The best AI photo editors of 2026

Photoshop has been the professional image editing standard since 1990, and the AI features Adobe has added since 2023 are the most significant change to how it is used in a very long time. Generative Fill lets you select an area, describe what should be there, and have it produced in context — matching lighting, perspective and grain. Generative Expand extends a photograph beyond its original frame. Neural Filters handle retouching, colourisation and depth adjustments that previously took skilled manual work.

What makes these more than a novelty is that they operate inside an existing professional workflow. The output lands on layers, with masks, in a file that goes through the same colour management and delivery pipeline as everything else. A retoucher can generate an element and then treat it exactly like any other element. Standalone generators produce an image and stop; Photoshop produces a component of a composition.

The Firefly provenance matters commercially. Adobe trained on Adobe Stock and licensed material rather than an open-web scrape, and offers indemnification for enterprise customers. For agencies delivering client work, that answer to "where did this come from" is worth real money.

The cost is the subscription, and the resentment about it is long-standing and justified — there is no perpetual licence, and stopping payment stops access. Affinity's free relaunch under Canva has made that comparison sharper. Photoshop remains the tool professionals use; it is no longer the only serious option.

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Apple Photos does a surprising amount of machine learning that most users never think of as AI. It recognises faces, pets, landmarks, objects and text in images; it lets you search in plain language for a beach photo from last summer; it assembles Memories automatically; and with Apple Intelligence it added Clean Up, which removes unwanted objects and people from a shot.

The distinguishing characteristic is that this happens on the device. Analysis runs locally, the resulting index stays on your hardware, and the library is end-to-end encrypted in iCloud. Competing services perform equivalent analysis on their servers. For a photo library — the single most personal dataset most people own, full of family, homes and locations — that architectural difference is worth taking seriously, and it is the strongest argument for staying inside Apple's ecosystem for this particular job.

The costs are real. On-device processing means the initial indexing of a large library takes time and battery. It means older hardware does not get the newer features at all. And it means the models are constrained by what fits on a phone: Clean Up is decent on simple backgrounds and clearly behind Photoshop's Generative Fill on anything complex.

It suits anyone in the Apple ecosystem wanting good organisation and light editing without a subscription or a second app. Serious editing still belongs in Lightroom, Capture One or Photoshop.

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GFPGAN and Real-ESRGAN are open-source models out of Tencent ARC's research group, and between them they underpin a surprising amount of the commercial photo restoration market. Real-ESRGAN handles general image upscaling and artefact removal — enlarging and cleaning photographs, illustrations and compressed images. GFPGAN specialises in faces, reconstructing detail in blurred, damaged or very low-resolution portraits.

They are frequently run together, because the two problems are different. General upscaling models tend to make faces look wrong; the human visual system is far more sensitive to facial error than to any other kind. Running Real-ESRGAN for the image and GFPGAN for the faces produces results that neither achieves alone, and that pipeline is what a great many paid restoration services are quietly doing behind a payment form.

Because they are open source and permissively usable, you can run them yourself: a local install with a GPU, a Colab notebook, or a hosted API like Replicate. Doing so costs nothing beyond compute and puts no photographs on a third party's server, which matters for family archives and sensitive material.

The trade-off is convenience. Running them yourself means dealing with Python environments, model weights and command-line arguments. Commercial tools wrap the same capability in an interface, add batch processing, and handle the edge cases. For a technical user with a large archive, the open-source route is better in every dimension except effort.

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Luminar Neo is Skylum's AI-first photo editor, and its pitch is that operations which take a skilled retoucher twenty minutes should take one click. Sky replacement that automatically masks a horizon and matches the new sky's colour temperature to the foreground. Portrait tools that smooth skin, brighten eyes and adjust facial lighting. Relighting that separates subject from background and lets you light them independently. Structure and atmosphere controls that add depth without manual dodging and burning.

For enthusiast photographers this is genuinely useful. The results are usually good, occasionally excellent, and reaching them requires no understanding of masking or luminosity ranges. It works as a standalone editor or as a plugin inside Lightroom and Photoshop, which lets it slot into an existing workflow for the specific operations it does better.

The trade-offs are consistency and control. Automated masking works most of the time and fails visibly when it does not — hair, glass, foliage against a bright sky. The looks it produces tend toward the dramatic, which is a stylistic choice rather than a neutral starting point, and it does not have Lightroom's cataloguing or Capture One's tethering and colour tooling.

Skylum has kept a perpetual licence available alongside subscription options, which is increasingly rare and is a real part of the appeal. It suits hobbyists and enthusiasts who want strong results quickly. Professionals generally keep it as a plugin rather than a primary editor.

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MyHeritage is a family history platform — records, family trees, DNA testing — that became briefly famous for something adjacent. Deep Nostalgia, which animates faces in old photographs so a still portrait blinks and turns its head, went viral in 2021 and introduced the company to millions who had no interest in genealogy. The reaction split between moving and unsettling, often in the same person.

The wider photo toolkit is more consistently useful: colourising black-and-white images, repairing scratches and fading, sharpening soft scans, and enhancing low-resolution faces. For anyone digitising a box of family photographs, the restoration results are genuinely impressive and the emotional value is real in a way that most software is not.

The core platform underneath is a serious genealogy product with a large international records collection, particularly strong in European archives, and it competes directly with Ancestry. Subscriptions gate the records access, and the photo tools have free allowances with paid tiers beyond them.

The consideration worth pausing on is data. Genealogy services hold family trees, historical records and, for DNA customers, genetic information about people who never consented — relatives are identifiable through a match they did not submit. MyHeritage has had a data breach in its history. None of that makes the service unusable, but anyone weighing a DNA test should read the current policy on data retention, law enforcement access and third-party sharing before submitting a sample.

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Upscale.media does one job through a browser: take a small or soft image, enlarge it, and reconstruct plausible detail rather than simply interpolating pixels. Upload, wait, download. Basic use requires no account, which is most of why people end up there — the friction is close to zero when you need one image fixed quickly.

The quality is reasonable for the price. Modest enlargements of photographs come out acceptably; product shots and logos usually clean up well. Push it harder and the characteristic failure modes appear: over-sharpened edges, waxy skin texture, and invented detail in areas where the original had none. Text and fine patterns are where it struggles most obviously, because the model is guessing at structure it cannot see.

Paid tiers raise the resolution ceiling, allow batch processing and remove watermarking on larger outputs. That positions it as a utility rather than a professional tool, which is the right framing.

For professional work — printing large, restoring archival material, or upscaling anything a client will inspect closely — Topaz Photo produces materially better results and gives you control over how much detail is invented. Magnific goes further still in the creative direction. Both cost real money, and both are worth it when output quality is the point. Upscale.media is for the moment when you need an adequate result in thirty seconds and nobody is going to zoom in.

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