AI has become standard language in the localization industry. Most language service providers mention it — in their pitch decks, on their websites, in their proposals. That’s not a problem. The problem is that “we use AI” doesn’t actually tell you anything useful.

If you’re evaluating an LSP that claims AI capabilities, here are the four questions that matter.

1. How deeply is AI integrated into their workflow?

There’s a meaningful difference between an LSP that has built AI into its core processes over time and one that has added it recently as a feature layer. The former has refined the workflow, knows where it works and where it doesn’t, and can explain exactly how it applies to your content type. The latter may still be figuring it out.

Ask them to walk you through their process, step by step. Not the pitch — the actual workflow. Where does AI generate content? Where does human review happen? What quality checks are in place? How do they handle edge cases? A provider with genuine AI experience answers these questions without hesitation.

2. Is there always a human in the loop?

AI moves fast. That’s the point. But speed without oversight is a risk, particularly for content that carries your brand voice, touches regulated topics, or reaches audiences where a mistranslation has real consequences.

The best AI-assisted localization workflows treat human review not as an optional extra, but as a built-in requirement. A qualified linguist validates the output before it reaches you — checking for accuracy, tone, cultural fit, and consistency with your brand. Some providers have formalized this into a quality standard that applies to every AI-supported deliverable, making the human validation step visible and accountable rather than implied.

When evaluating an LSP, ask specifically: at what stage does human review happen, and who is responsible for it?

3. Do they start with your needs, or their offer?

A good language partner asks questions before proposing solutions. What kind of content is it? What’s the target audience? What does your brand voice sound like? Is speed the priority, or is this content where tone and nuance are non-negotiable?

The answers to those questions should shape the approach — including whether AI is the right tool for that specific project, or whether a different method would serve you better. Not every content type benefits equally from AI assistance, and an LSP worth working with will tell you that directly.

If the first conversation is mostly about rates and turnaround times, you’re talking to a vendor. If it starts with understanding your actual problem, you’re talking to a partner.

4. Can they prove it with numbers?

AI is frequently sold with vague promises — faster, cheaper, more scalable. Those things may well be true. But “faster” by how much? “Cheaper” compared to what baseline? Push for specifics.

The LSPs that have genuinely integrated AI into their operations can answer with real data. A footwear e-commerce that cut a month-long content workflow down to three days, with a 23% increase in customer traffic and 20% cost savings per description. A tech company that achieved 90% reduction in manual work and 10x faster turnaround. These are the numbers that tell you whether AI is actually working — and whether the provider knows how to make it work for you.

Ask for case studies. Ask for client references. Ask what the quality benchmarks looked like before and after.

A practical checklist

Before signing with an LSP that uses AI, you should be able to answer yes to all four of these:

• Can they explain their AI workflow in concrete, step-by-step terms?
• Is human review a structural part of the process, not an optional add-on?
• Did they ask about your content and goals before proposing a solution?
• Can they show you measurable results from real projects?

AI is genuinely changing what’s possible in localization — faster timelines, lower costs, greater consistency at scale. But the technology is only as good as the process around it and the people accountable for the output. Choose an LSP that can prove both.