Everyone's Talking About AI Strategy. No One's Talking About AI Grief. I just finished working with a leader in the home improvement industry. The executive team is beyond excited about their new AI bot that will help associates in the field engage with customers, giving them prompts, suggesting responses, and helping solve complex problems. From the executive standpoint, this is a game-changer. From the associates' standpoint? They're terrified. Because they think they're training their own replacement. The executive told me: "We need help getting our people to embrace this change and be inspired to use it. We're looking for their alignment, not necessarily their agreement." That's when it hit me: We're asking people to embrace technology that feels like it's replacing their identity. And we're shocked when they resist? Here's what every AI leader is missing: Before people can get excited about AI's potential, they need space to grieve what feels like it's ending. Their expertise. Their relevance. Their sense of being needed. These associates are feeding customer conversations into this AI system, watching it learn from their interactions, building data on everything they know how to do. Of course they think they're planning their own funeral. The fear is real. The grief is valid. The most successful AI implementations I've seen start with this conversation: "What do you love most about your current work? How do we use AI to give you more time for THAT?" Not: "Here's how AI will make you more efficient." But: "Here's how AI will make you more human." Your team's resistance to AI isn't about the technology. It's about what they think the technology means about them. Address the grief first. The strategy will follow. How are you helping your people process what AI transition feels like? ♻️ Repost if you believe AI transformation is emotional transformation 🔔 Follow for insights on leading humans through technological change
Overcoming Resistance To AI In Customer Support
Explore top LinkedIn content from expert professionals.
Summary
Overcoming resistance to AI in customer support involves addressing the emotional and practical concerns of teams who fear being replaced or disrupted by technology. Building trust and highlighting AI's collaborative potential are key to ensuring successful adoption.
- Start with empathy: Recognize and validate team members' fears and focus on how AI can enhance their work rather than replace it.
- Co-create solutions: Involve customer support teams in the design and implementation of AI tools to ensure they align with daily workflows and address actual pain points.
- Showcase benefits: Demonstrate how AI can make their work easier, like handling repetitive tasks, so they can focus on building meaningful customer relationships.
-
-
There is an implementation trap with AI that few are talking about and I wanted to bring it up. Specifically, how two teams experience the same tech, but in two realities. Here’s the scenario that leaders need to look out for: Let’s say your company’s CX team rolls out AI orchestration with clear goals: unify data, automate touchpoints, and reduce friction across the customer journey. (I’d go more specific but let’s keep it high level for the sake of simplicity.) From the CX Team’s view, this is a strategic win. “We’re finally connecting the dots.” “This gives us real-time visibility and faster resolution.” “We can drive proactive service, not just reactive triage.” But in the contact center? “This thing is pulling tickets off our queue.” “I have to bounce between more tools now.” “Why weren’t we part of this decision?” Same rollout. Completely different realities. That’s the miss in most change efforts. Context is everything. The CX team sees orchestration as an upgrade. The contact center sees it as disruption. And unless you understand both perspectives, you don’t get transformation. Instead, you get tension. An important point here is that emotional reactions aren’t resistance. They’re system feedback. They tell you where the friction lives. Where the incentives don’t line up. Where the design skipped the people doing the work. If you want AI implementations to be successfully implemented, it starts with this: Co-design the change with those it impacts. Build for team workflows impacted by the tech, not just those customers see. Use the emotional signals like frustration, anxiety, and hesitation as diagnostic tools. Because when the context is ignored, the system will definitely let you know and push back! I see this all the time. And while AI Is exciting and people are starting to lean into the tech, the simple reality is that it’s still about people. People > Tech #customerexperience #ai #changemanagement #contactcenter #changemanagement #changeleadership
-
Customer service teams often hear that AI is here to "replace" them, but I’ve always believed it’s here to empower them. Recently, I had the privilege of working with a team that felt overwhelmed by the rise of AI tools in their daily workflows. Their biggest concern? Losing the personal touch that makes their brand special. Here’s how we turned that fear into excitement and success: I showed the team how AI could become their co-pilot, not their competitor. --Together, we worked on creating email responses that were: -More friendly: AI tools helped us strike a warm tone while maintaining professionalism. -Easier to read: We refined complex responses into clear, straightforward messages. -Concise: Long-winded emails became focused and impactful. -Aligned with their brand voice: By training the AI tools to understand their unique style, the team ensured every message felt authentic. The result? Happier customers, faster response times, and a more confident team that felt in control of the AI, not the other way around. What truly inspired me was seeing how quickly the team embraced this technology once they saw how it amplified their strengths rather than replacing them. AI isn’t here to take the "human" out of customer service. It’s here to make our human efforts even better. Have you or your team started using AI in your customer service workflows? I’d love to hear about your experiences or answer any questions you have!