AI readiness isn’t a slogan anymore, it’s quickly becoming the dividing line between CX teams that can scale automation safely and those that keep getting stuck in pilots.
As Martin Hill-Wilson, Owner at Brainfood Consulting, told CX Today, many organizations are learning the hard way that “readiness is more than just technology,” and that chasing outcomes without foundations can lead to what he calls “AI recklessness.”
AI readiness in CX is becoming a board-level obsession, but Hill-Wilson argues many enterprises still lack the shared understanding to execute safely and consistently, as he explains:
“My first instinct was foundation, understanding education. A lot of people still actually got imposter syndrome, to be blunt about it, from the boards downwards.”
That confusion shows up in extremes, he adds, from “it’s magic, it will do it,” to “it’s total tosh,” with too few leaders holding practical mental models of what modern AI can, and cannot, deliver.
Why CX Teams Keep Getting Stuck In POCs
Hill-Wilson describes today’s landscape as “a transformative opportunity, a disruptive opportunity, and a dangerous opportunity.” The danger is not theoretical. It is operational.
“The easiest thing to do is to get POCs working,” he says. “What we discovered last year is that everyone’s in POCs and they can’t get out of POCs into production.”
And even when teams do go live, he says the broader organization often cannot support the deployment.
“If they get into production, the associated readiness of the enabling part of the organisation, the data, the governance, etc., is brittle,” Hill-Wilson says. “It falls over and they crash and burn.”
That brittleness creates a costly pattern: pilot success, production friction, then retrenchment. It also burns internal confidence in the program.
The Boardroom Gap, And The Cost Base Question
Hill-Wilson sees a familiar tension getting worse in the AI era: strategic ambition rising faster than delivery capability.
“The mismatch between how the board has been wound up to be excited and the teams that are operationally responsible for deploying it, there is that gap,” he says.
“The missed expectations is causing frustration all over the place.”
He also questions whether boards understand what they are truly authorizing when they pursue agentic AI, beyond cost reduction.
“I don’t think [boards] actually understand the detail of what they’re really trying to evoke necessarily,” Hill-Wilson says. “They don’t understand anything beyond their immediate concern, which quite frankly, is 'can I change my cost base?'”
“You Can’t Busk This Stuff”: The Rise Of “AI Recklessness”
Hill-Wilson’s central warning is that speed without discipline increases risk, and makes failure more likely.
“All of those things are symptomatic of the fact that people are chasing it without necessarily planning it,” he says. “And you can’t busk it in this way. You really can’t busk this stuff because all AI is in fact doing is accelerating things.”
That acceleration cuts both ways. If an organization has fragmented data, brittle processes, and unclear ownership, AI can amplify those weaknesses.
“All AI is in fact doing is accelerating things. So if you’re accelerating, if you’ve got chaos and you want to accelerate it, guess what you get.”
Hill-Wilson calls the healthier alternative “creating discipline,” and he frames 2026 as a year when many organizations will be forced into a harder conversation about return on investment.