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New Data Shows How Business Leaders Think Gen AI will Change Contact Centers

Contributed article by Aaron Schroeder, Director of Analytics and Insights at TTEC Digital

As the hype around generative AI – and AI in general – rapidly approaches the one-year mark, many businesses still aren’t quite sure what to make of it. Is generative AI actually mature enough to unlock unprecedented efficiency and productivity, or does the reality of what it can deliver today still fall short of the grand vision businesses are being sold?

The overwhelming sentiment seems to be to wait and see. Earlier this fall, Gartner’s latest AI hype cycle confirmed this mindset when it placed generative AI at the very top of its peak of inflated expectations. Yet, within this broad category, there are exceptions where the gap between generative AI hype and reality is not as far apart as it may seem.

The contact center is a prime example of this.

In an environment so hyper-focused on conversations between brands and customers, the conversational abilities of generative AI tools built on advanced large language models are an immediate game changer. Paired with a set of growing challenges like evolving customer experience expectations, limited IT budgets, and an explosion of customer service channels, it’s clear contact centers desperately need to find new ways to become more efficient – or risk losing out to competitors.

A recent TTEC Digital report suggests businesses agree AI can help them solve these challenges. Many contact center operations have already invested in AI to infuse differentiated value into the customer experience, and 2024 is poised to bring an explosion of new AI investment.

With that in mind, let’s dig a little deeper into these two observations from the report.

Observation #1: AI is already deployed in many contact centers today.

First things first. AI is not new in the contact center. In fact, some of the leading contact center operations teams have already been using AI for a number of years to help automate simple tasks. What is new is explicit investment in AI as a tool to support a variety of contact center objectives.

What do I mean by that? Until recently, AI adoption occurred behind the scenes, embedded in existing contact center platforms and workforce management tools. For example, maybe a contact center has been transcribing customer conversations and mining those transcriptions for topic trends or automating certain aspects of the agent experience simply by “toggling on” features in their current Contact Center as a Service (CCaaS) platform.

As a result, our assessment of AI investment has focused on ad-hoc deployments such as sentiment analytics (34% of respondents), speech-to-text (29%), and desktop automation (20%). Organizations have generally not taken the time to spell out clear goals for AI or establish clear guardrails for its usage. This is where CX leaders have the most room for growth as they prepare for a more intentional wave of AI adoption.

Observation #2: New AI investment is focused on generative AI use cases that support CX at the point of conversation.

As contact centers plan for generative AI, they’re taking a more strategic approach. While nearly every application of AI is set to see growth in 2024, our assessment found that four use cases are poised to take the biggest leap:

• Proactive knowledge management
• AI-generated responses
• Post-interaction summarization
• Language translation

So, what can we take away from this? We’re seeing contact centers decide to focus their efforts on AI-enabled CX transformation at the point of conversation with their customers. They want to solve questions like:

• How can we help agents to answer better, faster, more comprehensively?
• How can we better segment customer conversations between live agents and virtual agents?
• How can we speed up post-call agent responsibilities to allow agents to quickly move to new customers?
• How can we engage more efficiently with global customer audiences?

In a modern CX environment where the quality of the customer experience can determine customer loyalty, satisfaction, and more, generative AI offers a new way to directly support these high-value touchpoints and build a customer experience that stands out.

How to Use AI to Create Your Customers’ Next Best Experience

If our assessment is any indication, AI-enabled experiences are the next frontier in CX – which means AI could soon become a key differentiator for those organizations that find a way to use it to deliver the experiences customers crave.

Here are a few recommendations to jumpstart your own AI journey at the point of conversation:

1.      Find your AI target areas with value chain mapping. If your organization already uses customer journey maps, take a look at those customer journeys as a starting place to identify which gaps currently exist. Ask questions like: Where are customer conversations occurring? What are the most common conversations about? How can your organization maximize these interactions? With outcomes in mind, it can become easier to decide which use cases are worth exploring.

2.      Get your data in order. Data privacy, security, and quality were rated the top barriers to entry when our assessment asked respondents what was standing in the way of their AI adoption. This should come as no surprise. After all, poor data coming in means poor insights going out. Before you put AI to work, prepare your data first. For each AI application, make sure that you have activated the right data sources and that the LLM you are using to support generative AI initiatives has been fine-tuned to reflect your brand’s industry, key topics, and customer experience use cases.

3.      Move quickly to deploy pilots – then focus on testing and measurement. AI is advancing rapidly, so it’s going to be important to test, grow, and evolve in real-time, over time. Hoping to implement AI once and see consistent, strong results in perpetuity is simply not realistic. At the same time, waiting to implement until all the possible applications for generative AI have been solved means it will already be too late. Most of your customers won’t wait around long enough for you to catch up.

Instead, start building AI-enabled experiences now and focus on continuous improvement as technology and customer expectations evolve. Not only will this help your operation unlock benefits right now, but it will also prepare your CX team to quickly introduce new AI applications that can inspire your customers’ next best experience over and over again.

Aaron Schroeder is director of analytics and insights at TTEC Digital, one of the largest global CX technology and services innovators. The company delivers leading CX technology and operational CX orchestration at scale. TTEC Digital’s 60,000 employees operate on six continents and bring technology and humanity together to deliver happy customers and differentiated business results. Download the State of AI in the Contact Center Report here.