Newsrooms will embrace some AI-generated imagery

In the last weeks of 2025, as I write this prediction, my social media feeds are awash with a new set of pronouncements about the death of photographic truth. As a historian of photography, I’m familiar with obituaries of this sort, which tend to circulate in popular media at moments when new photographic or image-editing technologies arrive on the scene that force us to reevaluate photography’s capacity to represent reality accurately. (The launch of Photoshop in 1990 prompted an especially vociferous outcry in this respect.)

The cause of this latest set of death notices is Nano Banana Pro, also known as Gemini 3 Pro Image; it is the newest offering from Google’s suite of AI image-generation tools. Nano Banana Pro has been described as creating images that are “hard to distinguish from the real thing” and, according to one tech reporter who couldn’t resist the low-hanging fruit, “so realistic it’s bananas.” Online responses to its release have tended to combine awe at its seeming accuracy and convincingness in creating photographic-looking images with a raft of concerns about its potential for deceptive use.

Like other means of AI image generation, Nano Banana Pro is a technology that is existentially distinct from photography. Rather than depicting people, things, or environments from life, as photography does, AI image generators fashion images by drawing on massive datasets. They are, we might say, regurgitative media. For this reason, most news institutions’ embrace of AI-generated imagery will be limited in 2026 to those realms of journalism where images aren’t expected to faithfully capture news events. We must remember that there are broad swaths of the newspaper where photographs haven’t traditionally been held to stringent expectations of accuracy, and where “news illustrations” are already welcome. This is where the use of AI-generated imagery in the press is most likely to grow.

Photographic truth is not going to be suddenly, cataclysmically “dead” in 2026, because photography’s epistemic authority has not been dismantled overnight. Critical attitudes toward photography’s capacity to represent the real both predate AI and will continue to exist alongside it. Photography’s plasticity, and photographers’ selective representation of reality, have been topics of discussion among viewing publics since the 19th century. This said, I do think that in 2026, the ease with which a range of actors will be able to use AI to create photographic-looking images will prompt more people to consider what other kinds of value photographs possess, beyond the indexical truth-telling capacities with which they’ve traditionally been associated.

The emergent photographic values that we come to embrace might provide fruitful grounds for a more critical evaluation of AI systems writ large. When we think about photographs not as evidentiary vessels but instead as points of connection between photographers, subjects, and spectators, what new possibilities emerge? Many photography scholars have shifted their attention in recent years toward the ways in which photography is premised on and productive of collaboration: working together, sharing a common world. Such values stand in powerful contrast to the fundamentally extractive presence of AI, whose existence is rooted in the appropriation of the intellectual, creative, and environmental commons. In 2026, as AI systems embrace enshittification while many grow cognitively dependent on them, critiques of their guiding principles will become more urgently needed than ever.