Q: How are publishers using AI in image creation & editing?
A: AI based tools now assist with virtually every stage of the imaging process in publishing. The most useful way to think about this isn’t as a set of individual tools, but as a single capability running across the whole workflow.
The technologies may be new, but the idea isn’t. Publishers have always enhanced and manipulated images, adopting the technology of the day to do it. What has changed is reach and speed: an automated workflow can now realistically handle 80% or more of a publisher’s requirements, at a quality and pace that far surpasses most manual processes.
That doesn’t remove the need for skilled Photoshop operators. The nuance of crafting and retouching critical images still relies on the human hand and the real gains come from combining the two.
Q: What is a particularly illustrative use-case?
A: A leading UK news publisher integrated an AI imaging platform into its existing editorial system, aiming to automate as much image toning as possible across its dailies and weekly and monthly magazines. The platform is now part of the content creation process itself, rather than a separate stage.
• Moving image correction to layout. The integration has shifted routine image correction from the Photoshop department to the page teams. Cropping, toning, cut-outs and upscaling are completed in a few clicks from within the content system. The result has been significant efficiency gains, and the Photoshop team now concentrates on high-quality work for magazine covers and the special editions.
• Photoshop AI tools. The imaging team also benefits from AI technology. Photoshop’s capabilities now include a multitude of AI based tools, including the removal of unwanted objects and portrait retouching. Arguably, the most beneficial of these is ‘generative fill’, which extends the background of an image with content that blends naturally into the existing scene. For example, if a portrait-oriented photograph of the King and Queen walking through Windsor Park needs to fit a landscape layout, an operator adds trees, grass and sky to fill the surrounding space in seconds, using a single click or a simple text prompt.
• Fully generated imagery. Pure AI image generation, using the text prompt engines, is used sparingly and applied mainly to infographics, where readers do not typically question the authenticity of an image. The diverse styles produced have proven effective at drawing readers’ attention.
• Unique requirements with a single workflow. Each department has its own requirements and preferred image styles, however, the singular approach allows every team to benefit from the full range of tools in its own way.
The online teams use the upscaling toolset to repurpose social media imagery which are traditionally low resolution and blocky. Combined with the image enhancement process, this significantly improves the quality and clarity. The AI background removal tool has enabled more creative page designs while dramatically reducing turnaround times. Complex cut-outs, such as headshots with flowing hair, sports imagery and food photography, now take seconds rather than tens of minutes.
• Digital provenance. Digital provenance is a concern across the publishing industry. Following the introduction of the C2PA technical standard, and amid growing liability questions around AI generated images, tools are now available to verify an image’s provenance where credentials exist (alongside detectors that estimate the likelihood an unsigned image was AI generated). The publisher has deployed this technology on specific titles, and it is proving effective in its initial stages.
Combining these tools in a single platform, accessible from the content management systems already in use, is an approach applicable to publishers of any size or location. It supports more diverse design styles, higher image quality on screen and in print, and an improved experience for readers, while delivering efficiencies right across the process.
There’s a common anxiety that AI represents something new and troubling in image creation and manipulation. However, it’s worth making the point that the idea is not new in any way. Enhancing and manipulating images has always been part of the publisher’s process, which has only ever evolved by adopting the technology of the day and AI simply continues that lineage.
Q: What are your three top tips?
- Automate the routine. Most publishers imaging is high volume, repetitive work – toning, background removal, upscaling, tagging. That’s what AI does best and fastest, freeing your team rather than replacing their judgement.
- It’s an ‘AND’ not an ‘OR’. The biggest gains come from combining AI with your existing skills and systems, not treating it as a separate entity. Aim for direct integration into your CMS and page layout tools; the goal is imaging that happens inside the workflow.
- Build in provenance and trust. As AI touches more of the image, be able to show what was done to it. Label AI generated images and preserve C2PA Content Credentials through your workflow, especially with 2026 EU AI Act transparency rules for publishers reaching EU readers.
About us
For nearly 30 years, Pixometry has been powering the imaging workflows of publishers around the world. Continuously evolving, our advanced image enhancement software intertwines the latest AI technologies with our proprietary imaging engine to deliver sharper, richer images that stop readers in their tracks, in print and digital alike.
Email: derek.milne@pixometry.com
Web: www.pixometry.com
Derek and the other contributors to our AI Special will be taking part in an ‘AI Special – Q&A’ webinar on 24th November. Click here for more information and to register.
This article was included in the AI Special, published by InPublishing in October 2026. Click here to see the other articles in this special feature.
