LLMs are advanced AI models that use various technologies to provide human-like responses to a given input. Here, we’ll discuss the role of large language models in customer support, the benefits they offer, and how to integrate them with existing CRMs.
Artificial intelligence has become an integral part of customer support in most industries. It helps automate repetitive tasks and provides quick responses to customers. The introduction of large language models (LLMs) and generative AI has further fueled the development of customer support. Many businesses have either invested in LLMs or plan to adopt LLMs for customer care services.
According to Precedence Research, the global large language market is estimated to be $7.77 billion in 2025 and is projected to reach $123.09 billion by 2034 at a CAGR (compound annual growth rate) of 35.92%. While North America had a dominant market share of 33% in 2024, the report shows that the Asia Pacific region is going to be the fastest-growing market in the coming years.
As per Deloitte’s reports, almost 80% of businesses think generative AI will drive transformation in their industries in the next three years. Another report by Zendesk Benchmark data shows that 72% of CX leaders believe AI agents should work as an extension of the brand’s identity. Moreover, 8 in 10 consumers think AI bots are useful to resolve simpler and smaller issues.
In this blog, we’ll find out more about large language models in customer support, such as their role, benefits, challenges, and how LLM companies can integrate the models into customer support systems!
AI chatbots are software tools built on powerful artificial intelligence and NLP (natural language processing) algorithms to communicate and interact with diverse users. Technologies like machine learning, data analytics, big data, etc., are used to understand customer information and behavior patterns to provide relevant and useful responses to queries and complaints.
AI-driven support systems can enhance customer satisfaction in many ways. For example, AI chatbots are easily accessible 24*7*365. Unlike human agents, AI support systems don’t get tired or take breaks. These can assist representatives in handling excess workload by communicating with several end users simultaneously. The systems can be integrated with CRM software and data analytics tools to analyze the data in real-time and provide actionable insights to the representatives.
Moreover, any business can use AI chatbots to streamline its customer support processes. AI product development services offer tailored solutions to build, deploy, customize, and implement the systems that align with each organization’s requirements. Additionally, the apps can be built and hosted on-premises or on remote cloud servers. Several enterprises prefer cloud-based AI chatbots as they are more effective, scalable, and flexible. They can be connected across multiple channels and accessed through a unified interface. The data is stored in a central repository and can be accessed in real time.
Almost every industry benefits from using AI in customer support. Most businesses have to interact with customers in some form, be it a retail or eCommerce marketplace, a healthcare center, a travel agency, an IT business, or a utility service provider. Furthermore, effectively analyzing customer data is crucial to ensure the business stays relevant in competitive markets and understands what the target audiences require. By empowering customer service with AI, an organization can streamline data flow, automate workflow, and reduce the load on human representatives.
This is an important question, as many businesses hesitate to adopt AI and LLM technologies due to the costs involved in the project. While the initial investment may be expensive, organizations can gain many cost benefits and enjoy higher ROI in the long run. A few benefits of using chatbots for support are as follows:
The advancement in technology and the development of large language models (LLMs) have revolutionized customer support in many more ways. LLMs can be used to build advanced AI agents that can empathize with customers and provide more human-like responses to their queries. These are powerful and can perform complex tasks with relative ease.
Absolutely! Large Language Models can reduce response time in customer support through automation. That’s because they reply instantly to a user’s message and try to provide a resolution. LLMs work in real-time to understand the input data and share a relevant output. Generative AI applications built on large language models are some of the best chatbots and AI agents used by businesses.
A greater share of customer queries can be resolved without human interference. This makes it possible for a business to be active and efficient even on non-working days or holidays. Customers who raise a concern on a weekend don’t have to wait for a representative to check their emails on a Monday morning. They can find a solution through LLM chatbots.
Not only do LLMs reduce response time, but they also provide contextually relevant and accurate answers using deep learning technology. This makes them a worthy option to revamp the customer support departments.
The quality of customer service offered by a business can determine its success and brand image in competitive markets. Customers of today don’t want to wait for long hours for a representative to reply to their message. They want instant results and personalized solutions. They want businesses to be customer-centric and show that they matter.
In such instances, LLMs and GenAI apps are highly helpful in revamping the customer support department and improving its overall efficiency and performance. It is recommended to hire generative AI services from reliable AI product development companies to align the business mission with customer expectations.
Here’s how LLMs can improve customer support efficiency:
LLMs are used to build generative AI chatbots that support humans in various ways. For example, the customer support representative can rely on the AI bot to interact with customers, track the conversation, translate messages from one language to another, and so on. When the issue is escalated to an expert, the person has access to the previous communication and can take over when necessary. A team can work on the same and use the AI platform for collaboration. Due to the human-like responses provided by the chatbots, the representative will not feel isolated or lonely at work.
The chatbots built using large language models are quick, more accurate, and user-friendly. While the previously designed chatbots could give only fixed responses, the genAI apps can give real-time replies, adjust the answer according to the input, and so on. For example, if a customer wants the chatbot to guide them in installing a product, it can provide a step-by-step procedure with a detailed explanation, much like how a human representative would do. This makes customers feel as if they are interacting with humans. It leads to a better customer experience.
Personalization has been a keyword in the global market for the last few years. Customers want personalized recommendations, and targeted ads about what they like, and want brands to show that they take user preferences seriously. By using large language models in customer support, businesses can provide personalized interactions to customers. This way, the user is less likely to exit a chat midway due to a lack of relevant answers or annoyance. Moreover, the AI chatbot can analyze customer data to suggest alternatives or products that suit their tastes. It elevates the shopping experience and promotes repeat purchases.
Even startups can have customers who speak different languages. Thanks to globalization, people from different cultures and communities work and live together. They use products created in other countries and rely on services from people across the seas. In such instances, businesses should have a customer support team that can speak multiple languages. While global brands can afford to have support teams in individual countries, the same is not possible for emerging businesses. It is just too expensive. A more feasible alternative is to use LLM-powered chatbots to communicate with customers who speak other languages. The bots are trained in several regional and global languages as well as their dialects and slang.
A tech tool can complete a repetitive job faster than a human. Also, it doesn’t tire of doing the same job a million times. By automating recurring tasks, a business can free up time for representatives. This allows them to focus on complex issues, the ones that cannot be left to a machine and have to be handled by a human expert. It reduces work pressure, which increases efficiency and results. Since the activities are automated, they will be completed quickly on the side. In short, the customer support department can finish more work in less time without compromising quality.
Large language models are also trained to detect anomalies in interactions and predict potential fraudulent transactions. Customer support representatives can use the chatbots to be proactive in enforcing security protocols to prevent customer data from being accessed by scammers. For example, a change in chat pattern or incorrect answers by a user can be an anomaly that triggers an alert. This might help in identifying if the user is a scammer with a stolen identity. The representatives can block a transaction or report it to prevent fraudulent activity.
Responding to a customer’s message and resolving an issue is not just about the present context. It is also about the type of relationship the customer has with the business, their expectations from the brand, etc. For example, a customer who has been loyal to the brand for years is likely to expect more respect from the customer support team. After all, a loyal customer has to be prioritized and kept happy. Large language models process customer data to get the background details and can engage customers actively in meaningful conversations. By gauging the user’s responses and previous interactions, the chatbots can prevent potential complaints from customers.
Another way large language models in customer support increase efficiency is by automatically creating more content tailored to suit the user requirements. Instead of copy-pasting the same information from the knowledge base, the chatbots can rewrite it in a simpler format, translate it to other languages, etc. It can quickly create content for target emails, marketing campaigns, and promotions to attract more leads or close a sale. By using technology for such time-consuming work, businesses quickly close the tickets raised to resolve customer complaints and queries.
Large language models are highly scalable and built to handle extensive amounts of data. Businesses can use versatile and scalable chatbots by partnering with LLM service providers to build applications tailored to their specifications. By hosting the IT infrastructure on secure cloud platforms, it is easy to scale and upgrade the apps without pausing work or causing delays.
While technology has many advantages, it is necessary to follow a transparent process and comply with data regulations to prevent the unethical use of AI. LLM consulting companies help businesses create detailed documentation for the same to avoid attracting lawsuits.
When using large language models in customer support, it is vital to train them on high-quality customer data. Otherwise, the chats, recommendations, and insights will be biased or incorrect, leading to more problems for the business. The data has to be cleaned before it is analyzed.
Building an LLM-based chatbot can be expensive. It also needs computational resources to run in real-time. Business should talk to the AI product development services provider about the financial aspects, their requirements, and constraints to create a strategic plan for revamping customer support.
The process doesn’t end with implementing the chatbot in the business. It has been regularly monitored and upgraded to work with the latest third-party integrations and new tools in the market. This prevents the app from becoming outdated. Hire a service provider who offers long-term maintenance to save time and resources.
Understand the requirements and budget constraints to share the expectations with the LLM consulting company.
Implementing large language models in customer support can redefine the organization by converting a business-centric model into a customer-centric approach. This makes the brand more accessible and reliable to the target audiences irrespective of the market size, share, and conditions.
With LLM-driven AI chatbots in customer care, businesses can ensure their customers are happy with the services and become a part of the ecosystem. Loyal customers are an asset and provide a competitive edge to many brands. By partnering with the right LLM consulting company, a business can achieve its objectives and increase revenue.
LLM aka large language model development services are a part of advanced AI development solutions. Experts can build a powerful application using LLMs as foundation models. They train the models using public and proprietary data to fine-tune their responses and increase accuracy. LLMs can handle large-scale datasets and provide real-time outputs by performing a series of complex tasks. Enterprises can use large language models in any department and for varied requirements.
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Fact checked by –
Akansha Rani ~ Content Creator & Copy Writer
