<p>GPT-4V's release in 2023 demonstrated that large language models could process images at a quality level useful for real tasks. Two years later, multimodal AI is in production deployment across enough industries to assess where it's generating genuine business value and where it's still overhyped.</p>
<h2>Insurance Claims Processing</h2>
<p>Property and casualty insurance is one of the clearest wins. Adjusters historically required physical site visits or manual photo review to assess damage — a process taking days to weeks per claim. Multimodal AI systems can now process photos submitted via mobile app, classify damage type and severity, cross-reference with policy terms, and generate preliminary settlement estimates — in minutes. Lemonade, Tractable, and Bdeo are all reporting 60-80% reductions in claims cycle time for standard property damage.</p>
<h2>Construction Monitoring</h2>
<p>Construction projects generate enormous volumes of site photography for progress tracking and safety compliance documentation. Manual review is time-consuming and inconsistent. Computer vision models trained on construction imagery can automatically categorize photos by trade, progress stage, and safety compliance indicators. Early adopters report eliminating 10-15 hours per week of manual photo categorization per project manager.</p>
<h2>Retail and Inventory</h2>
<p>Shelf monitoring is a recurring retail operations challenge: out-of-stocks cost retailers 4-8% of potential revenue. Traditional approaches required manual shelf audits. Camera-plus-AI systems can now audit entire shelf sections from mobile photos or fixed cameras, identifying stock-outs, misplaced items, and planogram compliance violations in real time. Deployment at scale across large retail chains is still in progress.</p>
<h2>Document Digitization</h2>
<p>The most mature application: converting physical documents (contracts, invoices, forms, identity documents) to structured digital data. Multimodal models substantially outperform earlier OCR + rule-based extraction on complex layouts, handwritten text, and multi-language documents. The combination of reading text AND understanding document structure makes multimodal models significantly more accurate than text-only models for this task.</p>