- What changed: Adobe brings AI critique right into the shot
- How AI critique works in practice
- Immediate impact on e-commerce and retail workflows
- Opportunities for content creators and social teams
- What to do now: strategic positioning for marketing managers
- The work still in progress: limits and open questions
- Looking ahead: where AI-assisted visual production is going
Adobe has announced a new AI feature inside its camera app, known as Project Indigo. The system can now analyze images shot directly in the app and give automated, critical feedback. It also removes any type of background with a single tap. It's a significant update for anyone managing visual content professionally.
So the impact isn't limited to photographers. It affects e-commerce marketing teams, social campaign managers and anyone producing visual assets at high volume. As a result, the average quality of content created on the go could rise significantly, cutting post-production time. Automatic background removal in particular is a feature retail workflows have been asking for years.
At SHM Studio, we're following this shift closely. Building AI tools into the moment of capture, not just the editing stage, is a paradigm shift in how brands manage their visual production. For anyone working in digital marketing, that's a real opportunity to cut production costs and speed up content publishing cycles.
What changed: Adobe brings AI critique right into the shot
On July 20, 2026, Adobe released a major update to its experimental camera app, Project Indigo. According to TechCrunch, the new feature lets artificial intelligence analyze photos taken in the app and give instant, critical feedback. The system can also now remove any type of background from images, not just plain ones.
This builds on the background removal features already in Photoshop and Adobe Express. But the real novelty is the context: the AI works during image capture, not only in post-production. That changes how many content teams operate.
So we're no longer talking about a simple editing tool. Adobe is redefining what a professional camera app is, adding real-time quality assessment.
How AI critique works in practice
The AI critique feature analyzes several image parameters. In particular, it evaluates composition, exposure, sharpness and how well the subject fits its context. Feedback comes back as text, with specific, actionable suggestions.
As with tools like Adobe Firefly, the model is trained on a corpus of professional images. As a result, the system doesn't just detect technical flaws. It also judges how effectively the image communicates against established aesthetic standards.
On top of that, background removal now works on complex scenes: hair, transparent objects, reflective surfaces. This overcomes the limits of earlier segmentation models. The result can go straight into production, with no extra manual retouching.
Immediate impact on e-commerce and retail workflows
For marketing leads at e-commerce companies, this feature has direct implications. Producing product images normally takes several steps: shooting, selection, background removal, optimization, approval. Each stage costs time and resources.
With Project Indigo, at least two of these steps are compressed into the moment of capture. Teams can significantly reduce the time-to-publish of visual content. For retailers managing catalogs with hundreds of SKUs, the operational savings can be substantial.
According to research by McKinsey, content production speed is now one of the main competitive factors in digital marketing. So tools that speed up this cycle have a direct impact on commercial performance.
At SHM Studio, we work every day with retail and B2B clients. That's why we're watching this shift with real interest: it directly affects the workflows we manage for our clients.
Opportunities for content creators and social teams
Beyond e-commerce, AI critique also matters to professionals working on organic content. Many social media managers and content creators shoot images on the go, often without access to advanced editing tools.
In this context, getting instant quality feedback before you even publish is a real advantage. And being able to remove backgrounds right in the app eliminates one of the most frustrating steps in producing content for platforms like Instagram, LinkedIn or Pinterest.
For companies investing in LinkedIn campaigns or organic content strategies, visual quality is a key driver of engagement rate. Tools that raise the average quality bar, even without advanced photography skills, have a measurable impact on performance metrics.
What to do now: strategic positioning for marketing managers
First, check whether Project Indigo is already available for your Adobe accounts. The feature is currently experimental, but Adobe has historically been quick to bring Project features into its main suites.
Next, it's worth mapping your internal visual production workflows. In particular, identify the bottlenecks in the chain from shooting to editing to publishing. Those are the points where Adobe's AI can deliver the biggest operational savings.
Finally, consider how this feature fits with the tools you already use. For example, anyone using Adobe Express or Creative Cloud to produce assets for Google Ads campaigns can benefit from a smoother, more consistent pipeline.
It's also useful to train internal teams to use AI feedback properly. The risk is relying on automated assessments uncritically and losing the creative and strategic side of visual design.
The work still in progress: limits and open questions
Even so, a few areas of uncertainty deserve attention. First, the quality of AI critique depends on the training corpus. The system may therefore favor conventional aesthetics over deliberately non-standard visual choices.
It's also still unclear how Adobe will handle analyzed images in terms of privacy and data use. This is a sensitive issue, especially for companies producing confidential content or content covered by NDAs. Before adopting it at scale, you need to check the updated terms of use.
Similarly, automatic background removal, though improved, isn't foolproof on complex surfaces. For high-stakes productions, human review is still necessary. For mass production, though, the current level of accuracy is already good enough for many use cases.
To dig deeper into the ethical and technical implications of AI in visual production, read the Harvard Business Review analysis of AI and creativity.
Looking ahead: where AI-assisted visual production is going
The direction is clear. AI won't replace the photographer or the creative director. But it will keep shrinking the distance between capture and publishing. As a result, the skills marketing teams need will shift from technique to editorial curation and visual strategy.
Over the next 12-18 months, it's reasonable to expect other players in the industry to build in similar features. Competition among AI-powered camera apps is already intense, with players like Google, Apple and specialized startups. Adobe has every reason to consolidate its position before the market gets crowded.
For Italian marketing managers, the message is pragmatic. Tools like Project Indigo don't call for an immediate organizational overhaul. Instead, they slot into your existing workflows and improve them step by step. So the best time to start experimenting is now, while the feature is still in early access.
If you want to understand how to integrate these tools into a structured AI marketing strategy, or how to streamline visual content production for SEO copywriting and digital campaigns, the SHM Studio team is happy to talk. We also regularly publish analyses of digital marketing tools and trends on our blog. And if you'd like to explore everything we offer, the SHM Studio services cover the full spectrum of digital marketing, from SEO to web development.
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