The hype around AI is loud, but the reality for marketers and customer experience leaders is much messier.
In a recent webinar, Forrester Senior Analyst Stephanie Liu cut through the noise to highlight what’s actually happening with AI, data, and personalization. Spoiler: most companies aren’t ready. And most consumers aren’t either.
Here are three truths that stood out, along with the practical implications for anyone building better customer experiences in the age of AI.
1. AI Won’t Fix Your Data Problems
The future of customer experience might be AI-powered, but it still depends on the same thing it always has: good data.
Marketers ranked “poor data quality” as their #2 barrier to delivering personalized experiences. But the real number one might just be data everything: access, latency, silos, gaps. The analyst made it clear: if your foundation is shaky, AI will only expose the cracks faster.
“AI needs high-quality data,” said Liu. I’ve had scary conversations where companies talk as if a chatbot can magically repair data issues. It doesn’t work that way.”
Case in point: Google’s AI overview once recommended adding glue to pizza sauce—because it surfaced a joke from an 11-year-old Reddit post. The data was “there,” but it wasn’t vetted, accurate, or safe.
The takeaway: Before you build your next AI-driven customer experience, audit your data. Make sure it’s accessible, reliable, and appropriate for the use case. AI can’t improvise around bad inputs.
2. Your Customers Aren’t All-In on AI—And Privacy Has a Lot to Do With It
Forrester segments consumers into five privacy personas: from “Reckless Rebels” (who share data freely) to “Skeptical Protectionists” (who guard it fiercely). These personas also predict how comfortable people are with sharing data with GenAI tools.
Across the board, only half of US online adults have tried GenAI at all. And even among early adopters, trust and transparency remain huge barriers.
Liu noted, “Just because AI is trending doesn’t mean your customers are ready for it—or trust it.”
The takeaway: Know your audience’s privacy posture. If they’re hesitant, don’t lead with “AI.” Lead with value. Tell them what they’ll get, how it helps, and why it’s worth sharing information.
3. The Next Wave of AI Might Belong to the Customer
Today, AI is mostly brand-owned. But what happens when customers start using their own AI agents?
That’s the idea behind “digital doubles,” or consumer-side AI tools trained on personal preferences, context, and goals. They’ll interact with brand algorithms, search engines, and shopping sites on behalf of the individual.
Think of it like Stitch Fix, but across the entire internet.
“Instead of bombarding me with emails for shoes that aren’t in my size, my digital double will just let me know when something relevant goes on sale,” Lui explained.
The takeaway: The personalization future may be less about targeting and more about being ready. Make sure your systems can receive and respond to preference data—rather than just guessing at it.
So, What Should You Do Now?
The guidance is clear. Whether you’re AI-curious or already experimenting, this is the time to get your house in order.
Start by:
Scoping your AI goals clearly: What do you want it to do? For whom?
Mapping your data needs: What do you have, and what are you missing?
Improving data quality: Clean, accessible, and compliant is the baseline.
Creating value exchanges for zero-party data: If you need it, ask for it. But offer something in return.
This isn’t about chasing hype. It’s about building trust, getting your data strategy right, and making sure your AI efforts actually help customers.
Ready to dive deeper? Watch the full webinar replay with Forrester’s Stephanie Liu or get in touch to explore how we can help turn your first-party data into an AI-ready growth engine.