Localization professionals from across Europe gathered in Tallinn on October 7 for a conversation that had little to do with software demonstrations and everything to do with how their field is being redefined. Crowdin, the localization management platform, hosted its first in-person community event, Crowdin Connect, at the Mövenpick Hotel Tallinn, drawing more than 50 localization, product and engineering professionals from 14 countries for an afternoon built around peer exchange rather than sales pitches.
The event opened with a keynote from Andreas Ekström, a digital futurist and TED speaker, who framed the day's central tension: automation can make workflows faster, but speed is not the same as understanding. Ekström's warning - "What we gain in efficiency, we might lose in learning" - set the tone for a room full of people whose jobs sit at the intersection of language, technology and business strategy. Much like understanding what split tunnelling does helps a user decide which traffic to route and which to leave alone, Ekström argued that teams adopting AI need to be deliberate about which tasks they hand off and which they keep under human judgment. His closing line to the audience was blunt: the real competitive question ahead is not which artificial intelligence a company buys, but which organic intelligence it hires. what split tunnelling does
From Bottleneck to Business Partner
The shift Ekström described in the abstract became concrete in the case studies that followed. Oksana Naidjonova, AI-first Localisation Lead at Bolt, described rebuilding her company's localization program from the ground up - starting with something as basic as Bolt's first glossary, then moving to AI-first translation paired with linguist review, automating ticket creation with engineers, and eventually growing an in-house automation specialist. The numbers she shared were striking: average delivery delay on localization requests fell from 136 business days to roughly 90 minutes. "When you free people from manual, mind-numbing work, they start fixing the things that stressed them out but that they never had the capacity to solve," Naidjonova told the audience.
That same pattern - automation clearing space for higher-value work - ran through the panel "Localization Is No Longer One Team's Problem," moderated by Sofiia Hapon of Crowdin. At Pipedrive, which has used Crowdin for 12 years, Localisation Manager Ingrid Kirikal described how a decade of accumulated translation data now feeds AI tools directly, cutting a copy-paste task for SEO content from two hours to five minutes on a bad day and shrinking lead time for non-critical content from two weeks to two or three days. At Nord Security, Head of Localization Mantas Baraišis said localization has become a gatekeeper for commercial decisions: "Any kind of market entrance has to be validated by the localization team." At Wise, Localization Specialist Mehmetcan Boz drew a firmer line around automation, noting that customer-facing financial content still requires human oversight - though the team's quality assurance work has expanded from catching typos to flagging functional problems across entire product flows.
Managing Change, Not Just Content
Hapon's closing remark to the panel captured the day's underlying argument: these professionals are not just managing translations - they are managing organizational change. The audience discussion that followed turned to practical concerns familiar to anyone navigating workplace automation: how to tie localization output to business metrics leadership actually cares about, how to make quality data legible to executives, and how to bring human translators along as their roles shift from production to review and strategy. Conversations continued informally over dinner at the hotel's ROOF restaurant, closing out an event that treated localization less as a back-office function and more as a discipline shaping how companies enter markets and speak to customers worldwide.