What Visual 1st Revealed About the Photography Industry

AI Everywhere, But Not All the Time

Every October in San Francisco, where robot taxis are busily roaming the streets, something peculiar happens. The photography industry’s old guard—print manufacturers, stock agencies, software makers—sits down with its new blood: the brilliant engineers building AI-powered photo services, mobile apps, editing tools, and verification systems. For a day and a half, they network, demo, debate, and exchange ideas in a uniquely productive collision of innovation and pragmatism.

What is generative AI’s actual impact on the photography industry, and how is the market evolving in response? The talks, panels, and firechats revealed something unexpected: all AI all the time is not the most evident path to success, even if the appeal is enticing.

Market Evolution: Four Signals of Change

The conversation at Visual 1st kept circling back to the same underlying questions: What role do different tools play? How are consumers actually adopting AI features? What’s the market rewarding, and what’s it rejecting? And most importantly: what does a sustainable, human-centered relationship with AI look like in photography?

These weren’t abstract debates. They were urgent, practical questions from an industry watching generative AI reshape its offerings, its workflows, and its customer base in real time.

The Resurrection of Film: One Tool Among Many

The most visible sign of the industry’s recalibration? The revival of instant film.

Ashley Reeder Morgan,  Vice President of Marketing Fujifilm, shared  that cumulative global sales of its Instax line- their instant film camera- have exceeded 100 million units since launching in 1998, with record sales continuing for four consecutive years. At Visual 1st, both Fujifilm and Ricoh, with their new point and shoot film only camera,  made it clear: in the age of digital, film remains vitally important.

Fujifilm shared findings from multiple studies on how users described film. The words that emerged were consistent: nostalgic, unaltered, tangible, and more meaningful. Importantly, users emphasized that film isn’t just about the photograph, it’s about the social, physical experience of sharing. A moment isn’t just captured when it’s taken; it’s truly captured when it’s recalled together, at the same time and place, via a print in hand.

But here’s what matters most: it’s not a binary world. Users of film use digital as much as anyone else. They’re not rejecting technology; they’re being strategic. Film is one tool in a whole toolkit, each one picked when most appropriate for the right social setting, the right moment, the right intention. Sometimes you want the immediacy of digital. Sometimes you want the deliberation and physicality of film. The choice depends on what and who you’re trying to communicate to, not on ideology.

The Creator Economy: The Paradox of Quality and Connection

The firechats brought this tension into sharper focus.

Jim Louderback, who built and sold multiple creator startups to Paramount and led VidCon for eight years, framed a core insight: the creator economy is fueled first and foremost by a desire to connect: to find an audience of people who share similar interests, perspectives, and values. But there’s a fundamental element of truth involved. Creator success is ultimately based on how true their audience feels they are. That authenticity is the currency.

Yet here’s where the contradiction emerges: creators need to supply their audience with the best quality content to sustain their livelihood. And the tools available to them have become entirely AI-driven. Every tool, every app, every functionality now relies on one or many AI models to execute.

From culling to retouching, the presentations at Visual 1st showed how deeply AI has impressed every aspect of image post-production. Google Photos,  now with 1.5 billion monthly users and over 9 trillion photos and videos stored,  exemplifies this: the AI now operates even at the point of capture, suggesting best framing and helping compose images with people not physically in the same place at the same time. It offers photo perfection to everyone, with no regard to whether it’s an unaltered reproduction of reality.

The result is a genuine paradox. Creators have access to unprecedented tools for producing professional-quality content and can produce better content faster than ever before. But here’s the catch: while audiences want quality content, they’re also watching for signals of authenticity. They’re looking for truth. And when every tool a creator uses is making decisions on their behalf, smoothing, optimizing, and perfecting, where does the authentic signal live?

This played out across the conference in quiet contradictions: presenters talking about AI democratizing creativity and helping creators sustain their livelihoods, while simultaneously acknowledging that democratized perfection can feel sterile, manufactured, inauthentic. The challenge isn’t rejecting these tools. It’s making intentional choices about which AI-assisted enhancements preserve connection and which ones erode it.

The Trust Crisis: Who Decides What’s Real?

Which brought the conference to its central panel: The Trust Advantage—Using Proven Image Authenticity as Your Competitive Edge in the Age of GenAI.

This wasn’t hypothetical. Representatives from Shutterstock, Canva’s Pexels, Catch and Release, and Imatag ( myself) tackled the question directly: How do we know what’s a real image and what’s been generated? How do we verify the authenticity of news images, product shots, and wedding pictures?

The consensus is urgency: without labels, without transparency, without guardrails, AI is a powerful tool for democratizing creativity, but without those structures, it can wreak havoc on our ability to make sound decisions. A manipulated news photo looks identical to a real one. A generated product shot can’t be distinguished from the genuine article to the human eye. A wedding photo that’s been algorithmically perfected has lost something essential, even if nobody can quite say what.

The panels on Photo+Video Convergence and Agentic AI expanded on this. The future isn’t just about better tools; it’s about tools that work in the background, suggesting frames, auto-generating variations, and optimizing for engagement—while leaving the creator unaware of where human intention ends and algorithmic suggestion begins.

The Print Innovation Wildcard

Tom Hughes, CEO of RPI Print and Blurb.com, and overseeing facilities in Seattle, Atlanta, Rochester, and Eindhoven, brought another thread: physical print innovation. The Photo Print Innovation panel explored new materials, production methods, and business models. Print isn’t dead; it’s evolving. It’s where digital meets tangible, where a creator’s work becomes something real, something verifiable, something that can’t be deepfaked or regenerated on demand.

This matters because print is the proof. It’s where authenticity becomes material.

What Terrell Lloyd Knows That Algorithms Don’t

Terrell Lloyd, who’s been the San Francisco 49ers‘ photographer since 1996, brought something to the conference that no AI panel could quite capture: the relationship between photographer and moment. With 30 years of experience capturing everything from Super Bowls to corporate events, Lloyd’s work isn’t about technical perfection. It’s about seeing what matters, when it matters, and having the judgment and intuition to know the difference between the shot and the shot.

That distinction, human judgment, creative intuition, the ability to recognize truth in the moment, became the unspoken anxiety beneath every panel. AI is getting faster at generating images. But is it getting better at choosing which moments matter?

What the Market Is Actually Telling Us

Here’s what emerged: the revival of film, the creator economy’s tension between quality and connection, the urgency of image verification, and the rise of agentic AI aren’t four separate trends. They’re four signals about how the photography market is evolving in response to generative AI.

Film is coming back because consumers are choosing it—not rejecting technology, but strategically reaching for different tools depending on context and intention. Creators are navigating AI-driven toolsets, but the ones winning aren’t the ones over-optimizing; they’re the ones making intentional choices about which enhancements serve their audience. Image verification and provenance tracking are becoming essential because the market needs trust mechanisms when AI-generated and real images become indistinguishable. And agentic AI is generating interest, but also caution: the industry is asking whether background automation actually serves creators or erodes their decision-making.

At their core, all four point to the same market reality: in a world where AI is making creation faster and cheaper, what’s actually driving consumer and creator behavior is selectivity, intentionality, and transparency. The industry isn’t rejecting AI. It’s learning which applications serve genuine needs and which are just technological solutions looking for problems.

 

Main image by Photo by Samer Daboul