Blog Articles

By the time a language services contract lands on your desk for signature, trust has usually already been talked about at length. What it hasn't been is written down. A sales conversation can promise reliability, security and quality, but a contract only protects you against the commitments that are actually documented, measured and enforceable. If you are choosing an interpretation partner for high-stakes meetings, conferences or institutional programmes, the question is not whether the vendor sounds trustworthy. It is whether that trust survives being turned into contract language.

Walk into a large conference hall or auditorium today and you will often see a screen at the front of the room carrying more than slides. Underneath the speaker's name, or along the bottom third of the display, a live transcript of what is being said scrolls in real time. This is on-screen captioning, and it has moved from a niche accessibility feature to a standard expectation at well-run onsite events. 

Every interpretation vendor's website claims to take security seriously. Most mention encryption somewhere on the homepage, and a fair number display a certification badge near the footer. For a buyer comparing providers, these claims tend to blur together, and it becomes easy to treat them as background noise rather than as evidence worth examining.

Every AI speech translation session carries a conversation that someone considered worth having in real time, whether it's a board discussion, a diplomatic briefing, or a clinical consultation. That conversation gets captured as audio, processed by machine translation models, and often stored or logged somewhere along the way. If the underlying infrastructure isn't secured properly, the convenience of instant multilingual communication comes with a data protection risk that's easy to overlook until it's tested.

Employees now trust their employer more than any other institution in their lives. According to the 2026 Edelman Trust Barometer, 78% of people trust their employer, ahead of business in general (64%) and government (53%). That figure looks like good news for leadership teams. It is also a warning.

A quarterly earnings call gets moved up by two days. A crisis communications briefing needs to go out to five markets within the hour. A regional sales kickoff, planned months in advance, needs interpreters booked, briefed and ready before the first slide goes up. These are all multilingual events, but they call for different approaches to interpretation, and choosing the wrong one costs time, money or both.

Most conversations about AI language performance still centre on English. A model scores well on a standard benchmark, gets praised as state-of-the-art, and is rolled out for global use. But a growing body of evidence, most recently the European Commission's new EU MMLU dataset, shows that strong English performance says very little about how a model handles French, Hungarian or Maltese. For anyone relying on AI live translation at international events, that gap is not an academic footnote. It is the difference between a delegate understanding a keynote and missing it entirely. 

Picture a training video recorded once in English that a global workforce needs in ten languages by Friday. A decade ago, that request meant hiring voice actors, booking studio time, and waiting weeks for each language. Today, it can mean uploading a file and downloading a dubbed version in hours. This shift is powered by AI dubbing.

Most sustainability conversations in the events industry start with venues, catering and offsetting. Travel is usually acknowledged and then set aside, because delegate and speaker travel is rarely up for debate: it is the reason onsite events happen. That instinct holds up. Business travel and accommodation typically account for 70 to 90 percent of an event's total emissions, and attendee travel is usually the single largest source within that figure. Across the industry as a whole, aggregated travel, energy, catering and logistics may account for up to 10 percent of global greenhouse gas emissions.