This topic covers AI image generation focused on photorealism and the practical workflows needed to use generated assets in production—advertising, e‑commerce, publishing, interior design, and game/entertainment pipelines. The current landscape emphasizes enterprise-ready, API-first platforms and specialist studios that bridge high-fidelity output with asset management and analytics. From multimodal generators to targeted editing suites, the tools aim to shorten time-to-market while preserving consistency and traceability. Key tools and roles: Stability AI provides enterprise-grade multimodal generation and developer APIs for large-scale image, video and 3D workflows; Recraft is an AI-first design studio delivering high-fidelity raster images plus native vector generation and production-ready mockups for designers and teams; Clipdrop offers an image-editing toolkit—background replacement, upscaling (up to 16x), relighting and cleanup—with API integration for automated pipelines; AI Interior Studio targets domain-specific photorealistic room redesigns with shoppable products; KDP Book Covers automates rapid, KDP-formatted cover concepts for self-publishers. Why it matters in 2026: demand for photorealistic, production-ready assets has shifted tool selection from experimental models to platforms that support scale, governance, and measurable marketing outcomes. Integration points—APIs, versioned asset exports, and hooks for A/B testing and attribution—are now core requirements. Practical considerations include maintaining visual consistency across variants, provenance and rights tracking, prompt/version management, and connecting generated assets to marketing attribution systems so creative variants can be tied to performance metrics. Choose tools based on output fidelity, format needs (raster vs vector), integration/APIs, and domain-specific capabilities.