Going global used to mean a slow, expensive localization process, but AI is compressing that timeline unevenly across different tasks. A survey of 600 marketers measured average time savings from AI across eight localization activities, and the results range from massive to marginal. Translation and video localization show the steepest time savings, while campaign setup and quality assurance show the smallest gains, suggesting AI is doing far more for production tasks than for judgment-heavy ones.

Essential Statistics

• Translation shows the largest average time savings from AI at 88%.
• Video localization follows closely at 82%.
• Market research and creative adaptation both show time savings in the low 60s percent range.
• Copy adaptation shows a 47% time savings.
• Campaign setup shows the smallest time savings at just 10%, with quality assurance close behind at 19%.

Key Takeaways

• Translation and video localization showing the steepest time savings suggests AI has matured fastest for tasks with clear input-output structure and less need for nuanced judgment.
• Campaign setup and quality assurance showing minimal time savings suggests these tasks still depend heavily on human oversight, likely because they carry more risk if something goes wrong.
• Market research and creative adaptation landing in the middle suggests AI is providing meaningful but partial support in tasks that still require some level of strategic or cultural judgment.
• The wide range between the highest and lowest time savings suggests a one-size-fits-all approach to AI localization tooling likely misses where the biggest gains actually are.
• This pattern points toward the remaining human workload in localization concentrating increasingly around judgment, culture, quality, and strategy, exactly the tasks showing the smallest AI-driven time savings.

Actionable Insights

• Prioritize adopting AI tools for translation and video localization first, since these tasks show the largest measured time savings and the most mature AI support.
• Keep human oversight concentrated on campaign setup and quality assurance rather than trying to automate these tasks further, since the data shows minimal time savings even with AI involved.
• Reallocate the time saved from translation and video localization toward market research and creative adaptation, where AI is helping but not yet delivering the same scale of efficiency.
• Set realistic expectations internally about which localization tasks AI can meaningfully speed up. Treating every task as equally AI-accelerated risks under-resourcing the ones that still need real human time.
• Revisit this breakdown periodically, since time savings in judgment-heavy tasks like creative adaptation and market research are likely to shift as AI tools continue to mature in these areas.

‘AI made translation almost free. It didn’t do the same for judgment calls. That’s exactly where your human team should be spending the time AI just gave back.’ – Neil Patel