Placing an AI-generated object into a real photograph used to require hours of manual masking, shadow painting, and color correction in Photoshop. Most creators skipped it entirely because the results looked obviously fake — floating objects, wrong lighting, hard edges that screamed "pasted on."

AI compositing tools have changed that equation. Modern blending algorithms now handle the technical heavy lifting — automatic edge detection, shadow generation, lighting matching, and perspective correction — that once demanded advanced editing skills. The result is that anyone can combine AI-generated elements with real photography and produce composites that hold up under close inspection.

This guide walks through the complete workflow for combining AI-generated images with real photos, from choosing the right base image to exporting a finished composite. It covers the technical process behind AI blending, the features that matter most in compositing tools, and step-by-step instructions for producing professional results in 2026.

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What It Means to Combine AI Images with Real Photos

Combining AI images with real photos means inserting, blending, or merging AI-generated visual elements into existing photographs so that the final image appears as a single cohesive scene. The goal is seamless integration — viewers should not be able to tell where the real photo ends and the AI-generated content begins.

1. From Traditional Photo Compositing to AI Editing

Traditional photo compositing in Photoshop follows a painstaking manual process. The editor creates precise layer masks to isolate the element being inserted, hand-paints shadows to ground the object in the scene, adjusts color curves to match the target photo's white balance, and corrects perspective distortion to align the element with the camera angle. A skilled compositor might spend three to six hours on a single high-quality blend.

AI-powered compositing compresses that entire workflow into minutes. Automatic segmentation handles the masking, intelligent lighting analysis matches the color temperature, and AI shadow generation creates realistic contact shadows without manual painting. The technical barrier that once limited compositing to professional editors has largely disappeared.

2. Common Types of AI-Photo Combinations

AI-photo compositing covers several distinct workflow types, each serving different creative and commercial goals. Object insertion places AI-generated products, characters, or props into real scenes. Background replacement swaps the environment behind a real subject with an AI-generated setting.

Image expansion extends a photo's boundaries with AI-generated content that matches the existing scene. Scene enhancement adds atmospheric effects — fog, light rays, particles — to real photographs. Each type requires slightly different techniques, but all share the same fundamental challenge: making real and AI-generated content look like they belong together.

3. Why Quality Depends on Visual Continuity

Every failed composite shares the same root cause: visual discontinuity between real and AI elements. When the light falls differently on the inserted object than on the surrounding scene, when shadows point in the wrong direction, when colors feel warmer or cooler than the environment, or when the scale is slightly off — viewers sense something is wrong even if they cannot identify the specific issue.

Understanding this principle is more important than mastering any specific tool. A creator who pays attention to light direction, shadow consistency, and scale alignment will produce convincing composites regardless of which software is used.

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Why Creators Use AI to Blend Images

The practical benefits of AI-photo compositing extend across creative, commercial, and logistical dimensions. Combining real photos with AI-generated elements solves problems that pure photography and pure AI generation each face individually.

1. Faster Visual Content Creation

Reshooting a product in a new location, adding a prop that was not available during the original shoot, or adapting an image for a different aspect ratio — these changes traditionally require scheduling a new production. AI compositing handles them from existing assets. A product photo shot on a white background can be composited into a kitchen scene, an outdoor café, or a holiday setting without leaving the desk.

For marketing teams working under deadline pressure, this speed advantage translates directly into campaign agility. Multiple creative variations can be produced from a single base photo in the time it would take to schedule a traditional reshoot.

2. Expanding What a Photo Can Show

AI compositing enables visuals that would be physically impossible, logistically impractical, or prohibitively expensive to photograph. A smartwatch floating above a mountain summit, a running shoe leaving a trail of energy particles, or a cosmetics product surrounded by fresh ingredients frozen in mid-splash — these concepts require either elaborate practical effects or full 3D rendering when done traditionally.

With AI compositing, the real photograph provides authenticity and texture while the AI-generated elements add creative ambition. The combination produces images that feel grounded in reality but extend beyond what a camera alone can capture.

3. Cost Efficiency Across Large Visual Campaigns

Brands producing content for multiple platforms, marketplaces, and audience segments need dozens of visual variations from every product or campaign shoot. AI compositing turns one base photo into many finished assets — each optimized for a different context — without proportional cost increases. AI image generators create the custom elements, and compositing tools blend them into the base photography, delivering a complete library of assets from a single production session.

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How AI Blends Generated Elements into Real Photos

The AI blending process involves several technical systems working in sequence. Each step addresses a specific challenge that traditionally required manual editing skills. Understanding this process helps creators troubleshoot issues and produce better results with any tool.

1. Background Removal and Subject Detection

The first step in any compositing workflow is isolating the element to be inserted. AI-powered background removal uses semantic segmentation to identify object boundaries at the pixel level. Modern models handle not just hard edges (the outline of a coffee mug) but also semi-transparent areas like glass, smoke, and fine hair strands that are notoriously difficult to mask manually.

The quality of this initial segmentation sets the ceiling for the entire composite. Jagged masks or lost fine details cannot be fully corrected later. Advanced background removal tools apply automatic edge feathering to create soft, natural transitions rather than the hard cutout look that betrays amateur composites.

2. Matching Lighting and Color

Lighting consistency is the single most important factor in whether a composite looks real or fake. The AI analyzes the target photograph to determine where the primary light source is, how intense it is, and what color temperature it carries. It then adjusts the inserted element's highlights, midtones, and shadows to match those characteristics.

Shadow generation is equally critical. An object placed in a scene without a shadow appears to float in midair. The AI calculates where contact shadows and drop shadows should fall based on the light direction it detected, then generates them with appropriate softness and density. Advanced systems also simulate reflected light — the subtle color bounce that happens when an object sits near a colored surface.

3. Perspective and Scale Adjustment

Objects photographed from one camera angle and inserted into a scene shot from a different angle create a spatial contradiction that viewers detect subconsciously. AI perspective matching analyzes the vanishing points and horizon line in the target photo, then transforms the inserted element to align with the established geometry.

Scale alignment works alongside perspective correction. A product that appears too large or too small relative to surrounding objects in the scene immediately breaks the illusion. The best compositing tools estimate real-world scale from contextual reference points — doorways, furniture, human figures — and suggest appropriate sizing for inserted elements.

4. Generative Fill and Photo Expansion

Generative fill lets users select any area of an image and have AI generate new content that blends seamlessly with surrounding pixels. For compositing, this is invaluable — cleaning up seams where elements meet, filling gaps left by repositioning objects, and creating smooth transitions between real and generated content.

Outpainting extends this capability to the edges of the frame. When a composite needs more visual space — wider for a banner, taller for a story format, or simply more breathing room around the subject — the AI generates new content that continues the scene naturally beyond the original boundaries. The generated extension matches the existing photo's lighting, texture, and content style.

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Key Features to Look for in AI Compositing Tools

AI compositing tools vary significantly in capability and approach. Some specialize in product photography, others focus on creative compositing, and a few attempt to handle everything. The features below determine whether a tool can produce professional-grade composites or only basic cutout-and-paste results.

1. Automatic Edge Blending

The transition between an inserted element and its new background is where most composites fail visually. Quality edge blending goes beyond simple feathering — it accounts for semi-transparent materials, fine details like hair and fabric threads, and the subtle color interaction that occurs where different surfaces meet. Look for tools that handle these complex edges without leaving visible halos, fringing, or unnatural sharpness differences between the object and its surroundings.

2. AI Lighting Matching

The tool should automatically analyze the target photo's lighting conditions and adjust the inserted element to match. This means correcting highlight placement, shadow density, ambient brightness, and color temperature — all in a single automated step. Shadow handling should include both removal of existing shadows that do not match the new scene and generation of new shadows that do.

3. Perspective Alignment

Automatic perspective detection ensures that inserted objects align with the scene's spatial geometry. The tool should analyze vanishing points, horizon lines, and surface planes in the target photo and apply corresponding perspective transformations. Without this feature, composited objects appear to exist in a different spatial reality than the rest of the scene — tilted at the wrong angle or receding incorrectly into the distance.

4. Generative Expand and Outpainting

Many compositing projects need more canvas space than the original photo provides. Generative expansion capabilities extend the image boundaries by generating new content that seamlessly continues the existing scene. This is essential when adapting photos to different aspect ratios, adding space for text overlays, or accommodating elements that extend beyond the original composition.

5. High-Resolution Export

Composites intended for commercial use need to hold up at print resolution and on large displays. The tool should support export at 4K minimum, with AI upscaling options available for larger output. Lossless export formats (PNG, TIFF) preserve quality for further editing, while optimized formats (JPEG, WebP) serve web delivery needs.

Feature	Why It Matters	What to Look For
Edge Blending	Prevents the "cutout" look	Hair/glass handling, anti-halo, soft transitions
Lighting Match	Creates visual consistency	Auto color temp, directional relight, shadow gen
Perspective Align	Objects sit correctly in space	Vanishing point detection, scale suggestions
Generative Expand	Creates room for composite elements	Seamless outpainting, aspect ratio adaptation
High-Res Export	Commercial and print viability	4K+ native, upscaling, lossless formats

💡 Did You Know? A 2025 survey by PHLEARN found that photographers who adopted AI-assisted compositing tools reduced their average editing time per composite by 65%, with the biggest time savings coming from automated masking and shadow generation — the two most technically demanding steps in traditional workflows.

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Step-by-Step: How to Combine AI Images with Real Photos

Creating a convincing AI-photo composite follows a logical sequence where each step builds on the previous one. These instructions work across any compositing tool and produce professional results when followed carefully.

1. Choose a Real Photo

The base photograph determines the quality ceiling for the entire composite. Choose a photo with clear, directional lighting — the light source should be identifiable so that inserted elements can be matched accordingly. Avoid heavily cluttered scenes where AI elements will fight for visual attention. The camera angle should be clean and readable, with a clear ground plane or surface where objects can naturally rest.

• Best base photos: Clear directional light, identifiable light source, adequate empty space, clean perspective lines
• Avoid: Multiple competing light sources, extreme wide-angle distortion, very dark or overexposed areas where elements will be placed

2. Generate or Select the AI Element

The element to insert can be generated fresh from a text prompt or sourced from an existing image. For AI-generated elements, write a prompt that specifies lighting direction and style to match the base photo. Including descriptors like "soft window light from the left" or "warm afternoon sunlight from behind" in the generation prompt produces elements that composite more naturally than generic outputs.

For elements sourced from existing photos, ensure the original lighting conditions are at least roughly compatible with the target scene. A product photographed under flat studio light composites more easily into most scenes than one photographed under strong directional light from the wrong direction.

3. Insert and Position the AI Image

Place the element into the base photo and adjust its position, scale, and rotation. The object should sit on the same spatial plane as other items in the scene — on the table surface, on the floor, at the correct height for its position. Use reference points in the original photo to guide alignment: furniture edges, floor tiles, horizon lines, and other objects at similar distances from the camera.

AI overlay tools can simplify this step by automatically detecting the target surface and snapping the element into position. Manual adjustments should focus on fine-tuning scale — using known objects in the scene as size references — and ensuring the element's perspective angle matches the camera angle of the base photo.

4. Match Lighting and Shadows

With the element positioned, the focus shifts to lighting integration. The compositing tool should adjust the element's brightness, contrast, and color temperature to match the surrounding scene. Verify three things: highlights fall on the correct side (facing the light source), shadow density matches the ambient conditions, and color temperature is consistent (no warm object in a cool-toned scene).

Add or adjust contact shadows so the object appears physically grounded rather than floating. The shadow direction must match the established light source in the base photo. If the tool does not generate adequate shadows automatically, AI shadow generation tools can create realistic drop shadows and ambient occlusion as a secondary step.

5. Refine Edges and Export

Zoom to 100% and inspect every edge where the inserted element meets the background. Look for hard cutout lines, color fringing, unnatural sharpness differences, and missing fine details. Use edge softening, inpainting, or AI blending tools to smooth any visible transitions.

Export the finished composite at the resolution required for the intended use. Save a master file in PNG or TIFF for future editing, then create optimized versions for each delivery platform — web JPEG, social media crops, and print-resolution files as needed.

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Popular Use Cases for AI + Real Photo Editing

AI-photo compositing serves practical needs across creative, commercial, and marketing applications. The use cases below represent the most common ways creators and brands are combining AI with real photography in 2026.

1. Product Marketing and Ads

E-commerce brands composite products into lifestyle environments to create marketing visuals that tell a story. A skincare bottle photographed on white can be placed on a bathroom counter, a bedside table, or a spa setting — each composite optimized for a different channel. The AI handles shadow generation and lighting matching, producing results that look like the product was photographed in each location.

2. Creative Portrait Photography

Portrait photographers use AI compositing to add surreal, cinematic, or fantastical elements to real portrait shots. A studio portrait gains dramatic depth when composited against an AI-generated misty forest, a futuristic cityscape, or an abstract gradient backdrop. The real photograph preserves authentic skin texture and expression that pure AI generation still struggles to match, while the AI-generated background adds creative dimension impossible to achieve in-camera.

3. Social Media Content

Content creators use compositing to produce scroll-stopping visuals without access to expensive production setups. AI-generated elements — floating objects, dramatic weather effects, surreal props — transform ordinary photos into shareable content that stands out in crowded feeds. The speed of AI compositing makes it practical to create unique visuals for every post rather than recycling the same set of edited photos.

4. Real Estate and Interior Design

Virtual staging is one of the highest-impact commercial applications of AI compositing. Empty rooms in real estate listings are composited with AI-generated furniture, rugs, artwork, and decor that help buyers visualize the space as a livable home. The AI matches the room's existing lighting conditions — window light direction, overhead fixture color — and generates appropriate shadows for each piece of placed furniture.

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Best AI Tools for Blending AI Images with Real Photos

The compositing tool market includes dedicated blending platforms, full-featured photo editors with AI capabilities, and AI generation tools with built-in compositing features. The tools below represent the most effective options for combining AI-generated images with real photography in 2026.

1. ArtSmart

ArtSmart combines AI image generation with inpainting and outpainting capabilities that make it a complete compositing solution in a single platform. Generate custom elements from text prompts, then use inpainting to blend them into target photos with automatic context matching.

The platform's inpainting feature is particularly effective for compositing because it analyzes the surrounding image context and generates new content that matches the existing lighting, texture, and style. Outpainting extends images naturally when composites need more visual space.

• Key Features: Text-to-image element generation, context-aware inpainting, outpainting for frame expansion, image upscaling for print-quality output, API access for batch workflows
• Best For: Creative compositing, product scene generation, image expansion, and complete generation-to-composite workflows
• Pros: All-in-one generation plus compositing, excellent inpainting quality, affordable from $19/month, fast processing, API for automation
• Cons: No drag-and-drop placement interface, compositing relies on inpainting rather than layer-based editing

2. Adobe Firefly and Photoshop Generative Fill

Adobe Firefly powers the Generative Fill and Generative Expand features inside Photoshop, providing the most comprehensive compositing environment available. Select any area, describe what should appear, and the AI generates content that blends with the surrounding image. Combined with Photoshop's full editing toolkit — layers, masks, adjustment layers, blend modes — the result is unmatched control over composite quality.

• Key Features: Generative Fill, Generative Expand, reference image support, full Photoshop layer editing, style transfer
• Best For: Professional designers who need maximum control and work within the Adobe ecosystem
• Pros: Industry-leading compositing control, seamless Photoshop integration, excellent generative fill quality, commercially licensed outputs
• Cons: Requires Adobe Creative Cloud subscription, steeper learning curve, slower than one-click tools

3. Photoroom

Photoroom specializes in product photo compositing with automated background removal, scene generation, and shadow rendering purpose-built for e-commerce. The one-click workflow transforms basic product photos into polished lifestyle scenes in seconds, making it the fastest option for high-volume product imagery.

• Key Features: Instant background removal, AI scene generation, automatic shadows, batch processing, e-commerce templates
• Best For: E-commerce brands needing fast, consistent product composites at scale
• Pros: Purpose-built for product compositing, extremely fast, strong automatic shadow generation, excellent batch capability
• Cons: Limited to product-focused use cases, template-dependent for scene variety, less flexible for creative compositing

4. Claid.ai

Claid.ai provides API-first image processing that includes background replacement, scene compositing, and automated image enhancement optimized for enterprise e-commerce operations. The platform processes thousands of images through consistent compositing pipelines without manual intervention.

• Key Features: API-driven background replacement, automated scene compositing, marketplace compliance checking, batch processing at scale
• Best For: Enterprise operations managing thousands of product images that each need environmental context
• Pros: Excellent API for automation, consistent output quality at high volume, marketplace compliance features, fast processing
• Cons: Enterprise-focused pricing, limited creative compositing, no manual editing interface

5. Kittl

Kittl combines AI image generation with a graphic design editor for creating composited marketing graphics. Users generate elements, place them into compositions with text overlays, and export finished visuals — all within one platform. The integrated workflow is ideal for social media content that combines photo backgrounds with AI-generated elements and design treatments.

• Key Features: AI generation, built-in design editor, layer compositing, text tools, marketing templates, multi-format export
• Best For: Content creators and marketers who need design-ready composites with branding elements
• Pros: Integrated generation-to-design workflow, marketing templates, no separate design software needed, accessible interface
• Cons: Basic compositing compared to dedicated tools, AI quality slightly below specialized generators, limited relighting

Tool	Best For	Auto-Blend	Generative Fill	Batch/API	Pricing
ArtSmart	Generation + compositing	Via inpainting	Yes	Yes (API)	From $19/mo
Adobe Firefly	Professional editing control	Yes (Photoshop)	Yes	No	Adobe CC sub
Photoroom	Product compositing at scale	Yes (auto)	Limited	Yes	Free + paid
Claid.ai	Enterprise e-commerce	Yes (API)	Yes	Yes (API)	Usage-based
Kittl	Marketing design	Basic	Limited	No	Free + paid

How ArtSmart Powers AI-Photo Compositing

ArtSmart stands out for compositing workflows because it handles both element generation and blending within a single platform. Generate a product, character, or environmental feature from a text prompt, then use inpainting to place it into a target photograph with automatic context matching. The AI analyzes the surrounding pixels and adjusts the generated content to match the lighting, texture, and style of the original image.

For teams producing composites at volume, ArtSmart's API enables programmatic workflows where product photos are automatically placed into different environmental scenes — generating dozens of lifestyle variations from a single base image without manual editing. Combined with upscaling for print-quality output, the platform covers the full compositing pipeline from generation to final delivery.

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Best Practices for Realistic AI Composites

Even with AI-assisted tools, convincing composites require attention to the visual details that separate professional results from obviously fake ones. Nearly every unconvincing composite fails for one of the same small set of reasons — and all of them are avoidable.

1. Do's and Don'ts for AI Image Blending

The most common compositing failures are lighting mismatches, missing shadows, incorrect scale, and hard edges. Addressing these four issues specifically transforms amateur results into professional-quality composites.

• Do: Match light source direction — if the sun comes from the left in the base photo, highlights on inserted elements must also come from the left
• Do: Add contact shadows wherever objects touch surfaces — shadowless objects look like they are floating
• Do: Use reference objects in the scene to gauge correct scale for inserted elements
• Don't: Ignore color temperature differences — a warm-toned product in a cool-toned scene is immediately obvious
• Don't: Leave hard edges on cutout elements — always soften transitions with feathering or AI edge refinement
• Don't: Forget depth of field — background elements should be slightly softer than foreground objects to match natural camera optics

2. Avoiding Fake-Looking Results

Before exporting any composite, run through three final checks. First, does every object have an appropriate shadow that matches the scene's light direction? Second, is the color temperature consistent across all elements — no warm objects in cool scenes or vice versa? Third, do the edges of inserted elements transition smoothly into the background without visible seams, halos, or sharpness differences?

Texture consistency is another detail that separates convincing composites from obvious fakes. AI-generated elements sometimes have a slightly different grain or noise profile than the real photograph. Adding a subtle unified noise layer across the entire composite — or running the finished image through a light film grain filter — helps unify the visual texture and prevents the "two different images pasted together" appearance.

3. Working with Multiple Composited Elements

Composites with multiple inserted elements require attention to how the objects relate to each other, not just how each relates to the background. Objects close together should cast shadows on one another. Foreground elements should partially overlap background elements where appropriate. Color spill from one surface should subtly influence nearby objects. These inter-object interactions are what make a multi-element composite feel like a real scene rather than a collage of separate images.

💡 Pro Tip: Before placing any AI element, identify the light source in the base photo and draw a mental arrow showing its direction. Every inserted element's highlights, shadows, and reflections must follow that same arrow. This single principle — consistent light direction — prevents the most common and most visible compositing mistake.

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Who Should Use AI Image Compositing Tools

AI compositing tools serve a broad range of professionals and creators who need to produce visual content that combines the authenticity of real photography with the creative flexibility of AI generation.

1. Marketers and E-Commerce Brands

Marketing teams and online retailers benefit from AI compositing by generating dozens of lifestyle product visuals from a single base photo. One product shot becomes multiple scene variations — each targeted to a different platform, audience segment, or seasonal campaign — without proportional increases in production cost or timeline.

2. Designers, Art Directors, and Photographers

Professional designers use compositing to prototype creative concepts rapidly, presenting clients with realistic visual mockups rather than abstract mood boards. Photographers integrate AI elements into their work to expand creative possibilities — adding environmental effects, extending compositions, and building visual narratives that go beyond what a single camera exposure can capture.

3. Social Media Creators and Real Estate Professionals

Content creators produce eye-catching composites that stand out in crowded social feeds without expensive production setups. Real estate professionals apply virtual staging to empty properties, compositing AI-generated furniture and decor into real rooms to help prospective buyers envision the space as a furnished home. Both groups benefit from the speed and accessibility that AI compositing provides over traditional editing workflows.

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Final Thoughts

Combining AI-generated images with real photography opens up creative and commercial possibilities that neither approach achieves alone. Real photos provide the authenticity, texture, and detail that ground an image in reality. AI generation adds the creative flexibility to insert, expand, and transform elements that would be impossible or impractical to photograph.

The quality of the final composite depends on the same fundamentals that have always determined compositing success: consistent lighting, accurate shadows, correct scale, and smooth edge transitions. AI tools automate the technical execution of these principles, but understanding why they matter is what separates composites that look real from composites that look assembled. Start with a strong base photo, match the lighting carefully, and inspect every edge before exporting — and the results will consistently impress.

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FAQ

1. What is the easiest way to combine AI images with real photos?
The easiest approach is using a tool with built-in inpainting or generative fill, like ArtSmart or Adobe Photoshop with Firefly. Select the area where the AI element should appear, describe or paste the element, and the AI blends it into the scene automatically — handling edge blending, lighting, and shadow generation without manual editing.

2. Why do AI composites sometimes look fake?
The most common reasons are mismatched lighting direction (shadows going different ways), missing contact shadows (objects appear to float), inconsistent color temperature (warm objects in cool scenes), and incorrect scale. Addressing these four issues specifically produces significantly more convincing results.

3. Can AI composites be used for commercial advertising?
Yes, modern AI compositing tools produce results that meet professional advertising standards. Major brands and agencies regularly use AI-assisted compositing for campaign visuals, product mockups, and marketing content. The key is starting with high-quality source photography, matching lighting carefully, and performing quality checks before final delivery.

4. What resolution do AI composites need for printing?
Print-quality composites should be at least 300 DPI at the intended print size. For a 16×20 inch canvas print, that means a minimum of 4800×6000 pixels. Most AI tools generate at lower resolutions initially, but AI upscaling can increase output to print-ready dimensions while preserving detail quality.

5. Do AI compositing tools work on mobile devices?
Several AI compositing tools — including Photoroom, Kittl, and some features of ArtSmart — offer mobile-friendly interfaces or dedicated mobile apps. While the most advanced compositing still benefits from a desktop workflow for precision editing, mobile tools handle product compositing and basic scene generation effectively for social media and quick turnaround projects.

Sources:

PHLEARN — The Ultimate Guide to Compositing in Photoshop Using AI,

PhotoshopCAFE — Composite Your Own Photos with Generative Fill AI,

Skywork AI — Multi-Image Fusion: Beginner's Guide to Blending and Compositing