We’re currently seeing an increasing number of companies investing in agentic AI, a new class of AI-enabled solutions that can perform tasks without human supervision, make decisions, and learn from past experiences. Notably, customer service is one of the fastest-growing areas of AI agents adoption.
Companies increasingly deploy AI agents to serve as virtual customer service reps who can independently handle a wide range of tasks, from inputting customer data into enterprise systems to providing customers with real-time order status and guiding them through resolving issues. The use of customer support AI agents is likely to accelerate in the future, with Gartner predicting that by 2029, 80% of customer service issues will be resolved by agentic AI.
In this article, AI agent experts highlight the use cases and advantages of agentic AI for customer service and provide tips for streamlining its implementation.
How AI agents transform customer service
Here are the key ways an agentic AI solution can help a company enhance customer service operations, supported by impactful real-life examples:
- Automating customer conversations
Since AI agents are built with the help of large language models and trained on vast amounts of data, they excel at understanding natural language, comprehending the context of conversations, and identifying intent behind the customers’ queries. Eventually, this enables AI agents to provide swift and relevant answers to even complex and nuanced customer questions, therefore helping companies enhance customer satisfaction and alleviate human agents from excessive workloads.
One example of successful AI agent implementation for communicating with customers is Eneco, a Belgian solar and wind energy company that decided to implement an AI agent complemented with natural language and conversational language understanding models. The solution can understand a broad range of questions without asking customers to rephrase their prompts. If an inquiry remains unclear, the agent can direct the customer to an online chat with a human rep, while providing the employee with a brief summary of their conversation with the customer.
As a result, Eneco achieved a customer intent recognition score of over 95% and increased the volume of automated customer conversations to 67% (compared to 40% when the company previously used an AI chatbot). Now, the AI agent successfully handles more than 24,000 chats per month, while the bot could only process 10,000 chats.
- Resolving customer issues across multiple channels
Since AI agents can interact with various software systems, collaborate with other digital agents, and execute multi-stage workflows, they can troubleshoot a wide range of customer issues typically requiring human involvement. This way, by automating troubleshooting processes with AI agents, companies can not only enhance customer satisfaction but also reduce operational and labor costs.
The example of Tidio, a US-based provider of a comprehensive customer service platform, shows the usefulness of AI agents for resolving customer issues. As the company grew, its support agents spent excessive time addressing recurring customer inquiries, including login issues and promo code failures, which often required taking manual actions for resolution. Tidio decided to implement an AI agent to automate customer communication and alleviate excessive workloads on customer service teams.
Today, the company’s AI agent can process customer inquiries from the support chat within 5-20 seconds to answer frequently asked questions, as well as email inquiries, typically associated with more complex issues. Agentic AI has already helped Tidio resolve over 2 million customer inquiries, resulting in 71% automation of the company’s customer support across live chat and email channels.
- Helping human agents provide better support
Some customer inquiries can still require human involvement to be resolved, and with the help of AI agents, members of customer service teams can do it faster and more accurately. Agentic AI can quickly route issues and complaints to relevant specialists, provide them with an overview of previous customer conversations, automate the retrieval of relevant help center content, and provide other assistance required for human reps to deliver more instant and useful responses.
It is worth looking at the example of Finnair, a Finland-based airline, to understand how AI agents can assist support specialists. 80% of cases at the company are resolved by AI, but some are routed to their human counterparts, if there is a specific need for customers to speak with employees. When a human rep receives an issue, its virtual colleague provides him or her with a summary of associated customer conversations. AI also automatically submits relevant information from corporate knowledge bases, such as specific rules for flights or pet travel policies, so a support agent doesn’t need to look for it manually.
Setting up AI-enabled agents as assistants to support specialists not only helped Finnair improve the quality of customer support but also significantly shortened the onboarding process for new contact center employees, who no longer need to search for answers across multiple corporate systems. In numerical terms, agentic AI enabled Finnair to reduce its complex year-long onboarding process by 25%.
How to ensure successful agentic AI implementation
To ensure frictionless and impactful agentic AI implementation that brings the expected results, companies need to focus on the following aspects:
Software integration
To function efficiently, an AI agent needs to exchange data and interact seamlessly with enterprise customer service software, which requires the enablement of seamless integration between AI agents and other systems. To streamline the integration process, companies should prioritize agentic AI platforms offering robust integration capabilities, such as API connections and no-code integrations.
Employee training
The success of the implementation largely depends on whether human employees can effectively use AI agents to automate repetitive customer service tasks. Therefore, companies should implement comprehensive training strategies to guide employees through studying the capabilities of the new solution and increase their proficiency in agentic AI systems and tools.
Security and compliance
The majority (56%) of respondents to the 2025 Agentic AI report from UiPath stated that IT security issues are their top concern about adopting agentic AI. They also ranked ensuring the technology’s safety and compliance with ethical and regulatory guidelines as the most critical factors determining the effective implementation of agentic AI workflows.
To maintain the high level of enterprise data security when implementing AI agents, companies need to select agentic AI platforms equipped with relevant security mechanisms, such as data encryption, masking, and loss prevention or develop these mechanisms from scratch. If the company operates in a strictly regulated industry, it should also ensure that its AI toolset complies with all the relevant global or industry-specific standards.
Final thoughts
Capable of human-like intelligence, decision-making, and learning from past experiences, AI agents represent an evolutionary step in AI-driven automation. The technology has already transformed customer service for Eneco, SafetyCulture, Tidio, and hundreds of other companies across various industries.
If you plan to join the ranks of those who have already embraced AI agents and streamlined customer service with their assistance, consider consulting agentic AI experts to ensure smoother and more cost-efficient implementation. Experts can match your unique business requirements to the right AI agent tool, help create a tailored implementation strategy, and, if needed, guide you through each step of AI agent implementation.
Source: How agentic AI streamlines customer service and support
