CRM and help desk platforms. They automate the flow of information across these tools, ensuring that support agents always have access to the most current and relevant customer data.

This integration works by:

Syncing customer records automatically: AI agent tools update customer data across systems in real time, removing the need for manual input and reducing errors.
Providing instant access to customer history: They pull data like preferences and past interactions to help deliver faster, more personalized responses.
Feeding service data into analytics tools: This allows businesses to track performance, spot trends, and make smarter decisions based on real-time insights.
Automating routine support tasks: From ticket assignment to follow-ups and data entry, the virtual assistant agents handle repetitive work so human teams can focus on complex issues.

By connecting intelligent systems and streamlining workflows, AI agents ensure digital transformation of customer service into a proactive, data-driven function that supports both customer satisfaction and business growth.

Sentiment detection and feedback analysis

Advanced virtual assistant agents are designed to understand customer emotions in real time, changing how businesses manage feedback and improve service.

By examining tone, word choice, and interaction history, these systems go beyond surface-level understanding to deliver truly empathetic customer service.

They continuously monitor customer mood and feedback to guide interactions and optimize service delivery.

These intelligent agents can:

Match response tone to customer emotions
Generates sentiment reports to help teams improve their approach
Automatically flag and escalate emotional conversations to live agents when needed

Unlike traditional systems that rely on post-chat surveys, AI agents provide live emotional insight, helping businesses stay proactive, responsive, and customer-focused.

AI agents vs Chatbots: What’s the real difference?

The rise of AI has transformed how businesses interact with customers, but not all AI-powered solutions are created equal.

While traditional chatbots follow scripted responses to handle basic queries, AI agents are a major advancement in customer service, capable of making decisions, solving complex problems, and learning from each interaction to deliver smarter, more personalized support.

Below, we highlight the key distinction between an AI agent vs chatbot, showing how customer support has been transformed.

Aspects	Traditional chatbots	AI agents
Task complexity	Answers basic, scripted questions. Also gives rigid responses without personalization.	Handles complex, multi-step workflows simultaneously.
Contextual awareness	Restricted to predefined scripts and can’t recall previous conversations. Customers have to repeat previous conversations.	High memories of past interactions and always adapts based on the context and customer preferences or needs.
Actions	Primarily provides or works based on pre-defined information. When faced with anything unexpected, they often break down, leading to frustration.	Executes tasks (e.g., process refunds) independently without human agents’ intervention.
Integration	Limited or no integration with other tools or apps.	Deep, unlimited integration with third-party business systems tools.
Learning and improvement	Static, hence, requires manual updates.	Continuously learns, adapts, and optimizes based on the changes.

Use cases of AI agents in different industries

Intelligent systems are transforming how businesses operate by automating tasks, improving efficiency, and enhancing user experiences. Here’s are some applications of AI agents across various sectors:

Industries related	Use cases
Customer service	AI customer service agents automate onboarding, handle customer queries, and generate insights to support service operations.
Logistics	AI agents optimize delivery routes, track shipments, and send real-time updates to customers.
Manufacturing	In manufacturing, they monitor equipment performance, predict maintenance needs, and manage inventory levels.
Education	AI agents handle student inquiries, automate attendance, and support communication between parents, teachers, and administrators.
ITSM (IT service management)	In ITSM, virtual assistant agents autonomously manage tasks such as ticket classification, incident resolution, and system monitoring, reducing manual workload.
Banking	In banking, AI agents automate fraud detection, assist with loan applications, and deliver personalized financial advice based on user data.
Real estate	These artificial intelligent agents guide buyers through listings, answer financing questions, and schedule property viewings.
Healthcare	They handle appointment scheduling, triage support, basic health-related questions, and direct patients to appropriate departments, freeing up medical staff for more critical tasks.

What are the challenges of customer service AI agents?

As AI agents become more integrated into business workflows, it’s essential to recognize the complexities and constraints that come with them.

Being aware of these factors helps organizations make informed decisions, refine their implementation strategies, and unlock the full potential of AI-driven support:

Data privacy and security: The AI customer service agents handle sensitive client data, so businesses must follow strict data protection rules and ensure secure storage and usage.
Initial setup effort: Setting up these virtual assistant agents takes time, money, and planning. It involves training the system with quality data and integrating it into existing tools.
Handling complex queries: Intelligent agent systems are great with simple questions but may struggle with complicated or emotional issues. These should be passed to human agents smoothly.
Continuous updates: AI agents need regular updates and training to stay accurate and useful as customer needs and products change.

Redefining the future of customer service with AI agents

As customer expectations evolve, businesses must adopt innovative tools to stay competitive and achieve customer service excellence.

From automating routine inquiries to enabling 24/7 availability, streamlining support, improving response times, and delivering personalized experiences at scale, AI agents are at the forefront of this transformation in customer service automation.

With powerful AI customer service software like BoldDesk AI Agent, you can automate routine tasks, reduce support costs, and respond to customers up to 3x faster than traditional chatbots.

Ready to revolutionize your customer service excellence? Contact us to start a 15-day free trial of BoldDesk AI Agent and discover how AI can elevate your customer experience and drive digital transformation.

Do you have any thoughts or questions about AI agents for customer service? Leave a comment in the feedback section and share your insights with us!

Related articles

Frequently Asked Questions (FAQs)

Will AI agents replace human customer service representatives?

No. These virtual assistant agents are designed to handle routine and repetitive tasks, freeing human agents to focus on complex, high-value interactions that require empathy and problem-solving skills that AI doesn’t have.

What is an AI agent in customer service?

An AI agent in customer service is an autonomous AI-powered system, designed to interact with customers and take actions to achieve specific goals. It understands customer queries, interprets context, and provides accurate, real-time support.

These agents can perform a wide range of tasks, such as answering frequently asked questions, resolving complex issues, and routing requests to the appropriate departments, often without the need for human intervention.

What happens if an AI agent cannot solve a problem?

With the right customer service software, the issue is seamlessly escalated to a human agent by automatically creating a ticket. All relevant conversation history and context are added to the ticket to ensure a smooth transition.

What types of AI agents are used in customer service?

Virtual assistant agents interact with their operational context to accomplish specific tasks, but the nature and complexity of the information they process depend on the type of agent involved. They include:

Multi-agent system: Multiple AI tools (Copilot, Agent, Actions) work together to streamline support.
Learning agent: Improves over time by analyzing ticket history, customer sentiment, and agent feedback.
Goal-based agent: Navigates customer queries by prioritizing resolution paths that align with defined support goals (e.g., reducing response time).
Utility-based agent: Optimizes customer support decisions by balancing speed, accuracy, and customer satisfaction to deliver the best possible experience.

How do AI agents improve customer support?

AI agents help deliver instant, consistent responses and operate 24/7, which significantly reduces wait times.
They help businesses scale efficiently by automating routine tasks and personalizing interactions using customer data.
AI agents free up human staff to focus on more complex or sensitive issues, leading to faster resolutions, increased productivity, and a more satisfying customer experience.

How do businesses ensure a smooth handoff to human agents?

A seamless handoff happens when AI agents recognize that the issue is more complicated.
With smart routing and context-aware transitions, they escalate complex queries to human agents without losing conversation history—ensuring continuity and a smooth customer experience.