Greg interviewed for SearchUnify: The Future of Frictionless Loyalty: Navigating the Shift to an AI-Operations Layer
Greg Kihlström was interviewed for SearchUnify about the role of AI adoption in customer loyalty and how “frictionless loyalty” can be driven by an AI-operations layer. Here is the original article.
Excerpt:
Greg, you’ve noted that AI adoption is being undermined by “psychological debt”—the cognitive and identity costs to employees. As brands integrate AI across the Customer Experience journey, how can leaders design these systems to augment human judgment rather than making teams feel like their professional expertise is being sidelined by an algorithm?
The “people problem” in AI adoption usually signals operational misalignment. When official tooling lags the work, teams improvise. That improvisation reflects a rational response to being asked to automate around contradictions the enterprise has yet to resolve. I’ve watched plenty of well-funded AI rollouts stall here.
Fortunately there are some design decisions you can make to keep humans-in-the-loop. This pays dividends not just in results but also in adoption and execution of the task at hand. Firstly, treat the ability to opt-out of intelligent-execution as a first-class capability. Make it as expected, fast, and respected as clicking submit. Make decision rights explicit. Record what the agent can do by themselves, what gets escalated, and who owns exception escalation workflow. Track direct adoption of new capabilities. Percent completion won’t tell you much about if your new capability is sticking in your customer-facing operations. If you want to build a knowledgeable culture that gets what you’re doing with your automations and knows how to execute alongside them, treat enablement like a Sustained Operation. Line it up with your platform change cycles.
The teams that adapt fastest move their expertise up the stack into system stewardship: designing prompts, governing exceptions, improving orchestration. Their authority grows in the process.