You Can Automate Growth. You Can’t Automate Loyalty.

Last week at the gym, I ran into someone from my community. He asked how I was doing, and I was candid that I was looking to take on more clients. When I asked how he was doing, he told me he had just launched a new podcast—about AI.

I suggested, enthusiastically, that he interview me. I use AI tools in my work every day. He dismissed the idea almost immediately, explaining that he was interviewing “AI people”—people from AI companies—not people who use AI to do their work. I understood the instinct. Titles feel like authority, and proximity to well-known technology companies often creates more (perceived) weight than lived experience.

But the exchange illustrated something I see frequently: the gap between talking about AI and actually using it.

I explained to him that my experience with AI goes well beyond writing assistance or research tools, which I always double-check and cite. For over a decade, I’ve worked in environments where AI—or its earlier forms—was embedded directly into the systems that made the business function. At Globetouch, the telecom infrastructure relied on ocular scanning and automated service connectivity, allowing drivers to move seamlessly from one service provider to another, across regions and countries without losing access to support. At CEB, I helped lead marketing efforts during the migration from analog content to digital platforms, a transition that depended on natural language search to make their California case law content libraries usable. At WM, I was fascinated by the machine learning of recycling processors—technology that didn’t just identify materials, but learned how to separate them more accurately, improving worker safety, and increasing material acceptance by more than 20 percent in just a few years.

He paused and acknowledged that I clearly understood AI. He still wasn’t interested in interviewing me. I wasn’t an AI technologist; I was “just” an actual user.

I may not be an AI technologist, but I’m also not just talking about it. My perspective has been shaped by working alongside systems where automation and machine learning were embedded into daily operations, not treated as abstractions or future promises. That experience has taught me both the power of these tools and the importance of understanding where their role ends.

On the flip side, while AI innovations unquestionably streamline work, create efficiencies, and expand what organizations can do at scale, they are still tools. They don’t create strategy, determine priorities, or decide when it’s time to pivot. They can accelerate execution and surface insights, but they cannot interpret nuance, weigh tradeoffs, or apply judgment in moments of ambiguity. Those responsibilities remain human, especially in B2B business.

Most importantly, AI does not manage relationships. It doesn’t build trust, navigate uncertainty, or restore confidence when something goes wrong. Human beings are still the ones who hold the customer relationship, who show up in moments that matter, and who create the conditions for people to stay—not because it is easy or efficient, but because it feels worthwhile.

This is where organizations may lose opportunities that bolster fidelity.

Growth scales systems. Loyalty scales trust.

Most organizations have become very good at building the mechanics of growth. They invest in tools, workflows, personalization engines, and automated journeys designed to reach people quickly and efficiently. These systems fill pipelines, generate leads, and produce metrics that are easy to monitor and optimize.

The mistake is assuming those same systems can produce loyalty.

Loyalty rarely breaks in dramatic moment; this is a separate article. Relationships erode quietly, when people stop feeling seen or understood. Engagement metrics begin to stand in for relationship health. Touchpoints replace conversations. Feedback is collected but rarely reflected back in meaningful change. Efficiency is optimized at the expense, or in lieu of presence.

Over time, customers feel interchangeable. Employees feel invisible. Commitments feel transactional. And when something better—or simply different—comes along, they leave.

Loyalty isn’t built through volume or velocity. It’s built through recognition, consistency, delivery, and trust over time. People stay when they feel remembered rather than processed, when their context is understood, and when questions are answered honestly—even when the answer is uncomfortable. Leadership presence matters most in these moments, not as messaging, but as engagement. None of these actions scale neatly, and that’s the point.

Organizations that retain loyalty don’t reject automation; they use it intentionally. They design systems that create space for real conversations rather than replacing them. They prioritize fewer, more meaningful touchpoints and build feedback loops that actually change behavior. They make leadership visible during moments of uncertainty, when human judgment matters most.

When loyalty is treated as a systems problem, the warning signs are easy to miss. Churn increases but is masked by strong acquisition. Tenure shortens while engagement scores remain flat. Trust erodes quietly, without a single metric to capture its loss. By the time leaders recognize what’s happening, the relationship is already gone. Numbers may talk, but people will tell you what’s really going on and if an organization is not connecting H2H, human-to-human, there’s little recourse.

If loyalty matters—to customers, employees, or customers—it must be designed deliberately. That means prioritizing human presence alongside performance and recognizing where technology supports the relationship rather than substitutes for it.

You can automate growth. You can’t automate loyalty.