The rise of creative provenance
Many people have been asking themselves an important question as they see new digital and print media like commercials, graphics, or even user interfaces:
“…was that made by AI?”
That question didn’t exist not that long ago; and now, it’s becoming less obvious to answer (at least in some cases). As consumers, we evaluated creative work on its quality and the overall outcome. We have rarely been given access to the work’s process or “behind the scenes” knowledge.
But with AI tools being relied on more and more to generate consumer media (and its output quality getting better), the line between human and machine-generated work is getting hard to detect. And general trust is wearing away; people want to know the source of who generated what. More than that, people want to know if what they’re consuming is “real” (whatever “real means to them).
To help build this trust back, creative work is shifting to not only show the final output, but also the process. People want proof of who made it, what tools were used, and the story of how it was made…kind of like a piece of art’s provenance.
But can you blame people (myself included)? Now that we’re in a world where almost anything can be generated by AI, we are naturally redefining what we value and trust about creative work.
Why we don’t trust what we see
AI and its integration within creative work have caused a shift in how work gets made, as well as how it’s perceived by you and me. There are many different factors where AI has negatively impacted creativity and influenced us to begin to question its authenticity.
One of the first areas is the cost of creation. Creative work used to require time and skill, but can now be generated in seconds. High-quality graphics or videos no longer signal “well-made by experts” since anyone with an AI tool and prompt can produce it. So the final deliverable has sadly become less meaningful because its labor has significantly decreased.
But we can’t talk about AI and creative work without its legal and ethical tension. Since the early stages of AI image generation with DALL-E and Midjourney, there are still unanswered questions around authorship, copyright, and compensation. So being able to trace how something was made, like what tools were used, what decisions were human vs. AI, and if the original authors were paid, is becoming more than just a nice-to-have.
With the deterioration of costs and ethics within AI-creativity, culture innately begins to put a higher value on “human-made.” So as AI and automation increase, people’s appreciation for work that feels well-crafted and real also increases. “Made by humans” is starting to function like a competitor differentiator (like slapping “Made in the USA” on product packaging).
Process is becoming the product
In practice, one of the more explicit signals of showing creative process is the position of “no AI.” Since we can no longer assume creative work was done by humans vs. machines, it now needs to be directly stated. Campaigns and independent creators are calling out when work is made entirely by humans, treating the absence of AI as a core feature.
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But alongside “no AI,” more of the nitty-gritty process is being shared. Many campaigns are beginning to show behind-the-scenes (BTS) content, like storyboards and in-progress iterations, for the purpose of verifying the work. They act as “evidence” that money and time were spent; and more importantly that a human was involved.
The creative process is no longer relevant to only stakeholder slide decks or case studies…its provenance has become part of the product message. Provenance is an expected piece of the final output, especially if there’s a need to build credibility (like if you state “no AI was used”).
Though how something was made is just as vital as what was made, it’s important to flag that this process itself can be manipulated. When being shown BTS content, you’re only seeing what the creators want you to see…possibly only the parts that help tell the right story.
So if the process is verification, how do we even know if that’s real? Though there’s no answer to this today, it’s critical to note that the creativity’s proof can easily become production (with AI involvement or not).
When does provenance matter?
Not every audience group or individual user will care about the provenance of the content they’re consuming. It also depends on a case-by-case basis; sometimes AI-assistance changes everything versus other times, it barely registers.
Think about when you watch a film or buy a concert ticket…
If you discover a film you assumed was written, directed, and performed by humans was largely generated with AI, it fundamentally changes how you interpret it. Since you begin to question the authorship, labor, and creative intent, the meaning of the work shifts. A film experience is about the output as well as the people behind it (think about the hundreds of names in the ending credits).
But now compare that to purchasing tickets online. You probably don’t care if the interface you’re using was designed with AI assistance. You more so care about the usability, speed, and general trust that your transaction will go through.
These scenarios show a spectrum between expressive and functional work; where provenance becomes situationally relevant or not.
On one side of the spectrum, the more a piece of work is tied to human expression, authorship, and originality, the more the audience tends to care about how it was made. In work like art, film, writing, or branding, the who and how are inseparable from the work’s meaning.
On the other end, in systems, utilities, or transactional experiences, provenance becomes less relevant. Audiences rarely ask how elements like a navigation bar were designed; they mainly care that the system works.
But with this spectrum, there’s a growing middle ground especially for UX UI design. Interfaces are not purely functional since they carry tone, personality, and decision-making power. And when AI is embedded into the experience, like making recommendations, users begin to care about how it works and what role AI is playing.
We’re already seeing this in UI patterns like: AI-generated labels in interfaces, explanations of how a result was produced, and toggles between “AI-assisted” and “manual” modes.
So provenance isn’t always a requirement, but needs to be designed for the context of the user and their experience.