Banking has now crossed a line where experimenting with AI is now riskier than choosing to commit to it.
Whilst ‘staying safe’ in the early days of experimentation was valuable to ensure future advantages, many institutions that are still running proofs of concept are no longer staying safe; they are instead accumulating CX debt while their competitors turn AI into measurable capacity.
Glia’s 2026 Benchmark Report reveals that banks should be achieving at least 90% in intent accuracy to ensure AI is reliable enough to contain high-volume queries without eroding trust. high-volume queries without eroding trust.
Justin DiPietro, Chief Strategy Officer & Co-Founder at Glia, argues that banks that choose to keep AI stuck in pilots will fall behind competitors, with AI in production now being a necessity, not a choice.
"The problem of keeping [AI projects] in experimental mode is that you're just going to be outcompeted by the competition,” he explained.
"The banks don't differentiate in many places, [but] they differentiate on customer experience.
"It's not optional anymore. [Financial leaders] have to get to production.”
When Pilots Become a Competitive Disadvantage
Whilst experimenting with AI allowed teams in the early stages to understand new capabilities before deployment, small AI pilots can no longer keep pace with how fast customer expectations and technology are shifting in banking.
A tactic that once reduced risk now slows progress in areas where competitors are moving quickly, as customers now expect seamless digital experiences, rapid problem resolution, and consistent support across channels.
Banks that choose to stay in pilot mode delay improvements that customers already view as standard, falling behind as competitors gain efficiency and strengthen satisfaction.
This shift in expectations means that banks must now be able to move from controlled pilots to broader implementation, as scaling AI not only accelerates the adoption of new capabilities but also provides real-world data to identify measurable business outcomes.
Without this shift, experimentation alone cannot keep pace with evolving expectations or demonstrate a tangible competitive advantage.
Dan Michaeli, CEO & Co-Founder at Glia, explained that because AI capabilities are improving rapidly, staying in experimentation mode puts a company at a competitive disadvantage.
"At the end of the day, it's the speed at which these capabilities are evolving and getting better,” he said.
“That's why you can't afford to be in experimentation mode anymore. You're just at a fundamental disadvantage.”
Why Underperforming AI Breaks Banking CX
Many banking customers have already been conditioned by previous negative automation interactions, with many choosing to skip it entirely.
With mistrust already baked into the banking experience, these prior interactions can make customers more likely to ask for a human in regulated environments.