Copy the enterprise wins at smaller scale: support deflection, lead routing, document extraction, and personalized offers—with metrics.
Enterprise case studies can feel distant if you run a 30-person firm or a growing e-commerce brand. The same mechanics apply; only the tools and team size change.
Support and sales qualification: Intercom, Zendesk, and many retailers have published results from AI-assisted chat that resolves common questions before a human joins. Klarna’s public deployment with OpenAI is an extreme version; a mid-size business might automate order status, returns policy, and booking FAQs, measuring deflection rate and average handle time. Revenue impact shows up as fewer abandoned carts and faster lead response.
Document and inbox automation: JPMorgan’s COIN is document AI at scale. Law firms, logistics companies, and lenders below Fortune 500 use the same class of tools—extract fields from PDFs, route exceptions to humans—to shrink turnaround on quotes and compliance packs. Metric: hours per deal or error rate on data entry.
Merchandising and offers: Amazon and Netflix scale personalization with huge data; a mid-size catalog can start with rules plus simple models—repeat buyers, category affinity, margin-aware bundles—and A/B test lift on average order value. Stitch Fix’s public story is a reminder that human plus algorithm often beats either alone.
Operations and scheduling: Uber and airlines have published for years on ML for demand forecasting and pricing; field-service businesses use off-the-shelf plus custom logic for drive-time routing and capacity. Metric: jobs completed per crew or utilization rate.
Duolingo has discussed using large language models to speed content generation for language courses—operational efficiency that lets the product team ship more lessons without linear headcount. Education, agencies, and media companies can use the same pattern for drafts, variants, and localization, with humans reviewing before publish.
Choose one workflow that touches customers weekly, baseline it for two weeks, then automate the dullest 40% with clear human override. That is how large incumbents de-risked AI—and how you get a factual before/after story for your own insight page someday.