GenAI for Contact Centers: The Latest Trends and Statistics

Uncover the latest applications, benefits, and statistics swirling contact center GenAI

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Contact CenterInsights

Published: December 18, 2023

Charlie Mitchell

The Oxford University Press recently named “rizz”, Word of the Year for 2023.

Yet, if the tech and CX industries had run similar competitions, “GenAI” (short for generative AI) would surely win both.

Indeed, Metrigy reported that 74.5 percent of companies would adopt generative AI for customer-related activities before the close of 2023 – underlining the tech’s rapid rise.

Furthermore, another 15.1 percent plan to do so in 2024, as evident in the chart below.

Sharing this research during a webinar with CCaaS visionary UJET, Robin Gareiss, CEO of Metrigy, pinpointed many more fascinating findings.

In doing so, she started by isolating where contact centers are beginning to leverage the technology.

The Most Valuable Use Cases for Generative AI in Contact Centers

As part of the study, Metrigy asked participants; of the ways companies use generative AI, which do you think is most valuable?

In response, customers pinpointed the following three top use cases:

  1. Content creation (40.0 percent)
  2. Classify customer interactions (30.8 percent)
  3. Summaries of internal meetings (22.9 percent)

Yet, content creation isn’t just one application of generative AI. It splits into several use cases.

That is evident in the chart below, which shares six examples already installed in more than a third of contact centers.

Interestingly, this highlights how brands are experimenting with applications like automated customer responses, call summaries, and issue classification.

Yet, no single use case is leading the way, with only five percentage points separating the most- and least-widely deployed GenAI in the contact center application.

Likely, this is because CCaaS and CRM vendors are building each of these into their platforms so businesses can easily augment their workflows with GenAI.

Moreover, it is already happening in the background, often without contact center leaders recognizing it.

In making this point, Baker Johnson, Chief Marketing Officer for UJET, reflected in the content creation for virtual agents use case, as included in the chart above. He stated:

“There is a misconception that generative AI and conversational AI are mutually exclusive. In reality, they can complement each other for more effective outcomes.”

Those go beyond content creation. Consider Google Dialogflow. The conversational AI platform offers a “Generative Flows” feature that allows developers to write – in natural language – what tasks the virtual agent should perform, and it’ll try to replicate that. There is no need to build decision trees.

However – alongside CCaaS and conversational AI platforms – GenAI is augmenting many other contact center systems to unlock more positive customer, employee, and business outcomes.

The chart below exemplifies this, with customer feedback platforms leading the way.

Perhaps this is not a surprise, as large language models (LLMs) – which power GenAI – can consume large feedback pools, surface trends, and feed these through as concise takeaways.

Moreover, knowledge management is another critical arena for GenAI, spotting gaps in the knowledge base and auto-creating content to plug them.

Finally, consider employee experience. As GenAI starts to augment workforce engagement management (WEM) solutions, expect more applications to come to the fore.

Already, use cases include isolating coaching opportunities, adding context to automated quality scores, and alerting supervisors to agent issues.

The Biggest Benefits and Challenges of GenAI Implementations

Each GenAI use case brings unique benefits. Yet, contact centers primarily look to the tech as a means of enhancing customer service and improving customer satisfaction – as per Metrigy.

After enhancing those outcomes, making agents more efficient, generating more revenue, and saving costs are the most predominant reasons for implementing the tech.

GenAI allows contact centers to meet these objectives, especially the latter.

Indeed, the research shows how some organizations have experienced a decrease in the number of contact center licenses they’ve had to purchase for 2024 – as the chart below shows.

Of course, there is likely more than GenAI at play here. Yet, according to Gareiss, it is a significant driver of this downward trend. She said:

“Generative AI, particularly in content creation, is highlighted as a factor contributing to the reduction in hiring, especially in tasks like web chat and after call work (ACW).”

Yet, despite these big benefits, concerns over GenAI in the contact center still run rife.

These concerns cover many bases, with accuracy of responses, data privacy, data source selection, internet bias, malicious use, job displacement, and the perceived newness of the technology all weighing on the minds of business leaders.

Thankfully, many trust-building strategies are coming to the fore. Chiefly, these involve limiting the data generative AI uses to create content and ensuring human oversight in content creation.

Kickstart Your Contact Center GenAI Journey with UJET

According to G2, UJET has the highest NPS score across the CCaaS industry, with many customers lauding its mobile-first, reliable, and secure design.

As per the latter, UJET doesn’t store personally identifiable information (PII) in the contact center. Instead, it utilizes encrypted real-time data exchange to read and write interaction data to and from existing systems (usually CRM). That reduces the scope and complexity of data compliance.

This is critical as contact center GenAI feeds from high-quality, compliant data.

Moreover, UJET is infusing GenAI with its conversational intelligence, conversational AI, and agent-assist solutions – alongside others – so brands can start leveraging the technology in a safe, secure, and value-enhancing way.

To learn more about UJET’s CCaaS solutions, visit: ujet.cx

 

 

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