Batch Editing Wedding Photos with AI

Choosing a tool is covered in the best AI wedding editing software; the wider sequence from ingest to delivery is on wedding photography workflow with AI.

The three ways to batch edit

Batching is either a manual sync, a fixed preset, or a trained profile applied per image. In Lightroom you can copy settings from one photo and paste them to a selection, or use Sync and Auto Sync to carry slider changes across selected photos; check Adobe's help documentation for the current menu path and shortcuts. A preset applies the same values to everything, so mixed lighting leaves exceptions to fix by hand; see AI profiles vs presets. A trained profile predicts per image according to the vendors, with the preparation described in how to train a profile.

A grouped batch in Lightroom Classic

A batch works best when each group shares one lighting condition, because sync copies identical values. Aftershoot's batch-editing guide (a vendor blog from a company that sells a competing product) describes the sequence below; check Adobe's help documentation for current menu names.

1. Group by light before you edit. The guide's examples of lighting conditions are direct sun, shade, window light, tungsten and flash; as our illustration, getting ready, ceremony, portraits, reception and a flash dance floor might each get their own master frame. A venue change inside one block, such as a doorway between indoor and outdoor light, is a reason to split the group.
2. Edit one master per group. Fix white balance, exposure and tone on a single representative frame.
3. Select the group with the master active, then open Sync. The guide advises clearing all boxes and ticking only what should match, rather than syncing everything.
4. Review the grid, then check a few frames at 100%. The guide names Match Total Exposures for exposure that drifts inside a group; treat that as a vendor suggestion to try on your own frames.

Auto Sync applies each slider change to every selected photo as you make it, which suits a global tweak and is risky otherwise: a crop, spot-removal or brush stroke made while it is on lands on every selected frame. The same guide warns against syncing crop, spot removal and brush, linear and radial masks, says sharpening and noise reduction should be synced only within the same ISO range, says AI masks can be synced (Lightroom re-detects the subject) but should be checked, and notes that large batches with AI masks can slow Lightroom and that an Update AI Settings step may be needed. How long that takes on your machine is something to time, not assume.

The table summarises the vendor guide and general Lightroom behaviour; it is not a tested rule.

Fitting an AI tool into the batch order

Where an AI tool sits in the sequence decides whether ratings and edits survive. Aftershoot's Lightroom workflow guide prefers culling before import and lists one-time setup for a Lightroom Classic catalogue: turn on automatic XMP writing, enable Smart Previews on import, and map star and colour labels before the first cull. It says that without automatic XMP writing edits already made in Lightroom can be lost when Aftershoot writes its ratings, that images with offline originals and no Smart Preview cannot be edited, and that its Edit In command sends a copy to Aftershoot, so duplicates need labelling before delivery. It also says the catalogue-based steps apply to Lightroom Classic and not to cloud Lightroom. All of this is Aftershoot's own description. How Narrative and Imagen treat existing XMP: not found in sources reviewed, so test on a copied catalogue.

Cull before you batch. Pay-per-photo cost scales with frames processed, and a hypothetical 700 delivered images per wedding is under a quarter of 3,000 shot frames. Example: 10 weddings at 700 images is 7,000 photos, or $350 at Imagen's listed $0.05, against $1,500 for all 30,000 frames (excludes the culling add-on and the US$7 monthly base fee the pricing page lists; arithmetic, not a measurement).

How each tool runs a batch

As of 8 November 2026, from vendor pages; Aftershoot prices per its pricing blog post, updated 5 November 2026, which says it checked the pricing page in October.

Sources: Aftershoot pricing tiers, Aftershoot homepage, XMP article, Narrative presets, Narrative pricing, Imagen plugin page, Imagen pricing.

The Aftershoot homepage also warns that preview rendering may be unreliable on Intel integrated graphics or GPUs under 2 GB of VRAM. Imagen processes edits on its servers from uploaded smart previews, so a connection is implied, though its plugin page states no connection requirement. Poor venue connectivity would matter for a cloud step and not for local processing; see Imagen review for its path.

Vendor speed claims

Vendor statements; arithmetic on them is not a measurement.

Taken at face value, 0.5 seconds per photo is about 8.3 minutes for 1,000 images, which excludes upload, download and your review. That gap between claimed processing and finished gallery is what to time.

Example, arithmetic on the vendor claim only: 0.5 seconds a photo on a 3,000-frame wedding is 25 minutes of claimed processing, about 19 hours across 45 weddings. That excludes upload, download, Lightroom reading the result and your review pass. If a tool only saves time when review is quick, the review pass is the number that decides.

Example: cost at 10, 25 and 45 weddings

Flat plans do not rise with batch size; pay-per-photo does. Arithmetic on cited prices at a hypothetical 3,000 RAW frames per wedding, all batched (an upper bound), annual billing, not a measurement.

Use the cost per 1,000 images calculator with your culled counts.

Where your files go

A batch can mean a local process or an upload, and several data terms conflict or could not be read, so none of these is recommended here on confidentiality grounds.

Aftershoot

per its transparency page, images are processed locally for batch culling, editing and retouching; custom editing-profile training uploads the images you choose; with learning on, culling sends small-resolution versions to its servers, which you can turn off at album import; storage is on Google Cloud, with deletion on request generally taking 7 to 14 days. The homepage separately says files never leave your machine and images are never stored on its servers, and the 2023 privacy policy says images and edits it collects are used solely for training its models; the policy says it applies to all information collected through its Websites and Service, and whether locally processed images count as "collected" is not stated. All vendor statements; terms of service source inaccessible (404).

Narrative

per its Select page, Personal Preset training uploads images and edit data and culling is local; sharing previews to improve Narrative is optional and off by default.

Imagen

smart previews upload; whether RAW files upload: not found in sources reviewed; Terms of Service not obtained.

Exit terms

Aftershoot Edit: cancel any time, custom profiles deleted when the plan ends unless $4 a month is paid (per the pricing post; an older support article says profiles are stored on cancelling, so confirm), one pause a year of up to three months. Narrative: "Change or cancel anytime"; refund terms not found in sources reviewed. Imagen: self-serve cancel; the listed annual Limitless plan is paid upfront and disputed for new buyers; monthly Limitless does not fall back to pay-as-you-go.

Who should pick what

Controlled light, one look

a preset and Lightroom sync may be enough.

Mixed light, flat bill

Aftershoot Edit. If local batch processing matters, Aftershoot says Edit runs on your computer (vendor claim; training uploads and the policy conflict are unresolved, see above).

Low volume or uneven year

Imagen pay-as-you-go.

Considering handing batches to a person

AI editing vs outsourcing.

Check this in your trial

1. Take 1,000 frames from a real gallery and note the clock time for each stage: import, any upload, processing, download, appearing in Lightroom, and your review.
2. Count the frames you correct by hand afterwards.
3. Check whether Lightroom reads the returned edits and keeps them adjustable.
4. Run the batch with the internet off to see which tools still work.
5. Check what uploaded and whether any learning upload can be turned off.
6. Before the first run, copy the catalogue and confirm automatic XMP writing is on, so an AI tool's write-back cannot overwrite edits you made in Lightroom.
7. Split the gallery by lighting group and compare the correction count per group; a tool that does well in the reception group may not in mixed church light.
8. Put one frame with an offline original into the batch and see whether the tool needs a Smart Preview for it.

Original test pending: WeddingWorkflowLab plans to time a 1,000-frame batch per tool on a licensed wedding gallery, from import to edits visible in Lightroom, and record the hand corrections.