The oldest assumption in photography and video used to sit quietly in the background. If you saw a plausible image, you usually assumed that some encounter with reality stood behind it. The AI era weakens that reflex. Public explainers for Content Credentials now state plainly that almost anyone can create realistic photos, videos, audio files and documents with a few clicks. YouTube requires disclosure for realistic altered or synthetic content, and the EU AI Act imposes transparency obligations for certain synthetic outputs. Once reality is no longer assumed, reality becomes a premium attribute.
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That is the paradox at the center of visual culture right now. Generative AI will absolutely produce more images, more videos, more variants, more speed, more convenience and lower costs. It will take a meaningful share of routine visual production because it is simply too useful not to. But abundance does not flatten every kind of value. It usually destroys the price of what is generic and increases the value of what is scarce. In a world of near-infinite synthetic supply, the scarce thing is no longer just a polished visual. The scarce thing is a visual with trustworthy origin, accountable process and real-world witness attached to it.
The visual market is starting to split
The easiest mistake is to treat all imagery as if it belongs to one market. It does not. There is a large and growing market for fast, plausible, flexible visual output where authenticity matters very little. Moodboards, concept visuals, synthetic backdrops, speculative product scenes, placeholder campaigns, stylized social assets and mass content variants all fit comfortably inside that world.
But there is another market where the image is doing more than looking good. It is helping a brand ask for trust. It is documenting a person, an event, a place, a promise, a product, a testimony or a lived moment. In that market, origin matters.
Getty Images’ research points directly at this shift. In its 2024 reporting on global consumer attitudes, the company said 98 percent of consumers agree that authentic images and videos are pivotal in establishing trust, while almost 90 percent want to know whether an image was created with AI. Getty also said people feel less favorably toward brands that use AI-generated visuals to create people or products, and suggested that pre-shot content may perform better when trust is the goal. That is not nostalgic resistance. It is a commercial signal.
This is why the future is unlikely to be a simple victory of prompts over cameras. It is more likely to be a bifurcation. Cheap, fast and visually convincing media will become more synthetic. Premium, trusted and accountable media may become more human, more documented and more carefully verified.
Real capture does something a prompt still cannot
A prompt can generate an image of almost anything. It can simulate rain on glass, the fatigue in a face, the grain of a handheld shot, the imperfect geometry of a street corner at dusk. It can imitate documentary aesthetics with eerie fluency. What it still does not do is literally undergo the event it depicts.
That difference matters more than it first appears. A photograph or a piece of video is not only a visual arrangement. In many contexts it is also a record of presence. Someone travelled. Someone waited. Someone gained access. Someone made a judgment call in real time. Someone responded to light, weather, emotion, pressure, uncertainty, movement or danger. Someone was answerable to what was actually there.
Authentic capture contains friction, and friction is becoming valuable. In an age when synthetic media removes the need for travel, access, timing and contingency, the fact that a human image-maker really did face those constraints becomes part of the meaning of the work. The image is no longer valuable only because of how it looks. It is valuable because of what had to happen for it to exist.
That is especially true when audiences ask questions that synthetic media cannot settle on its own. Did this happen. Was this person really there. Is this how the product actually appears. Is this footage evidence or illustration. Is this testimony embodied or fabricated. Those are not aesthetic questions. They are trust questions.
The demand for authenticity rises fastest where trust is expensive
The sectors most exposed to this shift are the ones where misleading visuals are costly. Journalism is the obvious case. World Press Photo prohibits AI images in its contest, and its verification rules make entries ineligible when people or objects are added, removed, rearranged or distorted within the frame. In late 2025, the Associated Press launched AP Verify, a system designed to help authenticate online photos, video and other digital content inside newsroom workflows. The industry is behaving as if proof itself has become part of the product.
But the same principle applies far beyond newsrooms. Travel brands sell the promise of a real place. Healthcare brands rely on credibility. Financial firms trade on confidence. Luxury brands sell scarcity, provenance and human craft. Wedding filmmakers sell memory, not simulation. Documentary creators sell witness. Independent creators sell intimacy and access. In all of these cases, synthetic imagery can still be useful, but it cannot simply replace authentic capture without altering the meaning of the offer.
Getty’s guidance makes this explicit. It says transparency expectations are rising in high-trust industries and argues that if authenticity is central to the campaign, high-quality pre-shot images and videos may be the better choice. That matters because it suggests the premium on real capture is not just moral or artistic. It is strategic.
There is also a subtler shift underway in audience psychology. Once viewers know that photorealism is cheap, they stop treating photorealism as proof. Surface realism loses evidentiary power. That changes the hierarchy of value. What rises is not merely “better looking” media, but media that can sustain scrutiny.
Authenticity is becoming infrastructure, not just a feeling
One of the clearest signs of this change is that authenticity is moving from rhetoric into technical systems. The Coalition for Content Provenance and Authenticity describes Content Credentials as a way to show provenance, method of creation and editing history. Adobe goes further and calls them a digital nutrition label for content, capable of indicating whether media was captured by a camera, generated by AI or edited in software.
That language matters. A nutrition label does not make food healthy by itself. It makes the product more legible. The same is true here. Provenance tools do not magically solve misinformation, forgery or deception. What they do is create a new layer of legibility around media origin. And in a high-noise environment, legibility is valuable.
The scale of adoption also matters. Content Credentials says the project is backed by more than 500 companies. Adobe documents growing support across creative tools and describes how credentials can persist through edits to create a transparent version history. OpenAI says ChatGPT-generated images include C2PA metadata, and that Sora videos ship with both visible and invisible provenance signals plus embedded C2PA metadata. These are not fringe experiments. They are early signs of a broader provenance economy.
The camera market is moving too. Leica says the M11-P was the first camera to integrate Content Credentials according to CAI and C2PA standards. Nikon says its Z6III provenance function can add signed metadata that proves an image was captured on a Nikon camera and records subsequent compliant edits. That is a remarkable shift. For years, cameras competed on resolution, autofocus, stabilization and color science. Now some of the competitive story is about verifiability.
This is the deeper point many casual observers miss. The industry is not merely inventing better AI. It is also inventing better ways to distinguish capture from generation, and better ways to preserve trust in captured media.
Human authorship is becoming more visible as value
The legal layer points in the same direction. In January 2025, the U.S. Copyright Office said generative AI outputs can receive copyright protection only where a human author determined sufficient expressive elements; mere prompting is not enough. That does not resolve every dispute around AI-assisted creativity, but it reinforces a principle with broad cultural force. Human authorship still carries legal and economic weight.
This matters for photography and video because the value of authentic capture is not only about truth claims. It is also about authorship claims. Who chose the moment. Who framed the scene. Who negotiated access. Who built trust with the subject. Who accepted the constraints of the real environment. Who shaped the final work with enough control, interpretation and intention that it bears the mark of a person rather than merely the output of a system.
In the AI era, “made by a human” may stop being an invisible default and become a visible differentiator. That applies to art, documentary work, branded storytelling and creator-led media alike.
The winners will not just shoot reality but preserve it
There is an important caveat here. Provenance metadata is useful, but it is not invulnerable. OpenAI notes that C2PA data can be removed accidentally or intentionally, and that many social platforms strip metadata from uploaded images. So the future premium will not belong only to people who capture authentic material. It will belong to people who capture it and preserve a credible chain around it.
That means the professional advantage of photographers and filmmakers may increasingly include things that once seemed secondary. Raw files. edit history. on-set context. behind-the-scenes documentation. publishing discipline. clear disclosure. identifiable authorship. trusted distribution. repeatable process. reputation.
In other words, creators may need to think less like image suppliers and more like custodians of origin.
This is not bad news for serious visual makers. It is a re-ranking of what counts as defensible value. Surface aesthetics alone will face relentless pressure because AI will keep improving at mimicry. But access, judgment, witness, reputation, accountability and process are harder to commoditize. The creator who can say “I was there, this is how it was made, and the record can survive inspection” may end up in a stronger position than the creator who can only generate a desirable look.
AI will not kill authentic image-making but it may make it premium
None of this means authentic photography and video will replace AI. That is not plausible. AI is too efficient, too cheap and too versatile for that. It will dominate plenty of categories, especially where speed matters more than origin. Generic commercial visuals, speculative concepts, visual filler, scalable creative variants and synthetic production assistance will keep growing.
What changes is the meaning of the upper tier.
As synthetic media becomes common, authenticity becomes scarce. As realism becomes cheap, verified origin becomes expensive. As the feed fills with things that could have happened, the images that really did happen may carry more cultural and commercial force. As generation becomes frictionless, the work that still requires presence gains a new kind of prestige.
That is why the future may not belong to the side that shouts loudest either for AI or against it. It may belong to those who understand that the visual economy is separating into layers. One layer values speed, flexibility and cost. Another values witness, provenance and trust. Those are different markets with different rules.
And that is the real paradox. The more synthetic media we produce, the less we can afford to treat authenticity as ordinary. In the age of AI, authentic photos and video may become more desired for the same reason handcrafted objects often rise in value during industrial abundance. Once imitation becomes effortless, the real thing stops feeling basic and starts feeling rare.
Author:
Jan Bielik
CEO & Founder of Webiano Digital & Marketing Agency
Sources
Getty Images Nearly 90% of Consumers Want Transparency on AI Images finds Getty Images Report
Getty Images newsroom summary of consumer attitudes toward AI imagery, transparency, trust and authentic visuals.
https://newsroom.gettyimages.com/en/getty-images/nearly-90-of-consumers-want-transparency-on-ai-images-finds-getty-images-report
Getty Images Building Trust in the Age of AI
Getty Images VisualGPS article on authenticity, audience trust and when human-shot visuals outperform AI-generated ones.
https://www.gettyimages.com/visualgps/creative-trends/technology/building-trust-in-the-age-of-ai
Content Credentials
Official overview of the provenance system, the Cr pin, and the companies backing the standard.
https://contentcredentials.org/
Adobe Content Credentials overview
Adobe documentation explaining Content Credentials as a digital nutrition label for content and describing use cases across capture, editing and AI generation.
https://helpx.adobe.com/creative-cloud/apps/adobe-content-authenticity/content-credentials/overview.html
YouTube Disclosing use of altered or synthetic content
YouTube policy page explaining when creators must disclose realistic altered or AI-generated media.
https://support.google.com/youtube/answer/14328491
World Press Photo What counts as manipulation
Official contest rules explaining prohibited alterations and why manipulated entries can be excluded.
https://www.worldpressphoto.org/contest/verification-process/what-counts-as-manipulation
The Associated Press AP introduces AP Verify to strengthen streamline online content verification
AP press release on its verification platform for authenticating online photos, video and other digital content.
https://www.ap.org/media-center/press-releases/2025/ap-introduces-ap-verify-to-strengthen-streamline-online-content-verification/
Leica Content Credentials in the M11-P
Leica page describing the M11-P as the first camera to integrate Content Credentials according to CAI and C2PA standards.
https://leica-camera.com/en-int/photography/content-credentials
Nikon releases firmware version 2.00 for the Nikon Z6III full-frame mirrorless camera
Nikon announcement detailing its image provenance function and signed metadata for authenticity verification.
https://www.nikon.com/company/news/2025/0827_imaging_01.html
U.S. Copyright Office NewsNet Issue 1060
Official summary of the Copyright Office position that AI outputs are copyrightable only where sufficient human authorship is present.
https://www.copyright.gov/newsnet/2025/1060.html
OpenAI C2PA in ChatGPT Images
OpenAI help documentation on provenance metadata in generated images and the limits of metadata preservation.
https://help.openai.com/en/articles/8912793-c2pa-in-chatgpt-images
OpenAI Launching Sora responsibly
OpenAI overview of provenance signals, watermarking and C2PA metadata in Sora-generated video.
https://openai.com/index/launching-sora-responsibly/
