Do you think AI has actually made customer support better?
For businesses, the answer is mostly yes. Costs have come down, coverage has expanded, and chatbots handle queries that would have once meant a 20-minute wait for a human agent.
But what about for the customer? That’s where things get a little blurrier.
In many instances, customers now have to parse a wall of generated text, judge whether what they're reading is accurate, rephrase their question when the AI misses the point, and verify whatever instructions they've been given before they act on them.
This means that for many customer service interactions, the customer has to put in more work, not less.
This point was raised by Shan Lilja, Co-Founder of Mavenoid, in a recent discussion with CX Today:
“Company effort has gone down, but customer effort has risen.”
This separation between organizations and customers is at the crux of AI-assisted support right now – and Lilja argues that multimodal is the bridge that can fix the divide.
The Hidden Tax
The concept of customer effort isn't new in CX. The Customer Effort Score has been a staple of support measurement for over a decade. But the way that effort manifests has changed with the introduction of large language models.
The old failure mode was friction from poor routing or slow response. The new one is cognitive load: the mental work required to interact productively with an AI that sounds confident but isn't always right.
Lilja describes this as a “hidden tax on every AI interaction, paid by customers.”
As discussed above, these taxable events are familiar to anyone who's recently used a support chatbot.
While these effort-sapping instances don’t show up on dashboards via containment rates or CSAT scores, they can really add up.
And this increased cognitive load can lead to abandoned sessions, repeat contacts, and a slow erosion of confidence.
Within this effort tax, Lilja points to a specific area that he believes to be one of the most damaging: “AI slop.”
“AI slop is low-quality, generic content produced by AI.”
This slop has the potential to cause serious damage to an organization's customer service operations.
An AI that tells a customer to press the wrong button can damage their product or, in a worst-case scenario, create a safety issue.
And the liability implications are real. Earlier this year, Woolworths was forced to make adjustments to its AI chatbot after it falsely claimed to have an “angry mother” and presented itself as having personal family experiences.