CS Labs recap - Where do we go from here with AI?

Earlier this week at CS Labs by Sophie Conti , over 60 CX leaders gathered to explore the evolving role of AI in customer experience. We were fortunate to be more deeply involved alongside our team over at Crescendo ! It was a fascinating look at where we’re headed, and here are some of the most impactful insights:

Autonomous AI and the power of ecosystems

Maurice Conti introduced the concept of "agentic AI"—AI that not only assists but acts autonomously. He pointed out that companies like Apple, which control their ecosystem, have a distinct advantage in that they already have access across their platform and do not need to worry about integration or data clarity. In CX, this kind of AI means empowering tools to operate with little to no oversight, driving efficiency and innovation. This reinforces a broader vision: CX is the tip of the spear, setting the pace for other departments to follow. As CX teams, we should embrace our role in leading strategic direction, pushing the organization forward into this new landscape. We are the proving grounds before AI hits it big in other areas of the business–and that’s an exciting thing.

Metrics matter—good and bad

One of the most interesting discussions centered on tracking “counter metrics” for the negative outcomes as much as we track the positive ones. For example, alongside CSAT, many CX leaders are leaning on CES (customer effort score) because it’s something CX teams can directly impact. Tracking both positive and negative outcomes in parallel offers a clearer picture of what’s working—and what’s not. For instance, using things like containment rate, escalation rate, and intervention rate–these things are valuable alongside more traditional measures, and allow us to see if AI is doing what we expect it to be doing. However, be mindful to measure things that have a direct relationship to the performance of your human team. If you wouldn’t be measuring your human team’s “hallucinations” (aka fibs or general untruths) should you really be measuring your AI’s? It’s a call to be intentional in measuring impact, so we can avoid getting lost in the weeds and focus on metrics that align with customer outcomes and strategic goals.

The evolution of process

Over the past year, there’s been a lot of learning about which processes don’t serve us anymore—often by going down rabbit holes and testing new methods only to realize they aren’t effective. Many CX roles today are heavily focused on process, sometimes exclusively so. With AI in the mix, defining and refining processes has become critical, as it allows us to better understand what can be automated and where human oversight is essential. Leaders are embracing this trial-and-error approach, using it to pinpoint which workflows are worth investing in and which need to be rethought. However, as familiarity with AI grows, everyone is hopeful that this rabbit hole approach will diminish as, almost universally, folks recognize that time could be better used elsewhere beyond just endless pilots.

Building automation with intention

A popular topic was process automation, where we need to set realistic goals and make the automation meaningful. The advice? Start with a rubric to assess what’s automatable and what’s best left to human expertise. Above all, avoid the common pitfall of committing to long-term AI contracts before seeing proven ROI. Several leaders emphasized the importance of staying agile and open to changes, experimenting with shorter contracts or pilots to see what works best for your team and customers before making large investments. AI is constantly evolving and next year the landscape may be entirely different, so be mindful of how long you are committing to a tool that may not serve you once everything has changed.

Human + AI: an opportunity, not a threat

We’re seeing bots increasingly used as co-pilots, assisting agents with context and efficiency. While fully autonomous systems are less common, the door is open for AI to go beyond support and add value across teams. AI doesn’t necessarily mean replacing jobs; it’s creating career opportunities, allowing teams to focus on high-impact work. Leaders are beginning to view AI as a collaborative partner, reshaping CX roles for greater strategic input rather than just transactional support. There is hope here, but also some fear that this perspective is just rose-tinted lenses.

End-to-end implementation—beyond turning it on

One of the major gaps in AI adoption is not the technology itself but the end-to-end implementation. It’s easy to activate new tech; the real challenge is managing it fully, considering how it integrates with existing workflows, and understanding the ripple effects across hiring and staffing. Successful implementation means thinking through every step—from turning it on to optimizing how it works with your team and systems. A robust approach to integration can maximize AI’s potential to serve customers without missing a beat.The future of CX is heading toward agentic and augmented AI, where tools need to be more than just generative. They’ll have to work autonomously—or at least with minimal oversight alongside humans—to deliver real CX impact. This journey is both exciting and complex, and it sounds like everyone is looking forward to seeing how it shapes our field and beyond!

Thank you to Sophie, the other sponsors and, of course, all of the amazing participants for sharing their time and energy to make this an amazing event.