AI can predict, recommend and act in an instant, but customers still need time to interpret what is happening and decide whether they are comfortable proceeding.
Patricia Camden, US Marketing, CX and Loyalty Leader at EY, calls the resulting mismatch the “human tempo gap,” warning that automation can undermine trust when it gets ahead of the person.
To ensure their brands don’t fall behind, CX leaders must be prepared to build AI experiences that aren’t centered on friction removal but preserving customer control.
In conversation with CX Today, Patricia explained why brands must move beyond optimising AI-driven experiences for speed alone.
“We think about it as today in the AI experience age, we design for confidence,” she said.
“We don’t design just for completion.”
The History Behind CX Speed
Today, AI-driven speed is beginning to move faster than a person can comfortably comprehend to make a confident decision, as the original digital experience design was built around removing friction.
When technology was often the slower part of the interaction, companies that offered fewer clicks, faster page loads and shorter forms generally offered a better experience.
However, AI is changing that relationship by inferring intent and moving customers through journeys before they may have processed the previous step.
“That’s what we’ve been calling the tempo gap. It’s that moment when the machine speed outpaces our human comprehension,” she explained.
“And for me, that’s not just a UX issue. That’s actually an issue of trust.”
This creates what can be described as “tempo shock,” particularly when AI makes an interaction feel as though it has progressed without the customer fully understanding how or why.
Camden explained:
“Tempo shock is this feeling of wait, what the heck just happened? How did we get here so fast? Did I miss something along the way?”
In AI-sensitive sectors involving personal data, customers may need more time to understand terms and consider whether they want to proceed.
An automated decision or personalized recommendation may appear efficient, but if the customer does not understand the rationale behind it, speed can undermine confidence rather than strengthen the experience.
In fact, this issue becomes more significant as brands face global AI pressure, as EY’s Future Consumer Index tracked declining consumer trust, contributing to the “age of the skeptical consumer.”
These customers are more likely to scrutinize automated decisions and personalized interactions more closely.
Camden emphasized:
“The more personal the moment is the way that we think about it, the more personal the moment, the more important human tempo becomes.”
CX leaders must now recognize where this speed helps and where customers need more context and control over their journeys.
How Can Marketers and CX Leaders Prevent This?
After identifying the human tempo gap within the journey, organizations must now design AI interactions that account for it by mapping when it recommends and triggers outreach, to then assessing whether customers have comprehended its actions.
“Just because AI can help a brand or a company predict a need, doesn’t mean the brand should immediately act on it,” Camden warned.
That principle can be applied through “intelligent friction”, a deliberate pause added to an automated journey to ensure customers have time to catch up.
This could include a confirmation before an important action or offering an easy route to human support to ensure customers remain in control without sacrificing speed.
Whilst this technique only adds a few extra seconds to the journey, it may prevent automation uncertainty and discomfort.
“In an AI world, the best experience may be the one that ironically has the right friction in the right moment because it feels more human,” she noted.
Furthermore, to make friction more purposeful, CMOs and CX leaders should apply a respectful relevance test to automated engagement to consider whether a message is genuinely useful or presumptive because AI has inferred something about the customer.
The same principle applies to customer intelligence, AI can analyze data to identify patterns and predict customer needs, but an accurate prediction does not automatically justify immediate action.
CX and marketing leaders will need to consider whether acting on that insight creates genuine customer value, or whether it becomes another opportunity to push an offer or intervention.
Communication between a brand and a customer should appear useful, timely and relevant from their perspective, and the use of their data should feel helpful rather than presumptive or creepy.
Secondly, clicks and journey completion can show objective achievement, but not whether that customer trusted or valued the interaction.
Monitoring abandoned journeys, backtracking, and movement toward human-assisted channels can provide additional signals that an AI-driven experience may have gone too far or moved too quickly.
Camden concluded:
“A click does not equal confidence, and a conversion is not the same as trust. We can’t confuse those things.”
Ultimately, customer intelligence should be assessed through its impact on trust and loyalty, rather than the historical expectation of driving immediate action.
The quality of CX will depend on how and when that generated insight is activated, as alone it can deliver short-term results but weakening customer confidence.
