Beyond optimization: 5 steps to AI that solves customer problems
Path toward a reimagined contact center
The state of AI in contact centers is at a critical juncture. Generative and agentic AI have forever altered the CX tech landscape and presented a new set of choices for customer service leaders. After incorporating a bevy of AI solutions to improve efficiency in recent years, they now face a fork in the road. Down one path is the familiar strategy of continuing to optimize existing processes with AI. This path has its charms. It’s well-trod and offers predictable rewards.
The other path is new, only recently created by the rapid evolution of generative and agentic AI. This path enables bold steps to radically transform the way the contact center operates. It might be unfamiliar, but it leads to spectacular benefits. Instead of incremental improvements with basic automation and agent support, it offers a more substantive transformation with generative AI agents that are capable of resolving customer issues independently.
At a recent Customer Contact Week (CCW) event, Chris Arnold, VP of Contact Center Strategy for ASAPP joined Wes Dudley, VP of Customer Experience for Broad River Retail (Ashley Furniture) to discuss this fork in the road and what it takes to travel the new path created by generative and agentic AI. Their conversation boiled down to several key points that translate into straightforward steps you can take now to start down the path toward a reimagined contact center that delivers much bigger benefits for the business.
You can also listen to the full conversation moderated by CCW's Managing Director of Events, Michael DeJager.
Step #1: Understand your customer journeys and pinpoint what’s not working
Up to this point, the primary goal for AI in the contact center has been to make existing processes faster and more efficient. While efficiency gains provide incremental benefits to the bottom line, they often do little to improve the customer experience. Simply swapping out your current tech for generative AI might buy you yet another small efficiency gain. But it won’t automatically improve the customer’s journey.
A better approach is to incorporate generative and agentic AI solutions where they can make a more significant impact. To do that, you have to pinpoint where the real problems are in your end-to-end customer journeys. That’s why mapping those journeys is a critical first step. As Wes Dudley explained,
One of the first things we did is start customer journey mapping to understand the points in our business of purchase, delivery, repair, contacting customer service. With that journey mapping with all of our leaders, we were able to set the roadmap for AI.
By identifying the most common pain points and understanding where and why customer journeys fail, you can explore how generative and agentic AI might be able to address those problem areas, rather than simply speeding everything up. As a first step, you don’t have to map everything in excruciating detail. You just need to identify specific issues that generative and agentic AI can solve in your customer experience. Those issues are your starting point.
Step #2: Make your data available for AI
There’s a lot of focus on making your data AI-ready, and that’s crucial. But too many customer service leaders interpret that message to mean that their data must be pristine before they can count on generative AI to use it well. There are two problems with that interpretation. First, it creates a roadblock with a standard for data integrity that is both impossibly high and unnecessary. The most advanced AI solutions can still perform well with clean but imperfect data.
The second problem with this narrow focus on data integrity is that it overlooks the question of data availability. An AI agent, for example, must be able to access your data in order to use it. As Chris Arnold noted,
We're finally to a place where if you think about the agents' work and the conversations that they manage, agentic AI can now manage the vast majority of the conversation, and the rest of it is, how can I feed the AI the data it needs to really do everything I'm asking my human agents to do?
Ensuring that your data is structured and complete is only part of the availability equation. You’ll also need to focus on maintaining integrations and creating APIs, which will allow AI solutions to access other systems and data sources within your organization to gather information and complete tasks on behalf of your agents and customers. By all means, clean up your data. At the same time, make sure you have the infrastructure in place to make that data available to your AI solutions.
Step #3: Align stakeholders and break down silos
AI implementation isn’t just about technology—it’s also about people and processes. It’s essential to align all stakeholders within your organization and break down silos to ensure a unified approach to AI adoption. As Chris Arnold explained, “Historically, we've [customer service] kind of operated in silos. So you have a digital team that was responsible for chat, maybe for the virtual assistant, but you've got a different team that's responsible for voice. And you create this fragmented customer experience. So as you're laying out the customer journey, begin with the customer in mind, and say, what are all the touch points? Include the website. Include the mobile app. Include the IVR. We no longer have to operate in silos. We shouldn't think of voice versus digital. It's just one entry point for the customer.”
If your goal is to continue optimizing existing processes with AI point solutions, then aligning stakeholders across the entire customer journey is less critical. You can gain efficiencies in specific parts of your process for digital interactions without involving your voice agents or the teams that support your website and mobile app. But if your goal is to achieve more transformative results with generative and agentic AI, then a holistic strategy is paramount. You’ll need to bring together all of your stakeholders to identify the key touchpoints across the customer journey and ensure that AI is integrated into the broader business strategy. This collaboration will help ensure that AI is used to complement existing technologies and processes in a way that yields measurable results for both the bottom line and the customer experience.
Step #4: Embrace the human-AI collaboration model
Much of the work that AI currently performs in contact centers is a supporting role. It offers information and recommendations to human agents as they handle customer interactions. That improves efficiency, but it doesn’t scale well to meet fluctuating demand.
One of the most exciting developments in AI for customer service flips the script on this dynamic with AI agents that handle customer interactions independently and get support from humans when they need it. ASAPP’s GenerativeAgent can resolve a wide range of customer issues independently through chat or voice. It’s also smart enough to know when it needs help and how to ask a human agent for what it needs so it can continue serving the customer instead of handing off the call or chat.
“We are of the mindset that, without exaggeration, generative agents can replace 90% of what humans do – with supervision,” says Arnold. “So maybe you don't want your customers to be able to discontinue service without speaking to a human. GenerativeAgent can facilitate the conversation… but it can come to the human-in-the-loop agent and ask for a review so that the [AI agent] doesn't get stuck like it does today and then automatically escalate to an agent who has to then carry on the full conversation. We can now commingle the [GenerativeAgent] technology, the GenerativeAgent with the human, and you can have just about any level of supervision.”
Right now, we have AI that supports human agents. As we move forward, we’ll also have humans who support AI agents. As the human-AI balance shifts toward a more collaborative relationship, we’ll see radical changes in processes, workflows, and job functions in contact centers. The sooner you embrace this human-AI collaboration model, the better equipped you’ll be for the future.
Step #5: Get started now
The future of customer service won’t just be elevated by AI. It will be completely redefined by it. Contact centers will look – and function – very differently from the way they do now. And this future isn’t far away. We’re already at the fork in the road where you have a clear choice: stick with the familiar strategy of using AI to optimize existing processes, or take steps toward the future that generative and agentic AI have made possible. The path is there. It’s just a matter of getting started. You don’t have to do it all at once. You can go one step at a time, but it’s time to take that first step.
As Chris Arnold said at CCW,
Do it now. Don’t wait. Don’t be intimidated. Start now. Start small because all of us who have worked in the contact center for a long time, we know that small changes can lead to great big results. Just start now.