E-commerce localization isn’t about choosing “AI vs human” up front — it’s about choosing a launch path that fits your budget and timeframe, then iterating based on what users actually do. In some cases it makes sense to segment early and launch with a mix (MT for low-impact scale content, hybrid for mid-impact, and human for conversion-critical surfaces like key landing pages, product pages, and checkout). In other cases, the fastest route is to launch with a lightweight baseline (often generic MT) to get into-market quickly, then use conversion and SEO data to identify where the user journey breaks down — and invest human work exactly there. Over time, those improvements create a valuable bilingual corpus that can support higher-leverage automation, including more tailored MT where volume justifies it, and systematic retranslation as the workflow matures. The point isn’t “more words faster.” The point is a measurable loop: ship, learn, fix bottlenecks, and scale what works without losing consistency or control.