How LLMs and AI Will Change the Contact Center Landscape

The next generation of contact center AI

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How LLMs and AI Will Change the Contact Center Landscape - CX Today News
Contact CentreInsights

Published: March 19, 2024

Rebekah Carter

Artificial Intelligence (AI) isn’t a particularly new concept for contact center leaders. For years, companies have leveraged AI to help with everything from automatically routing customers to agents, analyzing huge volumes of data, and even creating intelligent team schedules. 

However, in recent years, the abilities of AI have evolved. Next generation solutions like large language models (LLMs), and generative AI are paving the way for a new era of customer experience. Ever since Open AI launched ChatGPT, virtually every contact center vendor has begun exploring the potential of next-gen AI tools.  

The question is, how exactly will LLMs and generative AI transform the contact center landscape as we know it? Here are some of the biggest changes we’re likely to see.  

Reducing Operating Costs with AI 

While an incredible contact center delivering exceptional customer experiences can deliver huge dividends to companies, it can also be expensive to build, manage, and run. One of the biggest advantages of bringing artificial intelligence into the contact center, is that it can significantly reduce operating costs.  

Generative AI solutions and large language models in particular give organizations an advanced way to automate various tasks. These tools don’t just respond to customer queries and concerns using pre-set algorithms, they can creatively solve problems, complete transactions and more.  

Leading generative AI solutions can also reduce training costs in the contact center, by providing agents with real-time guidance, support, and standardized responses to queries. With the right tools, business leaders can eliminate a lot of the repetitive tasks that consume crucial time and money in the contact center and make agents infinitely more effective.  

AI can also help the contact center evolve beyond its current form, to include other areas of the business.  

In some cases, companies may even be able to reduce the number of contact center support agents they hire, by ensuring they can rapidly adapt to changes in demand.  

Enhancing the Self-Service Experience 

Perhaps the most obvious way LLMs and generative AI solutions will transform the contact center, is by providing companies with ways to optimize their self-service solutions. Around 88% of customers now expect companies to have self-service strategies in place, to prevent them from having to call an agent or request support from a human representative.  

Unfortunately, many of the initial chatbots introduced into the contact center failed to live up to customer expectations. Many were restricted in the way they could respond to customer queries, and implementing advanced machine learning and natural language processing capabilities was often a complex and expensive process.  

The rise of generative AI and LLMs will pave the way to more humanized chatbot and self-service experiences for business leaders. These tools will allow organizations to create bots capable of offering more personalized, relevant experiences to customers. They can draw data from multiple environments to assist customers with a variety of tasks.  

What’s more, generative AI bots can be customized to suit the need of a brand and its customers. They can deliver responses in a specific tone of voice, adapt to many different languages, and integrate with various tools, such as CRM systems and knowledge bases.  

Boosting Business Intelligence and Insights 

One of the most common ways companies have leveraged artificial intelligence in the contact center is to improve business insights. Contact centers collect and process huge volumes of data on a daily basis. This data is incredibly valuable for offering insights into the customer journey, behavioral trends, and opportunities for growth.  

However, analyzing all of this data manually can be extremely complicated and time-consuming. AI and LLMs can help businesses to not only collect more valuable data, but use it more effectively. An LLM-powered chatbot can intuitively request feedback and insights from customers, which can be used to generate NPS and CSAT scores, as well as other useful reports.  

The same tools can also help make various forms of data more accessible. Generative AI solutions can standardize call transcription processes, ensuring all interactions are accurately recorded and analyzed. According to one study, companies that use automated transcription tools benefit from 63% better agent performance, and 36% higher levels of customer retention.  

That’s because access to more high-quality data gives companies the tools, they need to understand their customers and their needs, optimize their service processes, and deliver better experiences.  

In some cases, AI tools could even help businesses to increase revenue and profitability. By analyzing customer data and behavior, these tools can provide agents with personalized product or service recommendations to share with customers, leading to potentially higher sales.  

Improving Contact Center Efficiency and Productivity 

Innovative and transformative technologies like AI and automation can make a huge difference to the overall performance of the contact center. LLMs and generative AI models can significantly impact agent efficiency, by automating routine tasks.  

Automating tasks like data entry and call wrap-up means agents can spend less time on monotonous tasks, and more time focusing on urgent and complex requests. This leads to faster resolution times, shorter wait times, and higher customer satisfaction levels.  

Generative AI solutions and LLMs can also streamline processes by providing standardized responses to agents on-demand and optimizing workflows. This reduces the risk of errors and inconsistencies in the contact center landscape.  

Companies such as Local Measure have used generative AI to create guided agent assistant tools (Smart Tools). These tools act as virtual assistants for employees, helping them to rapidly surface data, create canned responses to questions, and even automatically complete forms. These tools can potentially reduce call handling times by up to 50% and first-call resolution rates by 20%.  

Elevating Agent Experiences 

While many companies believe that LLMs and generative AI will have a significant impact on the customer experience, the impact on agent experiences is often overlooked.  

Some market leaders have even shared concerns that advanced AI solutions may eliminate the need for contact center professionals. However, like most AI innovations, LLMs and generative AI aren’t intended to replace agents, but instead augment their performance.  

The insights gathered by LLMs, and AI-powered tools can empower agents, by giving them access to more of the information they need to perform at their best. The right tools can reduce the risk of agent burnout, by streamlining workflows and processes. They can also reduce the number of tasks agents need to contend with every day.  

Intelligent solutions can ensure agents spend more of their time focusing on fulfilling, satisfying tasks, that benefit the business, and help them to hone their skills. Plus, they can reduce some of the tasks that agents dread most, like dealing with post-call work and wrap-ups.  

The Rise of The Next Generation AI Contact Center 

Generative AI and LLMs represent a powerful next step in contact center evolution. With these innovative tools, companies can potentially reduce operating costs, improve team performance, and enhance customer satisfaction levels.  

The key to success for business leaders will be learning how to implement AI solutions correctly, as a tool for augmenting, rather than replacing the human agent.  

As CEO of Local Measure, Jonathan Barouch notes:

Striking the right balance between automation and human touch is essential. Automating repetitive tasks allows agents to focus on more complex issues, but relying too heavily on automation may result in impersonal interactions and dissatisfied customers.” 

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