Top 10 Ways AI Agents Help Reduce Customer Support Costs in 2025

What do you see in this, as customer expectations are higher than they used to be? Thousands of factors are shaping why your business needs to provide top-notch customer support for simple to complex needs. One or two of the reasons include that customers want hyper-personalization and seamless support 24/7. Unfortunately, these areas are where traditional support often falls short, contributing to the high cost. 

What can you do to meet these customer expectations and also reduce customer support costs? Most businesses believe that improvements in customer service can be achieved by increasing budgets. According to the Salesforce Snapshot Survey, decision-makers assume that the customer service budget could increase by 23% over the next year. With already rising customer service costs, this rise could seem like drowning in a pool where you already have a tight budget and hit your bottom line. McKinsey claimed that customer support leaders are looking for ways to reduce customer support costs through automation. 

As a cost management strategy, AI agents become a huge savior, improving CX quality to an unimaginable level. AI agents are rapidly becoming a key tool for customer support, offering effective service, resolving L1 queries at the first contact, and reducing customer support costs to a significant level. This helps you save money on tickets, as well as in other areas that inadvertently raise costs.  

In this guide, we’ll break down how you can use AI agents to optimize resources in a balanced proportion, reduce customer support costs, and build high-quality support.

The cost per ticket can range from $6 to $40, depending on the L1 and L2 tickets. Surprisingly, these costs rise in proportion to the complexity as it appears. In most cases, traditional support adds to this pain. Delayed responses, recurring tickets, and frustrated customers are all common in traditional customer support, which hinders automation from working at its best. The hidden cost of poor customer service is acute. You can realize customer churn as the outcome. 

With the limited automation that traditional support enables, customer support often falls short of meeting its goals. AI agents can make a significant difference in implementing hyper-automation and contribute to cost reduction. Some eye-opening factors to support automation in customer support include, 

• 80% of repetitive queries

On a day-to-day basis, customer support receives 80% of repetitive queries that typical support does not resolve, contributing to the high costs. AI agent-led customer support can easily handle them, freeing service desk agents. 

• Poor knowledge base quality 

With limited automation, knowledge bases struggle to apply advanced techniques in capturing key interaction points and updating their existing data sources. This hinders self-service from operating independently and deflecting tickets on a large scale. Advanced AI automation keeps updating knowledge and boosts the ticket deflection rate.   

• Limited self-service adoption rate  

Due to a poor knowledge base and lengthy search answers, self-service sees lower adoption rates, as most users prefer using emails, phone calls, etc. This perhaps impacts ticket deflection rates. However, sophisticated AI automation, such as AI-agentic automation-based customer support like pagergpt, can result in an 80% decrease in deflection rates. 

• 45% of disconnected support channels: 

Traditional support systems often fail to facilitate seamless integrations. All collaboration and communication channels from emails to phone, and SMSes to chats to self-service work in silo in 40-45% cases. Wait times increase as the business struggles to unify data points and provide assistance. Advanced AI automation tools, such as pagergpt, offer seamless integration, enabling AI workflows for numerous customer support tasks. They unify customer interactions from all channels on a single platform to provide a single source of truth, thereby accelerating the ticket deflection rate. 

• Limited personalization in customer support 

Traditional support does not care about providing a one-size-fits-all solution for all problems. As it often overlooks the context of varied levels of questions, it produces generic answers and does not solve real problems. Advanced automation can overcome 30% of personalization limitations in self-service with scalable and real-time LLM-powered answers. 

Advanced automation that AI agents bring for your support drives cost reduction by improving efficiency across all levers that contribute to increased operational costs. Simultaneously, you can achieve a 20-30% reduction in ticket deflection rate without human intervention.

When you are dying to know how to reduce customer support costs effectively, there are multiple ways AI agents can help you achieve your goals. From improving self-service to updating knowledge bases, you can lower customer service costs in flexible ways. Find these approaches and learn how AI agents can help you manage expenses and cost savings for customer support. 

Automate tier-1 queries with 24/7 AI agents 

Is your support over-brimmed with questions like ‘what’s my order status’? Or ‘when I get my refunds back?’. These are the most common Tier-1 queries, including others such as onboarding, account updates, and KYC updates. Unlike traditional support, which accumulates tickets, AI agents can efficiently answer these questions and resolve customer problems. 

If you can deploy highly scalable and robust LLM-powered AI agents, achieving a deflection rate of up to 70% is relatively easy with 24/7 AI agents, which is otherwise unattainable when your human agents are not at their desks. 

pagergpt makes it easy for you to automate tier-1 queries at scale. You can streamline queries across sales, ecommerce, IT support, and anywhere you want. 

GoTo, a leading software service provider for remote communication and collaboration, dramatically achieved an 80% deflection rate using AI agents across its IT support. By enabling 24/7 availability, GoTo offers great promise to resolve tier-1 questions steadily. 

Reduce ticket volumes with smart self-service on autopilot 

AI agents can seamlessly integrate with knowledge bases and effectively retrieve answers to frequently asked questions (FAQs). Let’s say your customer needs an answer to ‘why my Figma account is not offering hand-off?’ An AI agent can put your self-service on autopilot, allowing your customers to find quick answers from dynamic FAQs and solve their problems without looking for human agent assistance. It means you can solve more tickets and reduce the volume.

With self-service on autopilot, you can provide much faster resolution to your customers, reduce human dependency, and save money. pagergpt provides this innovative AI agent platform that helps you put your customer support on autopilot. 

Here’s how autopiloting self-service customer support reduces costs by eliminating the need for human intervention. 

Per interaction cost analysis: 

According to Juniper Research, self-service can lead to a 50-90% cost savings in each interaction, estimated to drive $8 billion in annual industry savings across customer support. However, a hybrid approach is often more effective when you can combine self-service for 80% of routine queries with human agents for complex queries. 

Boost FCR via personalized answers 

With AI agents taking care of your support needs, you can also scale up first contact resolutions using hyper-personalization. When your service desks receive an escalation, they can equip the agent with the necessary tools and personalization recommendations to beef up resolution time. AI agents work across business tools and pull CRM, ERP, and analytics tools data to build personalized offerings and solve problems at the initial stage of ticket escalation. 

For example, your customer asks, ‘I was charged twice. How do I get a refund?’’ and this question lands as an L1 query. With AI agents fetching data for you, your support agent can instantly find real-time CRM data and update your customer about the exact date for a refund.

This is a proactive approach to providing faster and more accurate resolutions through personalized answers, while also eliminating the need for follow-ups and potential escalation to higher tiers. You can achieve significant cost savings by not engaging your agents. 

Interestingly, reducing follow-up interactions can reduce the customer support cost per ticket. By default, for 10k tickets, you can reduce follow-ups by 2k tickets and lower service costs by $60,000 per month. 

Optimize agent performance with AI copilots 

AI agent-led customer support fosters customer service cost savings by simplifying interactions and issue resolution for agents. With a support feature like AI Copilot, your service desk teams can enhance agent productivity in various ways and increase the resolution rate. 

• AI-based answers: Agents can use AI tools to generate replies and deliver quick answers for customer queries. 

• Instant issue handling: AI-tagged tickets draw immediate attention based on priority, enabling the most qualified agent to address them and reduce wait times. 

• SLA compliance: AI summaries enable agents to create valuable inputs from customer interactions more quickly and generate well-structured notes for stakeholders to help evaluate SLA compliance. 

• Quick onboarding: With AI agents helping agents derive significant resources for self-training, agents can learn more quickly and become more effective in addressing customer issues.   

With beefed-up agent productivity, agents can expand their capacity and handle a higher volume of tickets, resulting in a cost-saving benefit. 

Unlike most leading AI agent framework providers, pagergpt provides CX leaders with an AI copilot to help boost agent productivity and drive cost savings. 

Prioritize high-value tickets using smart escalation and live chat 

When you engage in manual iterations for triage, it takes hours to gain clarity about the logged issue, which puts your customers in the queue for a real-time answer. AI agents in customer support eliminate this traditional approach and bring a modern triage approach. 

AI agents can read human sentiment and understand the priority of direct conversation with a human agent. From analysis to escalation, AI agents handle everything, from the initial customer interaction to the resolution of issues. By applying smart triage, you can escalate a ticket to a live chat, where the most equipped person is ready to address the issue and resolve it. 

This is another practical approach, where AI agents reduce the chances of misrouting and triggering resolution delays. 

Also, Intelligent prioritization and escalation can reduce costly escalations later. Overall, smart escalation is believed to boost a 15% reduction in FCR and a 12% increase in CSAT. 

Real-time quality assurance & coaching

AI agents help with agent training to lower customer support costs. Unlike traditional support, AI-agent-powered customer support gives an enhanced view into customer interactions, chat history, and agent analytics. Using this support data, you can build a robust analysis of both chatbot and agent performance. AI agents like pagergpt offer advanced data insights into agent and bot performance to prepare AI audits, uncovering weak areas for improvement. 

With easy-to-get AI insights, you can learn how to work your training program out for agents and ensure compliance for support. The advantage of AI audits is that you can save on a training program that would otherwise require expensive QA teams. If you ignore the use of AI agents, you must be ready to pay for it. 

• Spend an annual package of $90,000 for a senior QA engineer, including benefits and other expenses.

• Pay an hourly rate of $65 for QA contractors. 

• Salaries and hourly rates can vary depending on location and team size.

• Also allocate resources for office space, software licences, and equipment. 

For your respite, AI agents for customer support help you eliminate all of the costs linked with QA needs. 

Create multichannel support via shared live inbox 

The cost of siloed customer support is enormous, as it leads to a loss of track of information and a failure to provide timely and appropriate support. Gartner claims in its survey that siloed data can cost companies $12.9 million per year for inefficiencies caused by lost data. 

Creating multichannel support helps you eliminate the risks. Customer support AI agent solution provider, pagergpt, brings multichannel support through its shared live inbox. You can prevent losing track of customer interaction data and unify it into this platform from Slack, MS Teams, WhatsApp, Messenger, web chat, knowledge base bots, and any other relevant sources. This enables you to streamline customer queries, quickly assess support priorities, and provide a coordinated response, leading to faster problem resolution and significant cost savings. 

Predict and prevent reactive ticket volumes 

Unlike traditional support, your AI-agent-based customer support provides the ability to harness predictive analytics, which detects issues before they become difficult to manage and mitigates them, while also reducing the volume surge. 

Let’s say a company has a new update for its collaboration software tool, which creates login failures. AI agents in your customer support system notify you of incoming support tickets with queries regarding login issues. Soon, AI agents can detect the pattern and alert the support team before it becomes widespread. This helps the company prepare a proactive response for customers and offer them a workaround for a quick fix.

Additionally, they update their knowledge base so that customers can handle a sudden outage independently and reduce the volume of reactive tickets. This helps lower costs by reducing the number of tickets assigned to agents. 

Build multilingual support 

If you rely on traditional support, you soon realize that it supports a few languages. This presents a significant communication barrier, often requiring assistance from a large multilingual support team. This adds to higher costs for hiring teams proficient in specific languages and delivering on a global scale. 

An AI agent for customer support, like pagergpt, offers multilingual support to remove barriers, promote engagement, and resolve queries at scale. With pagergpt providing support over 90+ languages, you can easily eliminate the need to hire a costly multilingual team. 

Stay compliant with industry-leading regulatory bodies 

Privacy violations can cost a lot. Non-compliance with HIPAA can cost $100-$ 50,000 per violation. GDPR fines are also notorious. Who doesn’t remember the imposition of penalties on Meta for GDPR violations? GDPR fines encompass 4% of the global annual revenue. When you use a traditional support system, chances are that you double your risk of violating privacy protocols because you need to maintain a lot of manual processes. 

The risk is reduced with AI agent-powered customer support, which features built-in security measures to protect privacy and provides automated compliance workflows for GDPR, SOC 2, HIPAA, and other critical data protection regulatory bodies. pagergpt ensures that you can build robust security frameworks for AI agents to comply with various regulations and help prevent penalties. 

Examples: Real-world case studies for customer service cost reduction 

It is not that AI agents are hype and all these cost reduction approaches are bubbles on water. AI agents transform how customer support works and boost cost reduction. Increasingly, companies are relying on AI agents to save significant amounts of money. 

• Unity, a blockchain-based gaming company, implemented AI-powered customer support. The company is believed to have deflected 8,000 support tickets and gained $1.3 million in savings.  

• Global Airlines gained a 50% cost reduction in managing booking and cancellation-related enquiries using AI-powered customer support. 

Some best practices for reducing customer support costs include clever strategies. It is essential to fully optimize AI agents and ensure they work towards your cost reduction goals. 

• Utilizing automation everywhere

Don’t over-automate each and every workflow that can also be done manually. Additionally, over-automation can erode trust in human skills. Your team can unleash real-time efforts even if issues are minor and low-value. 

• Being less serious about LLMs' answers 

Ensure you use healthy training data for your AI workflows. Having poor data for AI models means you only produce a bad response. Prioritize using well-structured and clean data to enable your LLMs to work with accurate information and produce responses tailored to user queries.  

• Ignoring the synergy between humans and AI

Most AI tools do not focus on the design that helps build human-AI synergy. This results in customers getting repetitive and meaningless answers, which don’t help solve their problems.  Ensure that you have implemented this design to enhance your AI-agent-based customer support and facilitate smart escalation to live chat when necessary.

Deploying AI agents does not guarantee that you can make the most of your tools. Make sure you focus on AI chatbot ROI in customer service. Calculating ROI through consistent monitoring of key performance indicators (KPIs) provides valuable insights into your customer support performance. It enables necessary iterations to build a high-quality support system while improving cost benefits. 

Here are the main KPIs to track: 

1. Cost per resolution: Find the average cost you need to resolve an issue using AI agents versus human support agents.

2. Ticket deflection rate: Calculate the percentage of tickets being resolved by AI agents without human intervention.

3. Agent productivity per hour: Track the percentage of tickets your customer support agents can solve in an hour. 

4. Customer satisfaction score: Allow your service agents to collect feedback to measure customers’ satisfaction score or CSAT based on their interactions with AI agents. 

A real-time dashboard is the perfect tool for your team to track each metric, enabling you to create a detailed analysis of your expenses and optimize costs to drive cost efficiency. pagergpt provides an industry-leading visual dashboard for all customer interactions, helping you perform ROI calculation and get the best value for your investment. 

Customer support expenses are something every CX leader should consider. They are rising as you must gather resources for agent training, tools, software licenses, facility management, and many other factors. With that, there are ongoing challenges of retaining a high-calibre team to handle complicated customer interactions. 

Just as you learned, AI agents can help reduce support costs; it is time to prioritize starting your AI agent game for customer support. pagergpt provides an easy way to start your AI agent journey. With no-code setup and industry templates ready to use for e-commerce, concierge, and support, as well as any other use case, you can realize a faster time to market and value. Connect with pagergpt and schedule a demo today.

How can you use self-service customer support to reduce costs?

Self-service customer support enables customers to access essential information easily at their fingertips. On top of it, when you use AI agents, you can put self-service on autopilot and help your customers resolve issues instantly without looking for human agents. This is a cost-effective approach to reduce ticket volumes and slash agent involvement, which helps reduce customer support costs. 

How can AI agents for your customer support help lower customer support expenses?

AI agents ensure you can provide support 24/7, resolve 80% of repetitive queries, and eliminate the escalation of tickets to higher tiers. This reduces workloads on agents, resulting in a cost reduction per ticket.   

How do AI agents help with agent productivity?

AI agents can assist human agents in expanding their capabilities for managing a large volume of tickets by providing AI suggestions, instant replies, internal notes for communication, and AI summaries. This can reduce the need for dependencies on agents outside of working hours. 

Can live chat help reduce customer support costs? 

Live chat is a crucial feature of any customer support system, facilitating intelligent escalation for prompt, real-time assistance with complex issues. By providing instant escalation, live chat ensures that there are no recurring tickets, allowing you to avoid a reactive approach and build proactive support for cost efficiency.