Partner perspectives: Genesys' resident AI expert on top contact center AI use cases

From creating art to diagnosing patients, generative artificial intelligence (AI) has its metaphorical hand in the evolution of just about every industry. The contact center is no different.

Yet for all of AI’s promise to deliver greater efficiency, personalization, and consistency to everything it touches, it continues to be met with apprehension. For some, this apprehension is based in fear. Organizations have valid concerns about the dark side of AI – when generative AI makes up facts or hallucinates. For others, the apprehension stems from a lack of technical and strategic knowledge. In other words, many organizations simply aren’t sure how to make the strengths of AI work for them.

Whether your organization is frozen by one — or both — of these fears, here’s some good news: In the contact center, AI’s potential isn’t just hype, it already has proven use cases. For the better part of a decade, AI has contributed to powerful improvements in call transcription, predictive analytics, and call routing, among others.

So, the challenge becomes, how do organizations equip themselves with the educational context they need to navigate the hype and find the right path forward? And, more importantly, which AI applications offer the most compelling benefits for the customer experience right now?

To help our readers better understand and assess the growing AI-enabled customer experience solution marketplace, we sat down with one of the leading AI experts in our partner landscape, Tim Friebel, to get an external perspective on the present and future of AI in the contact center. As the Global Experience Transformation Lead at Genesys, Friebel helps organizations establish their experience orchestration vision, including automation and AI strategies that personalize customer experiences and reduce costs.

TTEC Digital: First things first, what’s new and what’s not when it comes to AI in the contact center?

Friebel: Well, we’ve actually been using AI for a long time in the contact center at Genesys. Obviously, ChatGPT sparked everybody's interest at the beginning of the year to see how they can use generative AI, specifically. But we've been using conversational and predictive AI for several years.

So, if you think about the Gartner Hype Cycle and generative AI, some of those things we're now finally to the point where we're being productive. But customers have seen real value from the AI that we've had in the platform for years to help them automate tasks and generate insights.

TTEC Digital: Can you give us an example of some of the automation and insight use cases you’re seeing have the biggest impact?

Friebel: One that is top of mind is self-service automation. It’s really all about how we understand a customer's intent with conversational AI and then present self-service options back to the customer to allow them to serve themselves.

From a business value standpoint, this can be immensely helpful. If you're thinking about the contact center, we typically see that agent interactions are probably costing a business $10 every time an agent has to handle an interaction. So, that's some of the very real value right there. Now you're able to execute self-service in a more conversational, intuitive way.

I think the other key area is around predicting outcomes. For example, let’s say we’ve determined that a customer is on a mobile device, and they're likely to make a purchase. But then, with the help of AI we discover the probability of them completing that activity suddenly decreases. Now we know that, and we're able to act accordingly. We can create next best actions that are designed to complete the sale and unlock incremental revenue generation.

TTEC Digital: For organizations that may not be sure where to start their AI-enabled CX journey, which use cases provide the best jumping-off point?

Friebel: Some practical guidance I love to share is this: Democratize knowledge, automate simple interactions, and if we do need to escalate to a live agent, target the best one for the job.

To elaborate on that a bit, businesses have all this knowledge or FAQ data out there. Making it automatically available to both customers and agents can significantly increase self-service rates, reduce agent handling time, while also increasing customer satisfaction since they’re quickly getting the information they need.

In addition to providing those FAQ responses, another “low-hanging fruit” example of automating simple interactions is providing status on outstanding items like an insurance claim or order status, etc. Many organizations are still routing these types of interactions to agents without allowing customers to self-serve. You’re not going to contain all these interactions, but if you can conservatively remove 10-20% of them it can have big business value.

On the flip side, when we do need to escalate to an agent, let's target the best person. In these cases, we can use machine learning to predictably route the interaction to the best agent to handle this customer's specific need. Doing these three things frees up agents from handling the repetitive, mundane, interactions and lets them do what they do best, which is empathetically listening to customer concerns and providing the human touch.

AI as an ongoing initiative, rather than a one-time investment

Whatever your initial AI investment looks like, one thing is for certain: AI is an ongoing commitment that will require refinement over time to continue to extract maximum value. A partner like TTEC Digital can help make sure your initial AI investments don’t become a deployment burden as AI best practices evolve. Through our proven AI-enabled CX Model, we’ll work alongside your team to set up a custom strategy, build a powerful set of solutions across both the customer and agent experience, and optimize performance over time. This way, your operation can stay at the cutting edge of AI-driven efficiency – delivering solutions that are worthy of your customers and agents and focused on outcomes.