My current theme as an ICMI Contributor is strategic planning, something that CX leaders need to be doing as they seek to modernize their contact centers. No matter how far along that path you are, there are many forms of technology change (AI being just one of them) and they are happening at a pace we’ve never seen before. Modernization is an ongoing process, and not just a matter of fixing one thing, or adopting one new application.
Strategy is about having an overall plan, and not a series of isolated responses as each wave of technology change hits the contact center. It’s also about anticipating what’s coming, along with how you intend to respond. AI has essentially been imposed on the contact center, and even though you’ve been trying to modernize prior to AI’s rise, this environment brings both new challenges and opportunities.
In my last article, I talked about there being two core objectives for deploying AI in the contact center: improving customer service, and optimizing operational performance. That article focused on the former, and now we’ll shift to the latter. Operational performance is internally focused, little of which the customer ever sees.
AI strategy here will largely be about creating efficiencies, but ultimately this must translate into better CX. As such, your planning needs to be intentional, and not just a checkbox to satisfy senior management demands for adopting AI. Striking this balance will not be easy; hence the importance of being strategic.
To that end, here are two foundations for developing your AI strategy. They are the same foundational pieces as with my previous post — setting priorities and expectations — but now framed for how AI can be used for internal operations.
Foundation 1: Setting priorities for AI
Part of what makes AI transformational is the way it impacts every aspect of both the contact center and the customer experience. While AI can be deployed as a point solution to address a specific problem set, its strategic value comes from having a holistic impact on the entire operation. This means taking a through line from how operational improvements directly lead to better CX outcomes.
For decades, operational performance has been defined by a well-established set of KPIs, largely focused on how efficiently agents handle customer inquiries. These metrics provide value for their intended purpose, but with CX now becoming a strategic priority for the business, they don’t provide much value for what happens outside the contact center, especially on the CX side of the equation.
In terms of setting priorities for AI to improve internal operations, a different focus will be needed. Conventional KPIs still have value, but greater value will come from new metrics that connect the dots from AI-driven operational improvements to CX gains. Rather than focus on maximizing agent productivity, the priority should be on how AI can automate internal processes and workflows, not just for the sake of automation, but rather for how automation will free up agents to have deeper engagement with customers to provide more personalized forms of service.
This represents a different way of thinking for many CX leaders, and the starting point is breaking with convention where AI is only seen as a tool to modernize existing ways of doing things. Before you can define new metrics for measuring AI’s impact on operations, CX leaders must recognize that different priorities are needed to get the more impactful benefits from deploying AI.
Foundation 2: Setting expectations for AI
Setting priorities is an essential first step with AI, not just because there are valid use cases for every aspect of contact center operations, but also because some deployments will be easier to do than others, and some will yield tangible benefits faster than others. All of these must be considered when setting priorities, and the same holds for setting expectations.
Since CX leaders will be driving their AI deployments, the setting of priorities will reflect what’s most important to them. Success for those priorities; however, will largely rest on getting support and buy-in from other stakeholders, especially top management, IT and contact center personnel. This is where setting expectations is critical, especially with AI being so new.
While it may be clear to CX leaders how AI will impact operational performance, it may not be to this set of stakeholders. Aside from the fact that most will only have a cursory knowledge of AI, they may still be grounded in conventional contact center thinking where KPIs remain the standard for measuring performance.
This is where the above “break-with” reference is so important. Some stakeholders might view AI as a silver bullet that magically fixes everything, but they may only view this from the lens of legacy KPIs. New thinking is needed in these cases, and setting expectations here is about connecting the dots between intentional operation improvements and better CX outcomes. This bigger picture is what makes AI strategic, and you won’t be able to address that if expectations are little more than maintaining the status quo for contact center operations.
Conclusion
Over the course of my three posts about strategy, I have outlined the need for CX leaders to take a strategic approach for adopting AI. All forms of new technology require a strategic response, but none more so than AI. Conventional contact center technologies remain widely-used, but they were designed for a time where deployments were static and had long lifespans. Cloud platforms turn that model on its head, and now with AI, nothing stands still.
With constant change being the norm, strategy needs to be about setting priorities and expectations around what forms of AI to deploy, along with what outcomes are the most important. As noted earlier, there are AI use cases across the entire spectrum of contact center operations and CX, so a shotgun approach to AI will not be effective.
Just as there is a distinct set of use cases and outcomes for improving customer service, the same holds for improving internal operations. Similarly, each requires setting distinct priorities and expectations since all contact centers operate with limited resources. Putting all of this together is the essence of a workable strategy, and this series of articles serves as foundational thinking for CX leaders as they go down the adoption path with AI.