Editorial
The Gist
-
Customer-first AI. AI tools succeed when designed with direct customer input. This helps build trust through collaboration.
-
Transparency matters most. Clear communication about AI capabilities and limitations prevents frustration and encourages stronger customer relationships.
-
Utility drives impact. AI solutions focused on solving real customer problems outperform flashy, underwhelming features that lack purpose.
The recent backlash Meta faced over its AI-powered celebrity bots is a wake-up call for brands everywhere. Instead of delighting users, the rollout of these AI characters sparked an outcry. Why?
It wasn’t just the technology. It was the disconnect between what users expected and what they received. This scenario highlights an important lesson. AI should be built with your customers, not just for them, especially when considering customer experience design.
Table of Contents
- Prioritize Customer Needs Over Brand Goals
- Collaborate With Customers to Shape Experience Design
- Build Trust Through Transparent AI Customer Experience Design
- Focus on Solving Real Problems
- Core Questions Around Designing AI for Customers
Prioritize Customer Needs Over Brand Goals
When brands build AI solutions in isolation, they risk misunderstanding what their customers actually want. Meta’s character bots, for example, were intended to enhance social interactions. But without sufficient input from users during development, they ended up feeling intrusive and irrelevant to many.
AI that doesn’t align with customer expectations doesn’t just fail. It can actively harm brand trust. How can brands avoid this pitfall? Here are four ways to avoid this trap in AI customer experience design.
Collaborate With Customers to Shape Experience Design
Treat your customers as collaborators in the customer experience design process. Invite them into the process through surveys, focus groups and beta tests. By involving them early, you make sure your AI solutions reflect their needs and preferences. This approach doesn’t just minimize risk. It also turns your customers into advocates for the final product.
Build Trust Through Transparent AI Customer Experience Design
Customers need to understand how your AI works and what it’s meant to do. Therefore, you need to be upfront about its capabilities, limitations and intentions. A lack of transparency was part of what derailed Meta’s bots. Users didn’t understand their purpose and felt their online space was invaded. Clear communication can bridge this gap.
For example, let’s say your company launches a chatbot designed to assist with online customer support. To build trust, you could communicate its capabilities, limitations and intentions in these ways.
-
Capabilities: "Our chatbot can answer frequently asked questions, help you track orders and assist with basic troubleshooting 24/7."
-
Limitations: "For complex issues like technical escalations or account-specific questions, a human representative will step in to ensure accuracy."
-
Intentions: "This tool is here to make your experience faster and smoother, which frees up our team to focus on solving the more nuanced problems you might face."
By clearly outlining this upfront — on your website, during the chatbot introduction or in marketing materials — you set proper expectations. This transparency helps users understand the AI and prevents frustration when the tool faces challenges it wasn’t designed to handle.
Related Article: Why Transparency Is Vital When Brands Use AI
Focus on Solving Real Problems
While it’s tempting to chase flashy features, utility should come first. Ask yourself how this AI will improve your customers’ experiences. A tool that simplifies a task or solves a problem will always resonate more than one that exists purely for show.
Refine Through Ongoing Customer Feedback
The launch of any AI solution should be just the beginning. Gather real-time feedback, analyze usage data and adapt accordingly. This iterative approach helps you make sure your AI evolves alongside your customers’ expectations.
Meta’s AI bot misstep is a cautionary tale for all of us working with emerging technologies. As brands, we’re often excited about what’s possible, but we can’t lose sight of what’s useful. AI has the power to transform customer experience, but only if we design it in partnership with the very people it’s meant to serve.
Webinar
Sep
25
CMS Briefing: A Live Look at What’s Next in AI-Driven Platforms
Learn how leading organizations are using AI‑driven tools to publish faster, personalize smarter and stay secure.
Register
Webinar
On demand
Ready or Not: How Data-First Organizations Are Unlocking Agentforce Potential
Learn how to cut through the noise, activate Agentforce and build a Salesforce AI strategy that actually delivers.
Watch Now
Webinar
On demand
AI in Customer Service: Faster Resolutions, Happier Customers
Don’t let rising demand burn out your team. See how to build a smarter, more resilient support org.
Watch Now
Webinar
On demand
From Hype to High-Impact CX Strategies That Actually Scale
Turn buzzworthy AI and outsourcing trends into measurable CX wins with fresh 2025 data.
Watch Now
Webinar
On demand
Insights to Action Rethinking the Contact Center for Real Business Impact
Join our exclusive webinar to hear CX executives share their innovative strategies for transforming service delivery.
Watch Now
Webinar
On demand
Accelerating Healthcare Ops with AI
Sign up to see how your peers are putting AI to work — and making it stick.
Watch Now
Core Questions Around Designing AI for Customers
Editor's note: Here are two important questions to ask about AI in customer experience design.
How can brands ensure their AI aligns with customer expectations?
Brands can involve customers in the design process through co-creation methods such as surveys, focus groups and beta tests. This helps make sure that the AI reflects their needs and preferences, and it helps prevent missteps like those seen with Meta's AI bots.
Why is transparency important when implementing AI in customer experience design?
Transparency builds trust with customers by clearly communicating an AI tool's capabilities, limitations and intentions. Setting proper expectations upfront helps avoid user frustration and creates a seamless, positive experience where the AI solution fulfills its intended purpose without overpromising.
Learn how you can join our contributor community.
