Featured Guest: Darren Smith
In this episode of The CustomerX Files, Alison sits down with Darren Smith, CTO at Point of Reference, for a candid, behind-the-scenes look at how AI is reshaping the world of Customer Advocacy and Customer Marketing. This conversation is packed with practical, real-world insights. Darren shares powerful ways AI can elevate your day-to-day work.
Artificial intelligence is no longer a distant concept or futuristic tool — it’s becoming embedded into everyday workflows, customer interactions, and marketing strategies. Yet with its rapid adoption comes a real concern: how do we integrate AI in ways that enhance our work instead of diluting the empathy, nuance, and authenticity that only humans can bring? In this episode, Darren and Alison unpack this complex balance, walking through both the opportunities and the guardrails necessary for success.
Darren brings a unique perspective as a technology leader deeply embedded in the technical evolution of customer advocacy. He and Alison unpack how AI is currently being used behind the scenes to accelerate processes — from data retrieval and analytics to personalization and predictive insights — and they emphasize that AI’s true value lies not in replacing humans, but in augmenting the work humans already do best.
Throughout the episode, Darren and Alison emphasize a simple but powerful principle: AI should be treated as a tool — not a replacement — for what humans do best. They explore how customer marketers and advocacy leaders can use AI to enhance program outcomes without losing sight of the personal relationships that drive long-term engagement and loyalty.
Listeners will find real-world examples of where AI can be applied thoughtfully and where caution is warranted. Darren discusses how AI can support teams by:
But this episode doesn’t just focus on the “what” it also digs into the “how.” Darren offers thoughtful guidance on questions like:
By sharing actionable examples and thoughtful frameworks, Darren helps demystify the role of AI in customer advocacy and marketing while reinforcing that human intuition, empathy, and relationship building remain irreplaceable.
Whether you’re just beginning to explore AI tools, or you’re already integrating them into your day-to-day operations, this episode will expand your thinking and equip you with strategies to use AI responsibly and effectively — without losing the humanity that makes your customer programs meaningful and impactful.
Listen now to gain practical insights on how to strike the right balance between intelligent automation and human connection — and discover how AI can be a strategic enabler, not a substitute, in your customer engagement journey.
It's only natural that many advocacy leaders have landed on the same objective: make the program easier to use by meeting users where they're already working.
Today, that increasingly means Microsoft Copilot, ChatGPT, Claude, Gemini or whatever generative AI assistant employees happen to have open.
Imagine a salesperson simply asking AI, "Find me three German healthcare customers using product Y, willing to speak with a prospect," instead of navigating to another interface, or waiting for someone from advocacy, or elsewhere, to respond. It's easy to see the appeal. Removing friction has always been one of the fastest ways to increase adoption.
It is exactly the right instinct.
The difficult parts, arguably the reason program managers exist, occur before and after AI says, "Here are your three best matches."
The value advocacy professionals bring is the ability to operationalize and scale customer advocacy for maximum impact. Quality advocate information doesn't just appear, it's the result of a system.
Now that the user has three advocates, what should happen?
Notice what happened. The search was completed.
The next steps are just as manual as ever if AI search is the be all, end all.
Reality Check
AI can tell you who could participate. It can't tell you who should participate unless someone (or something) has been keeping score.
This is where the story starts to feel strangely familiar.
Many companies still operate their program using spreadsheets, scattered CRM fields, shared drives, email folders, and the remarkable memories of a handful of program managers.
Eventually, organizations realize they aren't managing an advocacy program at all. They're managing lists that happen to contain advocates.
But the shortcomings are real:
Purpose-built advocacy platforms emerged because advocacy is much more than a search problem.
Ironically, AI has convinced some organizations to revisit the same shortcut they worked so hard to escape.
Let's imagine two different worlds.
In the first, AI recommends an advocate for a sales call.
Months later, AI knows this customer recently participated and may deserve a break before being asked again.
Now imagine the second world.
Three months later someone asks how many customer reference contributed to the revenue this quarter.
Silence. Nobody really knows.
The advocacy happened...hopefully. The program didn't. Collectively, the organization slowly stopped feeding the very system it depended on to understand its advocacy program.
Reality Check
If AI helps facilitate twenty closed-won opportunities this quarter, but none are recorded, your executive dashboard still says zero.
One of the easiest mistakes to make in an AI-first world is assuming that successful interactions somehow become organizational knowledge on their own.
They don't.
If a customer agrees to speak with a prospect and nobody records it, the organization loses far more than a single activity.
The most valuable advocacy data isn't simply who your customers are.
It's everything they've done.
That's the story AI actually wants to read.
It's often said that AI needs good data.
That's true.
But operational history is far more valuable than static customer information.
Those aren't search results.Those are patterns.
Remove any one of those pieces and AI becomes little more than an exceptionally fast search engine.
Reality Check
Every workflow skipped today is a pattern AI won't discover tomorrow.
The AI revolution has created tremendous excitement, and rightly so. Finding the right advocate is becoming dramatically easier than it was only a few years ago.
That's worth celebrating.
Just don't confuse a better search experience with a better advocacy program. Search is only one chapter in the story.
The organizations that see the greatest return from AI won't necessarily be the ones with the most sophisticated models.
They'll be the ones with the richest operational history.
Those organizations won't use AI merely to answer the question, "Who should we ask?"
They'll use AI to answer far more valuable questions.
That's when AI stops behaving like a better Google search.
That's when it starts behaving like a strategic partner.
Finding the right advocate has always been the opening scene.
If your AI can find advocates but your program can't learn from using them, you've built a remarkable search engine instead of a remarkable advocacy program.
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