During SlatorCon Remote on December 2, 2025, a panel discussion focused on embedding AI into everyday business operations within the context of globalization and localization.
Moderated by Slator Head of Research, Anna Wyndham, the panel featured industry leaders Semih Altinay, VP of AI Solutions at Phrase, Esther Curiel, Globalization Manager at Zoetis Diagnostics, Freddie Braun, Localization and International Content Lead at Monzo Bank, and Zach Duncan, Head of Localization at Stripe.
The discussion’s central theme was the shift of AI from an experimental technology to a business-as-usual (BAU) capability, driven by AI’s ability to deliver significant operational efficiency, unlock unprecedented scale, and enhance the quality and consistency of global customer experiences.
At Monzo Bank, the AI-as-BAU philosophy is anchored in two principles: “removing friction and elevating people.” Freddie Braun explained that AI now automatically handles heavy, repetitive tasks like translations and rewriting support messages within their content system.
This automation has transformed the Monzo team’s mandate. “That changes the team’s roles. Instead of policing processes, they become strategic content guardians,” commented Braun, adding that this allows them to focus on high-value work like tone, nuance, clarity, and building customer trust.
At global payments processor Stripe, the focus is squarely on “operational efficiency.” Zach Duncan described how AI makes his team feel like “superhumans,” accelerating daily work. He cited a personal example of dictating for five minutes and producing a finished presentation in about an hour, a task that would have previously demanded significantly more time.
At life sciences company Zoetis Diagnostics, AI is seen as the key to achieving a long-held goal: providing all global customers with an experience comparable to their domestic counterparts. Esther Curiel noted the excitement is not just about current efficiencies but about how “as we bring AI into the business as usual, we’re actually building the future of communications, with our customers, we’re reimagining how those communications can work.”
Semih Altinay summarized the provider perspective at Phrase in simple yet eloquent terms: “I think AI is now no longer a project. It’s just this embedded capability, and I love it because it just makes us so much more productive.”
The catalyst for this institutional shift was often a point of crisis or overwhelming scale. At Zoetis, for example, the explosion of product, medical, and support content driven by fast innovation became the breaking point.
Esther Curiel explained that for them, traditional localization methods simply were not keeping up, making AI adoption a necessity to maintain speed and empower product teams with content autonomy.
A Matter of Trust
The consensus among the panelists centered on three major areas: AI has moved or is moving beyond experimentation; AI dramatically improves operational efficiency and scale; and trust in AI requires governance.
Building trust in AI systems is a core challenge, the participants concurred, but one that is being achieved through robust user control, transparency, audibility, guardrails, and domain constraints, as well as “explainable AI” that eliminates black-box processes. For AI to become truly business as usual, especially in regulated sectors like banking and life sciences, establishing trust is non-negotiable.
To Altinay, at Phrase, key foundational elements include a transparent, traceable infrastructure, the seamless integration of brand voice, and continuous quality scoring.
In the high-stakes environment of banking, Monzo’s Braun noted that AI first had to prove itself on “the unglamorous bits like legal disclaimers, financial terminology, and regional compliance.” Once AI reliably handles this high-stakes work within established guardrails, stakeholders stop seeing it as optional.
Similarly, Zoetis mitigates risk by educating internal teams on prevention strategies, fostering an “ecosystem where we’re all managing risks together.”
Stripe’s Zach Duncan advocates for “walking in a responsible manner as opposed to sprinting,” focusing on durable infrastructure that can leverage future advancements.
“I think AI is now no longer a project. It’s just this embedded capability, and I love it because it just makes us so much more productive.” — Semih Altinay, VP of AI Solutions, Phrase
Quiet Automation and Value of AI
The tangible value of embedded AI manifests as a combination of automation, autonomy, and scale. Phrase’s Altinay highlighted quiet automation where AI disappears in the background, with “no new systems, no new buttons, no friction.” Users simply state a goal, and AI agents orchestrate the entire workflow.
For Zoetis, the greatest benefit is the increased autonomy of the teams they serve, allowing the localization function to get “out of the way,” shifting the focus from transactional tasks to strategically curating the technology ecosystem.
For Monzo, the value lies in the synergy of speed, precision, and consistency, in how AI ensures regulatory safety through precision, delivers features faster, and builds trust. “Customers just really get the same clear human Monzo experience, whether they’re reading the app in English or any other language,” commented Braun.
For Stripe, Duncan says the single biggest impact is scale, noting that projects and ideas that were previously a “hard no or unreasonable are now back on the table.”
Looking ahead, the panelists agree that the next two years will see the rise of multimodal, context-rich AI, more sophisticated AI Agents managing end-to-end workflows, and hyper-personalization in content.