Silke Zschweigert

It’s a fascinating and fast-moving time in our industry as we all explore and apply the capabilities of AI. The pressure to offer solutions that help companies do more for less has always been there, but the speed of change has gone up exponentially. This means that leaders at LSPs need to define and apply new approaches faster than before.

Generally, the opportunity could be huge for us to build new service offerings and approaches that align with Post-Localization. These include:
- Content generation for highly customized in-market content instead of translating or transcreating content that was created for a home market.
- Next-level post-editing/quality reviewing. AI-generated translation has output issues that are different from traditional machine translations. For example, AI translations can be full of bias that comes from the data they were trained on. Those errors and omissions need to be found and fixed.
- Applying AI across the workflow. AI automations can handle things like file prep, subject matter assessments, routing to the right translator, post-translation, quality control, etc.
- Helping enterprises create, test, and improve their LLMs or GenAI models they have developed for their own products.

And because AI implementation is strategic and revenue-driving rather than transactional, it gives LSPs access to C-suite executives, who are now often demanding that everyone use AI in their area and are keen to have these conversations.

The winners in our industry will be those who automate wherever possible while focusing on dedicating the right human experts to add value wherever needed to help companies go global faster, more cost-effectively, and at optimal quality. The era of Post-Localization demands more of us and will require that the strongest of minds within our industry rise to these challenges.