5 real scenarios for enterprise AI adoption (with cost ranges)

Direct answer: the right starting point for enterprise AI is not "building a model platform" — it is one concrete business process. These five scenarios have the clearest ROI and mature paths to production.

Scenario 1: The lead-generating website (GEO)

Definition: website building and optimization that makes your content easier for AI to cite. Typical use: industry Q&A content, structured product pages, an explicit AI-crawler policy. Cost range: subscription pricing — far below a custom build.

Scenario 2: AI visual inspection

Definition: image recognition replacing human judgment in inspection. Typical use: AI skin analysis in beauty retail — customers upload a photo and get a skin report, a direct in-store conversion hook. Cost range: from per-call API pricing to dedicated deployment.

Scenario 3: AI CRM

Definition: lead scoring, follow-up suggestions and automatic nudges on top of a classic CRM's record-keeping. Typical use: new leads auto-ranked by close probability, follow-up reminders on schedule. Cost range: per-seat subscription.

Scenario 4: AI ERP

Definition: recognition and forecasting models handling document entry and inventory planning inside ERP. Typical use: photo-to-entry document capture, demand forecasting. Cost range: modular implementation that scales with scope.

Scenario 5: The content factory

Definition: a pipeline for bulk, compliant, sustainable content production. Typical use: generating marketing content by industry and keyword, then publishing in one place. Cost range: per-article pricing that falls with volume.

Bottom line: of our 10+ AI products, four core lines — GEO website building, AI skin analysis, AI CRM and AI ERP — cover the first four scenarios. One rule for adoption: start from the most painful process, not from AI for AI's sake.