How artificial intelligence (in particular LLMs) can assist agents in the contact center 

Artificial Intelligence (AI) is becoming a normal part of operations in many industries. But despite that, there’s still an incredible amount of hype around it. Plenty of it justified, and plenty more that’s not. 

Every day I see a lot of fearmongering on LinkedIn about how AI will consume 80 percent of jobs. Equally, huge swathes of people embracing AI and offering tips on how to use it most effectively. 

As we welcome services such as content generators, website builders, image creators, financial strategists and code builders into our lives, it’s easy to get overwhelmed. 

The pace of change is truly astounding. 

But, crucially, as with pretty much anything in life, it’s how AI is harnessed that will determine its impact and effectiveness. 

In this article, I explore how artificial intelligence is impacting the contact center. In particular, I’ve looked at the use of Large Langue Models (LLM), such as ChatGPT and how they can assist the agent and contact center operational team, driving performance improvements. 

I’ve also outlined actual use cases that generative AI can support and take a look at what’s next for contact centers who embrace AI. 

From cost center to profit center 

Contact centers have been under immense pressure for some time. 

It’s now widely accepted that the experience you give customers is a differentiator for your brand and can provide a competitive advantage in a highly commoditized society. 

And yet, contact centers are a large drain on resources – something senior management doesn’t like. And this means they’re often starved of investment. 

When you then layer in other challenges faced by the contact center, including: 

• Difficulty hiring and keeping agents 
• Legacy infrastructure, systems and processes 
• Lack of performance insight 
• Poor mental health of agents and staff 

It starts to paint an even more challenging picture. 

To try and tackle some of these challenges, progressive contact centers are turning to artificial intelligence for support. 

But how are they using AI in contact centers to drive operational efficiencies? Well, they’re automating repetitive and mundane tasks. Summarising large volumes of information in seconds. And they’re categorising, filing and coding information that can be retrieved in the future.  

All these things that were once on a wish list for many Senior Contact Centre leaders have now become a reality. Especially with the use of Large Language Models (LLMs). 

Large Language Models and the contact center 

By now, I’m sure you’ll have given an LLM, such as ChatGPT, a go. Venturing into the world of LLMs tends to start with feeding in prompts, usually in the hope of getting an amusing answer. 

Businesses too are getting to grips with LLMs to perform a wide variety of functions. Especially given the advancements made in where and how they’re hosted and tighter data retention policies. 

There are two core areas of the contact center that can be supported by LLMs: 

• Agents – automating repetitive or time-consuming tasks, such as summarizing a call, or summarizing previous customer interactions to help them solve the issue faster 
• Operational teams – accelerating performance insights, for example, asking the LLM to read a transcript and mark performance against a scorecard 

Just from this brief summary, you can quickly see that the potential is fairly far-reaching. 

Any job that’s currently manual in nature, involves large amounts of data or is a time drain can likely be replaced or supported through the use of LLMs. 

Let’s go into more detail about how LLM’s are changing the game in contact centres.

How Large Language Models can support contact center agents 

Here are some of the best use cases for LLMs in contact centres.

Call Summarization – Call transcripts are clunky things, especially if the agent has been on a long customer engagement. If a new agent picks up the conversation, then information is often lost, or there is a time delay while the new agent gets up to speed. 

Summarizing call details, using support from LLMs has multiple benefits: 

• Agents can instantly be brought up to speed without having to read the full historic interaction transcript 
• Operational teams don’t have to listen to long recordings to find information 
• Call summaries can be shared with customers as evidence their query has been taken seriously and the previous details are correct 

Quality Assurance (QA) – Despite the huge advancements in technology and AI, this is still a manual process in many contact centers. QA is the core performance benchmark system in use today. But when you can automate this process the benefits are clear and make a big impact: 

• QA teams spend less time manually listening to calls and more time making performance improvements 
• Scorecard completion can be automated – The LLM can ingest the transcription and the performance criteria and tell you how well agents have performed 
• Regulatory adherence can be checked for every single interaction, improving compliance scores and mitigating the risk of breaches and fines

Call Classification – This is still a major challenge for contact centers and a resource drain to manually fix when calls are wrongly classified. 

LLMs can be used to read the call transcript and decide, with a high degree of accuracy, how the call should be classified. 

Access to Knowledgebase Articles – Agents waste a large amount of call time looking for information to help customers. 

Through the use of LLMs the agent can ask a question and receive a real-time answer collating information from their (normally vast) knowledgebase articles. Saving time to reach the correct answer. 

This powerful capability also means new agents can be on-boarded faster. There’s no longer any need to spend weeks on end in training, hoping that they’ll retain the right process knowledge to answer customer enquiries.

Things change quickly in the contact center as they’re at the mercy of wider company changes. With the right LLM solution, contact centers can make fast changes to process information without having to wait for an IT team to make the change.

Talk to the team to see how AI can help your contact center 

What I’ve shared in this article is just the tip of the iceberg when it comes to the use of AI and LLMs in the contact center. Every week I see new use cases and opportunities to leverage this powerful technology. 

If you’d like to know more about how AI can support your contact center operations, contact the team today and book your free demo.