Gen AI in Customer Support: Tools, Benefits, and Challenges

Many contact centers struggle with long wait times, inconsistent responses, and agent burnout, making it difficult to maintain service quality. Generative AI in customer support helps businesses handle these challenges with faster resolutions, reduced agent workload, and better experiences. According to HubSpot’s 2024 Annual State of Customer Service Report, 84% of respondents say AI tools will help meet customer service expectations. 

livepro helps businesses meet these expectations with AI-powered solutions that make customer support faster, reduce agent workload, and keep interactions consistent. Agents get quick access to accurate information, while AI-driven voice assistance handles routine inquiries efficiently.

livepro’s Generative AI Solutions for Contact Centers

livepro brings AI-powered customer support to contact centers, making it easier for businesses to handle high inquiry volumes, assist agents in real time, and deliver accurate responses without added complexity. 

It offers two major products for using generative AI in customer experience: 

AI-Powered Knowledge Management

Managing and retrieving knowledge efficiently is one of the biggest challenges for customer support teams. livepro’s AI-powered knowledge management improves how contact centers access and use information. 

Instead of agents manually searching through documents, policies, or outdated databases, livepro’s AI understands queries and instantly delivers relevant, approved answers.

Here’s how it helps: 

• Context-aware search: Understands the intent behind a query and delivers the most relevant information. For example, if an agent searches for “refund policy,” the system pulls up the latest approved guidelines instead of outdated documents.
  
  
• Luna AI Voice Agent: Luna is livepro’s AI-powered voice agent that sounds natural and helps customers over the phone, any time of day. It connects directly to the same trusted knowledge your agents use, so it always gives accurate answers (we discuss this in more detail in the next section). 
  
  
• AI Overview: Gives agents instant, clear answers by generating natural language summaries from approved knowledge. It only pulls from trusted content, so every response is accurate and links back to the original article. This helps agents double-check details and reply with confidence. Agents can give feedback by clicking thumbs up or down, helping improve future suggestions. A copy button makes it easy to paste the answer into a response, saving time. For example, if an agent asks how to reset a customer’s PIN, AI Overview will show a short, ready-to-use answer with a link to the full guide. This makes support faster, more accurate, and easier for everyone.

• Assisted recommendations: Livepro suggests the most relevant answers using a mix of keyword and semantic search, AI relevance scoring, and past agent feedback. This combination helps the system accurately understand user intent and surface the right knowledge article without manual searching. For example, if a customer asks about service availability, the system might instantly suggest an article covering business hours, eligibility, or troubleshooting. This saves agents time and helps them respond confidently.
  
  
• Agent Assist: Agent Assist listens to live phone calls and monitors chat messages in real-time. As the conversation unfolds, it automatically surfaces the most relevant knowledge article, based on what the customer is asking. For example, if a caller reports a login error, Agent Assist instantly pops up the step-by-step troubleshooting guide — no need for the agent to search manually. This helps agents respond faster, reduce handling time, and stay focused on the conversation.
  
  
• Gen AI Authoring: Authors and admins can create knowledge easier than ever before. Add in rough or draft content and polish using AI. Knowledge authoring workflow is drastically faster and easier. 

Luna: An AI Voice Agent

Handling high call volumes and providing round-the-clock support can be a challenge for contact centers. Luna is designed specifically for contact centers, acting like a human when interacting with customers by answering inquiries using an organization’s knowledge base. 

Unlike generic solutions, it delivers consistent and reliable responses without adding to knowledge silos. 

Luna’s generative AI customer support chatbot can:

• Handles high call volumes: Luna manages multiple calls at the same time, helping customers before they reach a live agent. This reduces call queues and wait times, especially during busy periods. For example, if several people call with billing questions or to schedule appointments, Luna can handle those requests right away, without placing anyone on hold. This keeps your customer service fast and responsive, even when call volumes spike.
  
  

• Delivers accurate responses: Pulls information directly from the organization’s approved knowledge base, providing correct and consistent answers. Customers receive reliable information without the risk of AI-generated misinformation.
  
  
• Available 24/7: Works beyond regular business hours to provide uninterrupted support. Whether it’s a late-night account inquiry or a weekend service request, customers always get an answer without delay.
  
  
• Transfers to human agents when needed: It detects when a query requires human assistance and smoothly hands the call over to the right agent. This keeps complex issues from being mishandled while Luna manages simpler requests.

Generative AI vs. Traditional AI in Customer Support

Traditional customer support AI relies on rule-based systems that follow pre-set scripts and decision trees to handle customer queries. These models use structured data and keyword recognition, making them effective for straightforward and repetitive tasks like FAQs or basic troubleshooting. 

While useful, they have limitations when dealing with unpredictable questions. If a query is phrased differently or falls outside the programmed responses, the system may struggle to provide a relevant answer.

Generative AI works differently by using large language models (LLMs) to generate responses dynamically instead of selecting from a fixed set. It processes natural language, retains context throughout conversations, and adapts to different phrasing, making interactions feel more natural. 

Instead of relying on scripted responses, Generative AI predicts user intent and constructs context-aware replies in real-time. This allows it to handle complex, multi-turn conversations that require flexibility and deeper understanding.

Use Cases of Generative AI in Customer Support

Generative AI is being used in customer support to improve response times, assist agents, and automate routine processes. 

Here are some Gen AI in customer support examples that show how businesses are applying this technology:

1. Live Support

Generative AI can assist customers in real time through chatbots and voice assistants, handling common inquiries without human involvement. Many customer support challenges arise when agents are unavailable or need to call customers back after looking up information. 

This leads to delays, repeated follow-ups, and customer frustration. AI-driven assistants help by understanding context, providing immediate answers, and reducing wait times.

2. Personalized Customer Interactions

Generative AI can adjust responses based on a customer’s history, preferences, or previous interactions, making support more relevant and reducing repetitive conversations. Instead of offering generic replies, AI can pull relevant details to provide a more seamless experience.

For example, a patient calling to check their upcoming appointment details doesn’t need to wait for a receptionist to look up their records. Conversational AI in healthcare, like Luna, can instantly retrieve their scheduled appointment, confirm the time and date, and provide any relevant instructions, such as fasting requirements before a test, without requiring the patient to repeat their information. 

If changes are needed, Luna can help reschedule the appointment or escalate the request to a human agent when necessary.

3. Automated Ticketing and Issue Categorization

Generative AI can automatically analyze customer messages, identify the issue, and automatically categorize tickets. This reduces the need for manual sorting and makes sure inquiries reach the right team faster. 

AI can also recognize urgency, prioritizing time-sensitive requests like service disruptions or complaints. This helps businesses manage support queues more effectively and respond to customers faster.

4.  Multilingual Customer Support

Generative AI can translate customer inquiries and responses in real-time, allowing businesses to assist customers in multiple languages without needing bilingual agents. This helps companies expand their reach and provide consistent support across different regions. 

AI detects the customer’s language automatically and generates accurate translations, reducing misunderstandings.

5. Sentiment Analysis for Customer Interactions

Generative AI can analyze customer messages to detect emotions like frustration, urgency, or satisfaction, allowing businesses to respond appropriately. If a customer expresses frustration over a delayed order, AI can recognize the sentiment, prioritize the inquiry, and escalate it to a human agent if needed. 

This helps businesses handle complaints more proactively and adjust responses to match the customer’s tone. By understanding sentiment, AI can improve interactions and prevent small issues from escalating into larger problems.

The Future of Generative AI in Customer Support

More businesses are integrating generative AI into customer support to improve response times, assist agents, and automate processes. Gartner predicted that by 2025, over 75% of customer service and support organizations would use generative AI to boost productivity and improve customer experience. We already see this shift happening, with AI-driven tools helping agents work more effectively and making customer interactions smoother.

So, what’s next for generative AI in customer support?

• AI-Human Collaboration: AI is not replacing human agents but working alongside them. When organizations activated AI-powered tools, agents could instantly summarize text and voice interactions, reducing contact time by 10 to 20 seconds per interaction. This speeds up resolutions while allowing agents to focus on complex cases.
  
• Proactive Customer Support: AI will analyze past interactions and behavior patterns to anticipate customer needs before they reach out. This enables businesses to offer solutions in advance rather than reacting to issues.
  
• AI-powered Training and Skill Development: Generative AI is also reshaping agent training. AI-driven simulations can mirror real customer interactions, helping agents practice different scenarios and improve soft skills. Early results show that 80% of ongoing training could be replaced by AI-driven training, leading to a 33% improvement in customer interactions.
  
• Voice AI Advancements: AI-powered voice assistants will continue to become more natural and context-aware, improving phone-based support and reducing reliance on human agents for routine inquiries.

Despite its growth, generative AI in customer support comes with challenges that businesses need to manage:

• AI Accuracy and Hallucinations: AI-generated responses need careful monitoring to prevent misinformation and maintain reliability. Unlike generic AI solutions, Luna pulls information directly from an organization’s approved knowledge base, making sure customers receive accurate and verified answers instead of AI-generated assumptions.
  
• Data Privacy and Compliance: Businesses must comply with regulations like GDPR, CCPA, and HIPAA to protect customer data, especially in industries like healthcare and finance. livepro’s AI-powered solutions help businesses stay compliant by using controlled access, approved knowledge sources, and governance features to prevent unauthorized information sharing.
  
• Maintaining Human Oversight: While AI can automate many tasks, human agents are still essential for handling sensitive or complex inquiries. AI should assist rather than replace agents, offering suggestions and summarizing interactions to help them make informed decisions while keeping the human element in customer support.
  
• Integration with Existing Systems: Implementing AI shouldn’t slow things down. livepro works with your existing platforms, so there’s no need to change tools or rebuild workflows. What makes livepro stand out is how quickly you can get started. Features like LightspeedAI, Source Documents, and AI Overview are built to help teams set up and go live faster than any other system. Whether you’re importing existing documents or delivering instant answers, livepro makes AI adoption smooth, fast, and practical.

Book a free demo today to see livepro in action. 

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