While voice assistants like Alexa and Siri have become familiar names, the next wave of AI customer service agents is more than that. They're designed to handle nuanced conversations, anticipate customer interactions, and deliver consistent, human-like support 24/7.

This has profoundly impacted customer expectations to the point where 68% of customer support teams believe AI has directly influenced them.

This blog post will help you understand the concept of an AI agent and how it improves customer service. It will also discuss real-life use cases and challenges to help you choose the perfect AI agents to provide unmatched service.

What is an AI agent?

AI agents are software programs designed to replace or augment the work of human agents. They are trained to understand the user's needs, respond to inputs, and act without human intervention.

They rely on ML and NLP to execute diverse tasks, from answering simple questions to resolving complex issues such as sentiment analysis, fraud detection and customer issue prediction.

How does an AI agent work? 

AI agents don’t just follow orders. They set tasks, determine priorities, and reprioritize tasks until the overall goal is achieved. The fundamental design of AI agents revolves around three key components: perception, decision-making and action.

Let’s understand how they work:

Perception: AI agents gather data from various sources, including customer interactions, transaction histories and social media. This helps them understand the context and nuances of customer queries.

Decision-making: The AI agent uses sophisticated machine learning models to identify patterns and make decisions based on the collected data. The agent improves decision-making by learning from past experiences and continuously refining responses.

Action: Once the decision is made, AI agents can execute tasks such as answering a customer query, processing a request, or escalating complex issues to a human agent.

How do AI agents improve customer service?

Parul Mishra, VP of product management in digital labor at IBM, says, 

“While the capabilities of AI agents across specific domains will vary depending on industries and use cases, the key point is that those agents will work in collaboration with AI assistants alongside a suite of other tools to transform a chatbot experience into a multi-dimensional system that can plan, test, write, and autonomously implement solutions.”

Here is how AI agents can improve customer service:

Faster response times

AI agents are available 24/7, ensuring customer inquiries are answered promptly, regardless of time zones or business hours. Being continuously available enables customers to meet their needs via self-service while improving satisfaction.

Personalized customer interaction

With AI entering the scene, 73% of customers feel they are treated as unique individuals in 2024, up from 39% in 2023.

This is because AI analyzes important information such as customer name, location, and past purchases in real time to tailor services to customers so that they feel valued and important.

Managing large-scale inquiries

AI agents can handle thousands of queries simultaneously without delays. They integrate with knowledge bases to provide instant and accurate information and automate routine tasks such as order tracking and password resets.

This ensures they maintain consistent service levels and enhance overall customer satisfaction.

Proactive customer support

AI customer service agents can determine the next best action for your customers by analyzing information from customers' contracts, warranties, and purchase history. For example, AI can set email alerts when it’s time to renew a subscription or when a product upgrade or discount is available.

Improved accuracy and consistency

AI agents can improve the accuracy of responses through agentic loops and human-like reasoning. This ensures consistent and accurate responses to customer queries and reduces the risk of errors.

Delivering consistent results helps build trust and confidence in the brand by meeting customer expectations.

Data-driven insights

Incorporating AI can help you gain deeper insights into every interaction to understand customer satisfaction levels. It enables you to track key metrics such as CSAT, CES, and NPS to optimize processes and proactively address customer needs.

Types of AI agents in customer service

From a support tool to a strategic game-changer, here are the most impactful ways you can use AI agents in customer service:

Chatbots

According to a study by Simplr, in 2022, chatbot usage doubled compared to 2020. This is because chatbots are fast, convenient and available 24/7.

Apart from just answering questions, chatbots can:

• Provide the most relevant information about your products and services
• Book appointments or make reservations
• Offer personalized product recommendation
• Handle refunds, product returns, and exchanges
• Guide customers to solve technical problems

Plivo CX's self-service chatbot, developed and powered by OpenAI, is available 24/7 to resolve queries instantly. With in-app customer service, customers can easily send and receive photos to report issues and queries, making the interaction much more convenient.

Voice assistants (IVR)

AI voice agents or voice bots are popular among businesses looking for additional ways to automate customer service operations. Just like chatbots, interactive voice response (IVR) can answer incoming calls, provide product/ service information, recommend relevant products, update account information and much more.

Sentiment analyzers

Sentiment analysis is a key component of speech and voice analytics that uses NLP and ML to capture customers’ emotions by analyzing vocal and speech characteristics such as pitch, tone, words, volume and other variables. 

Based on that, sentiment analyzers assign a score to each positive, neutral, or negative conversation.

Predictive AI agents

Predictive AI agents can analyze historical customer data, browsing history, and purchase patterns to predict issues and needs such as product failures, churn risks, or future purchase preferences.

Depending on the data, it can offer tailored recommendations and prevent potential problems.

Call transcribers

With real-time transcription and analysis, agents can quickly retrieve customer histories and previous interactions. 

These transcripts are especially useful for reviewing agent performance and ensuring calls adhere to regulatory requirements. Businesses can also identify recurring issues, customer preferences, or opportunities for upselling and cross-selling.

Omnichannel AI agents 

Sophisticated omnichannel platforms offer agents tools and contextual insights to effortlessly carry on a conversation across multiple channels. Although modern chatbots are more effective, they still fall short of managing all inquiries entirely. Omnichannel agents bridge this gap by facilitating seamless handoffs from self-service to live agents when necessary.

Plivo CX’s true omnichannel solution brings frequently-used communication channels, such as voice, SMS, WhatsApp, and live chat, together in a single platform, allowing agents to monitor, track, and manage customer interactions effortlessly.

Uses cases of AI agents in customer service 

Let’s have a look at how businesses worldwide are using AI agents to boost customer satisfaction and agent productivity:

Function of Beauty

This American brand uses AI to build products that are unique to each customer. Upon signing up, customers must complete a survey that understands their hair type, styling preferences, and texture. 

These responses are then analyzed with an AI-powered algorithm to design a unique formula for the customer.

Once the formula is generated, the brand employs AI-powered manufacturing to produce customized items at scale. The final product is sent to the customers, who are asked to give feedback. AI then analyzes this feedback to understand customer satisfaction and improve the customization process.

Lily AI

Lily AI is an AI tool designed to enhance product discovery and conversions in eCommerce, specifically for fashion, home, and beauty retailers. It uses sophisticated technology to match product attributes with consumer preferences.

For example, in fashion, it analyzes attributes like fabric, style, and neckline to recommend similar items, such as white crewneck t-shirts. For homeware, factors like product type, color, and wood tone are considered when displaying relevant products.

eBay

eBay has introduced its AI-powered “Shop the Look” feature, which offers personalized fashion recommendations based on users’ shopping history. The goal is to offer products that align with individual style preferences. 

Shoppers who view at least 10 fashion items in 180 days will see “Shop the Look” on their homepage and fashion landing page. The tool evolves with customers over time to enhance their shopping experience. 

Risks of AI customer service agents

As AI technologies become more common, 61% of customers highlight the need for trust, though fewer than half feel businesses use AI ethically. This gap allows companies to stand out by upholding ethical practices, transparency, and fairness in AI.

To create a secure customer experience, watch out for these potential risks associated with AI customer service agents:

Complexity with existing tools

Implementing AI systems can be complex and expensive, especially for smaller companies with limited resources. The initial investment, maintenance and training costs, and integration with existing tools can pose financial challenges when establishing commercially viable AI operations.

Data privacy concerns

As AI systems rely on large amounts of data, customers’ private information is at risk of being misused and manipulated. To maintain customer trust, companies must comply with legal regulations such as the General Data Protection Regulation (GDPR) and be transparent about processing and protecting customer data.

Lack of emotional intelligence

AI interactions can feel impersonal and lack the emotional connection customers crave, as they often involve robotic messaging. While AI enhances efficiency, it doesn’t offer the empathy many customers seek. 

How to choose the right AI agent for your business

With the wave of AI sweeping in, every business wants to hire an AI agent to make work simpler and more efficient. But every business is different, and so are the capabilities of an AI agent.

If you are new to the AI realm, consider these tips to find a tool that is most compatible with your business needs:  

Assess your needs

Determine the specific functions you want the AI agent to handle. Evaluate the tasks it should automate or support, such as responding to queries, managing orders, or providing recommendations.

Ensure it integrates with existing tools

The AI agent you select should easily integrate with your existing systems, tools, and workflows. To speed up implementation, prioritize tools that provide pre-built APIs or connectors. 

Moreover, a seamless integration process ensures the AI agent adds value without causing delays or technical difficulties.

Consider scalability

Select an AI agent that can scale its processing power, storage, and analytical capabilities to meet future demands. Evaluate its ability to handle larger datasets, integrate with evolving systems, and maintain performance under heavier workloads. 

Scalability is essential for businesses looking to expand, ensuring the AI solution remains effective and reliable as the company grows.

Ensure compliance and security

Finally, ensure the AI agent safeguards the data by using data encryption, controlling access, and adhering to industry standards. Learning and utility-based agents, which process large amounts of data, require stronger security to prevent unauthorized access. 

Opt for AI solutions that offer regular security updates, comply with regulations, and minimize risks like data breaches or cyber-attacks. 

Make interactions more personal with Plivo CX’s AI agents

Going forward, there is a need for seamless integration between artificial and human intelligence. This collaboration will give humans the wings to be creative and build meaningful bonds, while AI agents will ensure fast, proactive and accurate services.

Plivo CX is a complete cloud-based platform that can support this partnership and make customer service more empathetic. It is built to integrate effortlessly into your business and support mechanisms.

You can also train OpenAI-powered chatbots using your company’s unique datasets, ensuring customer queries are answered with the most relevant and accurate information.

Some of its top features include:

• AI-powered chatbots: Interact seamlessly with customers by providing accurate responses at speed
• Simplified escalations with notes: Summarize conversations and pass them to human agents whenever needed
• Unified agent desktop: Visualize complete customer context and insights on a single, easy-to-use application
• CRM integration: Access customer details from your existing CRM and tech stack for a more personalized experience
• Detailed customer insights: Examine live or recorded interactions to uncover opportunities for growth and improvement
• Automated ticket management: Automatically organize and prioritize incoming tickets, ensuring critical issues are addressed promptly
• Interactive voice response (IVR): Set up automated menus to efficiently direct callers to the appropriate team or agent
• Integration: Integrate seamlessly with your existing tools, such as ERP, CRM, and helpdesk tools

• Enterprise-grade security:  Protect customer data with enterprise-grade security features complying with SOC-2, GDPR, HIPAA, and PCI DSS

‍Book a demo to learn more.