How should leaders go about adopting AI in customer support? Start with curiosity, not judgment. AI arrived with a full spectrum of emotions: excitement, optimism, fear, annoyance, bitterness. When those emotions drive evaluation, implementation and adoption, they become self-fulfilling prophecies. If we expect AI to solve everything, we’ll overlook where it falls short. If we resent its arrival, we’ll only find proof it doesn’t work. The best results come when leaders approach AI as students of the technology: open-minded, curious, and willing to test assumptions. That mindset makes it easier to see real opportunities and real limitations. Start now. There is no future where AI quietly goes away. That would be like undoing the internet. This means knowing how to deploy a chatbot, build and use AI-assisted workflows, or implement background automations that improve both efficiency and experience is quickly becoming a basic qualification for CX leaders. In addition to job expectations, as brands adopt AI successfully, customer expectations rise with them. If you, or your organization, isn’t experimenting yet, it’s time. Play with what you already have. Your ticketing and telephony platforms likely have AI capabilities sitting unused. These are ideal places to explore and learn without a long evaluation cycle, scary invoice, or pressure to prove immediate ROI. Low-risk experimentation will build confidence and AI-fluency while exposing areas of opportunity for more sophisticated technologies. Set your AI compass. There’s dozens of ways customer service teams can implement AI, and new solutions, features and capabilities are launching everyday. After a few successful rollouts, it can be tempting to seize all the AI opportunities with All The Things meme enthusiasm. Except they won’t all fit your business, customer, or service philosophy, risking diminished customer experience and operational efficiency. Know the purpose and goal for each AI launch. Rework workflows if they’re not giving you the results you intended, and choose to not launch features that don’t align with your goals. Have a solid change-management strategy. AI changes how work gets done, which means adoption can’t be handled with a single announcement or training session. Leaders need an early and clear communication plan, strong team buy-in, open feedback loops, and mechanisms to encourage and reinforce adoption. When teams understand why AI is being introduced and see tangible benefits from it, the change sticks.
