Usability was the baseline—now it’s trust

For decades, usability has been the gold standard. Could users complete tasks quickly and efficiently? Could they find what they needed?

That’s no longer enough.

AI introduces a more human layer of evaluation. Users don’t just assess outcomes—they assess intent, tone, and credibility.

“We don’t test for personality. We test for usability,” Mike said, pointing to a growing gap in how teams evaluate AI-driven experiences.

That gap is where AI UX design best practices are evolving fastest. Products now need to communicate with clarity, consistency, and context. They need to feel reliable, not just function correctly.

This is the heart of trust in AI interfaces. It’s not built through accuracy alone. It’s built through interaction.

A response that is technically correct but poorly framed can erode confidence. A response that is clear, grounded, and context-aware can reinforce it.

In that sense, AI is less like software and more like a representative—one that speaks on behalf of your brand every time a user engages.

The customer journey is happening somewhere else

The traditional customer journey assumed a sequence: awareness, consideration, conversion. Each step was designed, measured, and optimized.

That sequence is dissolving.

“People are just going and talking to their favorite AI bot… and they have this really rich, lengthy conversation… before they even talk to you,” Mike said.

This is the new reality of AI-driven customer journeys.

Customers are:

• Researching through AI
• Comparing options through conversation
• Forming opinions before visiting a brand

By the time they arrive, they are not starting a journey—they are continuing one.

“You don’t know what state of mind they’re in when they come to you,” he added.

That uncertainty is what makes traditional funnels feel increasingly fragile. They assume context that no longer exists.

From controlling journeys to entering them

For marketers, this shift is especially profound.

The goal has long been to guide users—to design paths that move them predictably toward conversion. But AI disrupts that control.

“We are now enabling conversations rather than driving them,” Mike explained.

This reframes the role of marketing within AI marketing funnel transformation. Instead of directing behavior, teams must now support it—wherever and however it emerges.

That requires a different kind of preparation:

• Information that AI systems can access and interpret
• Messaging that holds up in unscripted dialogue
• Content that answers questions beyond the confines of a campaign

It’s less about sequencing touchpoints and more about ensuring coherence across them.

When AI becomes the customer

If conversational AI changes how users interact, agentic AI changes who is interacting.

“You can use agents today to go and find products and purchase products on your behalf,” Michael said.

This is the early shape of agentic AI in customer journeys—systems that don’t just assist decisions, but make them.

These agents can:

• Navigate websites
• Evaluate options
• Execute transactions

In some cases, they operate with minimal oversight.

This introduces a new dynamic for AI agents in eCommerce. Your customer may no longer be a person navigating your experience directly. It may be a system interpreting it on their behalf.

That distinction matters.

Designing for humans—and their proxies

Most digital experiences are optimized for human behavior: scanning, clicking, comparing.

AI agents behave differently. They prioritize clarity, structure, and efficiency.

Michael notes that many of these systems interpret websites in ways that mirror human interaction—but with far less tolerance for friction.

That raises the bar for:

• Information architecture
• Content clarity
• Logical flow

If your experience relies on nuance, guesswork, or visual cues alone, it may break down under AI interpretation.

Designing for this future means building experiences that are legible to both humans and machines—without compromising either.

The pace of change is the real disruption

What makes this moment different isn’t just the technology—it’s the speed.

Capabilities that felt experimental a year ago are now entering mainstream awareness.

“This is starting to hit the general public,” Michael said.

That shift—from early adopters to broader usage—is where transformation accelerates. It’s when behaviors change, not just possibilities.

For teams shaping AI customer experience strategy, this creates a tension: act too slowly, and you fall behind. Act too quickly, and you risk chasing the wrong problems.

The danger of building what feels impressive

AI makes it easy to build things that look compelling. It’s harder to build things that matter.

“It is really easy to find experiences that feel really compelling… but don’t actually solve a big customer problem,” Mike said.

This is a familiar pattern in AI in product development. New capabilities invite experimentation—but not all experimentation leads to value.

The distinction comes down to intent.

Are you using AI to:

• Demonstrate innovation?
• Or solve something meaningful for your customer?

The former creates attention. The latter creates impact.

What to do now—and what to explore

The conversation draws a clear line between urgency and exploration.

What requires immediate action

Conversational AI is already reshaping expectations. This is not a future state—it’s a current one.

Teams should:

• Reevaluate interfaces through the lens of conversation
• Test for tone, trust, and clarity—not just usability
• Align AI behavior with brand voice

“Your user interface is probably at least somewhat obsolete,” Mike said.

What requires experimentation

Agentic AI is evolving quickly, but its implications are still unfolding.

This is where teams should:

• Explore use cases tied to real customer needs
• Monitor how agents interact with their platforms
• Stay flexible as capabilities shift

This dual approach—execution and exploration—is central to any meaningful AI-powered digital transformation.

A different kind of interaction model

At its core, this shift is not about technology—it’s about interaction.

We are moving from:

• Interfaces to conversations
• Journeys to interactions
• Users to participants—and, increasingly, proxies

This evolution in human-AI interaction design challenges assumptions that have shaped digital experiences for decades.

It also creates an opening.

Moments like this—when the rules are unclear and the pace is high—are when new leaders emerge.

The opportunity inside the disruption

Mike has seen these transitions before. Each one reshapes industries, displaces incumbents, and creates new categories.

But they also share something else: they reward those who engage early.

“These generational changes in technology enable generational changes in the companies that are building with that technology,” he said.

That’s the real story here.

Not that AI is changing customer experience—but that it is changing who gets to define it.

The bottom line

The rise of conversational AI customer experience and agentic AI in customer journeys is not an incremental shift. It’s a structural one.

It challenges:

• How users interact with products
• How decisions are made
• How brands participate in those decisions

And it does so in real time.

“Your user interface is probably at least somewhat obsolete, and you’ve got to rework it… and your user journeys are more or less obsolete.”

Resources & links

• Mike Mace on LinkedIn
• Michael Domanic on LinkedIn
• Nathan Isaacs on LinkedIn
• Effective AI: how to choose the right generative AI features—and build them fast. Covers how conversational interfaces are changing interaction models, how to design for emotional impact and credibility, and how to increase adoption of AI features.
• How to test AI: a practical guide for evaluating AI user experience and product design. Explains how to evaluate AI-enabled experiences, including agents and copilots, and how to integrate AI UX research into product development.
• AI employees and the future of work. Discover how AI employees are transforming the workplace with Surojit Chatterjee. Learn what it means to build for the future of work—starting now.
• UX for AI: Designing intelligent experiences with Greg Nudelman. Discover how UX must evolve in the AI era with Greg Nudelman. Learn to design intelligent, content-first experiences that truly serve users.

FAQ: AI and the future of customer experience