As AI becomes becomes more pervasive in our daily work, we often wrestle with a big question: what should we automate and what should we protect as deeply human? We experience this profoundly in creative work. We are drawn to the speed and efficiency of new tools, yet we also crave the slow, messy process of making things by hand. We see the promise of AI as a collaborator, yet we feel the pull to hold onto our voice, our craft, and our way of thinking.
In my latest article and podcast episode, I explore that tension with an honest look at how creativity and technology shape one another, how artists and makers adapt when the ground shifts, and why curiosity might be a better starting point than fear as we imagine what comes next. I then explore seven key trends that we are likely to see in the upcoming years.
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What Will We Automate?
Recently, I gave a keynote on deeper learning and someone walked up to me afterward and asked, “What type of AI do you use for your videos and slideshows?”
“I don’t,” I answered.
His face dropped. “So, you have to pay someone to make your those sketch drawings for you?”
“No, I make them myself. I have a whole bank of drawings that I can access but I’m constantly adding to it,” I answered.
“If you were to use AI, what process would you use?” he asked.
I walked him through the prompt engineering process and share some ideas of programs that will do the animation for you so that you don’t have to move things around by hand. But I offered a warning. “You have to be really intentional about going beyond the default. But even when you do that, it sometimes looks too pre-packaged.”
He nodded. “So, when you make a sketch video, how long does that take you?”
“I’m faster than I used to be. So, now a 2-minute video might take about six to ten hours.”
“For a two minute video?” His eyes lit up.
Suddenly, I felt the need to justify my work. “I use these videos in blog posts, in trainings, in the courses I teach, and so much more. So, it feels like a good investment of my time.”
“I guess that makes sense,” he said. “Well, I think they look great.”
“Thanks for the kind words,” I answered.
But as I walked away, I felt a bit unsettled. We talked about time and money. We discussed efficiency and AI. But there’s a deeper truth at work. I make sketch videos because I love to draw. I’ve always been an incessant doodler and my sketches end up on my slides, the pictures within my blog posts, and the products I make.
The process of creating a sketch video also helps me think at a deeper level. See, I’m an expressive, verbose guy with ADHD. I can knock out a two-thousand word essay in 45 minutes. Yesterday, I did a deep dive 4k word essay for my job and it took about two hours. However, there’s a cost. Sometimes, I get careless with words. I over-explain. And, yes, editing can help. However, sketch videos force me to be clearer and more concise. The act of drawing visuals alongside a script allows me to think more concretely about abstract ideas. As a result, I tend to remember key theories at a deeper level. There’s almost a meditative element to it.
I understand why people use AI to generate images. But as someone who loves to write for the joy of writing and for the way it helps me think about ideas, I have no desire to swap my own writing for something AI-generated. As someone who loves to draw, I can’t imagine swapping out my own drawings for something generated by an LLM.
But I also realize that we are all wrestling with questions of what type of work we want to automate. I’m guessing a chef wouldn’t want to use AI to help with meal prep . . . but I do that all the time. A programmer might avoid AI altogether but I have found AI to be really useful for my novice-level coding.
I have mixed feelings about all AI content and what that does to artists, writers, coders, and any other makers. I think we need to engage in big conversations about copyright, intellectual property, and how AI will impact creative industries around the world. However, right now, I want to approach the topic of creativity and AI from a place of curiosity.
The Challenge of Defining Creativity
When we think of creativity, it’s easy to think about it through the lens of art. This is especially true with respect to AI, because of the huge leaps that have occurred with generative images and videos. I regularly wade through fake videos on Instagram ranging from current events to cute animal videos. I see so many AI-generated cartoons and infographics with that same dystopian yellowish, brownish color tone. But the truth is that creativity is bigger than simply making something new.
In the past, I’ve used the very unscientific distinction of the various types of creative approaches that educators use. This is simply a way of thinking about creativity in our everyday work:
Researchers tend to describe creativity in multiple domains that interact with each other. We often think of the cognitive domain, where people generate fresh ideas, remix concepts, and make connections that are not always obvious. But we also have the social and cultural domain, where a community decides on what counts as creative in the first place. I love Edward Clapp’s work on participatory creativity and the notion that we should look at the biography of an idea or a creative work itself rather than a solo genius pulling from the inside. An idea might feel brilliant on its own, but it becomes creative when others recognize its value. In other words, it’s the ecosystem that leads to creativity.
There is also the domain of expertise. This can sometimes look like creativity as a sort of craft. People often create their best work when they have spent time developing skills, building background knowledge, and learning the patterns of a field. Here we see the value of contextual thinking and empathy but also the functional novelty of divergent thinking. At the same time, there is the sense of individual voice, where personal qualities like curiosity, courage, and experimentation shape the creative process. When these domains overlap, creativity becomes something richer and more dynamic. It is less about a moment of inspiration and more about the way ideas, people, and environments interact.
But regardless of how we view creativity, we need cognizant of the relationship between creativity and technology.
The Reciprocal Relationship Between Technology and Creativity
As humans, we have a reciprocal relationship between our creativity and our technology. New tools open up fresh possibilities. They give us new approaches that we can use as craft new works or develop new solutions. At times, the technology leads to creative constraint, where the limitations in the technology actually leads to innovation:
Technology also shapes how we learn and explore new ideas. If creativity involves critical consumption, the technological tools we use to process and create media will inevitably impact how we curate and organize information as well. Technology can help us facilitate deeper problem-solving (think advanced computers versus slide rules). They allow us to experiment and express our ideas in new ways as well.
We often experience what Stuart Kauffman describes the adjacent possible. It’s a bit like a house where every new idea unlocks another room we could not even imagine ahead of time. Here, our technology functions as a key that opens fresh doors, revealing new spaces for experimentation and problem solving. Each tool we adopt expands the floor plan a little more, giving us options we did not even know existed. As we step into those new rooms, we create even more doorways waiting to be opened.
At the same time, creativity drives the need for better tools. It shapes the technology we create and adopt. Our current creative work inspires designers, engineers, and artists to build what did not exist before. As people imagine new ways to communicate or design or explore, they imagine new forms of technology to solve a need. In this back-and-forth exchange, creativity grows because technology evolves, and technology evolves because creativity keeps asking for more.
In general, as we experience this reciprocal relationship between our technology and our creative approaches, we see a few trends. First, creativity grows more expansive and varied while at the same time key tasks become more uniform. Think of the variety in writing that the printing press introduced while also leading to the loss of gorgeous manuscripts written by scribes. Technology also makes the creative process faster and cheaper. I can create a video on my phone, sketch out visuals on paper, scan those, and add them all on iMovie with very little time or financial cost. This has some huge potential, in terms of the democratizing of creativity (both in the ability to solve complex problems and in the ability to create new content) but it can also lead to cognitive atrophy, where we allow the technology to do too much of the heavy lifting for us.
I think it’s important to remember that technological innvoation, and even automation, isn’t new. This relationship between creativity and technology is actually a part of what it means to be human. We can talk about technology as a dehumanizing force but the ability to create and use tools to think creatively is a deeply human endeavor. That’s why I want to remain curious rather than judgmental about how this relationship is playing out with generative AI.
Seven Ways AI Will Transform Creativity
Here are a few ideas of trends we might see within the next few years.
1. AI Will Push Us to Be More Creative
Technology has always shaped the arc of art. The invention of mirrors, lenses, and new types of paint allowed artists to achieve incredible levels of realism. Think of the lifelike portraits of the Renaissance or the precise light of the Dutch Masters. But the invention of photography changed things overnight. Suddenly, realism was no longer the artist’s domain. The camera could capture a moment faster and more accurately than any painter could. But instead of ending art, it pushed art in a new direction.
Artists leaned into what photography couldn’t do. Things like emotion, abstraction, and perspective. Impressionism emerged with its blurred edges and fleeting light. The post-Impressionist Van Gogh used bold brush strokes to create an entirely new reality. Over the next century, we experienced the reductionist dada art, wild surrealism, distinct cubism, geometric humanism, 60’s pop art, and postmodern pastiche. Each movement embracing distortion, imagination, or irony. And each coming with the dire warnings of the “death of art.”
The more machines took over realism, the more artists leaned into what only humans could express and pushed the boundaries of the definition of art. I get it. Some people hate this process. Some people love hyper-realistic art. And there’s still a market for that (see the previous point about hand crafting work). But we also need to recognize that AI will push us to create art in new ways.
Similarly, AI will create certain types of simulations that will lead to huge creative discoveries in the sciences as well. It will lead us into new directions in terms of problem-solving.
2. People will use AI itself in a “hacker” way
When the drum machine first came out, critics warned that this would be the end of the live drummer and the studio musician. They had reason for concern. Record companies wanting to maximize profits could easily say, “Let’s not pay a human if a machine can do this instead.” But something else emerged from the process. Electronic music. If we think of rap and hip hop (electronic elements at its best) EDM (electronic at its worst), or that vaguely catchy 1990s hold music, we can see that drum machines sparked new musical innovations. We see it with sampling and reinterpretation. But we also see it with T-Pain (who actually has an amazing voice) using auto-tune the “wrong way” and sparking new artistic innovations.
We are currently in a space where people tend to use AI to replace certain current tasks in a way that feels somewhat normal. Write this email for me. Create this outline for me. We have also seen examples of people using AI in a negative hacker way, including making friends or having romantic relationships with AI.
But I think it’s important to recognize that we will see more and more uses of AI in ways that we could never have initially imagined (again, the idea of the adjacent possible). We will see the drum machine effect play out on a regular basis.
3. AI will replace aspects of human creativity and human creativity ends up being a niche luxury
For me, this is the most depressing reality of AI and creativity. We live in a capitalist society with large corporations that want to squeeze the highest profit value for shareholders. For what it’s worth, I love aspects of capitalism. I benefit from this system as a creator myself. But I also recognize that if AI can replace humans in certain creative domains, companies will jump on board with that. We’ve already seen this with the Coca-Cola ads filled with awful AI slop.
In this sense, it can help to look at automation in certain crafts like furniture. Right now, we can buy cheap furniture from IKEA and this has huge benefits for consumers. But if we want something that’s higher quality, durable, and customized, we can go with an expensive handcrafted option instead. I doubt that my IKEA bookshelves will last another decade. They are essentially invisible. However, we have an antique grand piano with character that will likely remain for decades.
In this scenario, AI will be the inexpensive option while human-generated creativity will be expensive. Authenticity and even small mistakes become a badge of honor. We will gravitate toward work that is idiosyncratic and distinct. Generative AI uses predictive analytics to create new work. In the past, the process has led to work that skews toward the derivative and cliche. I compared it to vanilla ice cream and mentioned that creators will have an advantage when they can make it their own:
Two years later, I feel more nuanced about this. Generative AI has shown some real potential in divergent thinking. It does well with connecting unrelated ideas and concepts. It’s getting way better at generating “functional novelty,” or works that are pretty original but also useful.
What that means for us is that we will need to think differently than the algorithm. If you are solving problems, you might use AI to solve a problem and then ask, “Is there a different way to solve this? Is there something I know that the AI is missing?”
If you are creating works of art, you might need to be wildly and unabashedly different:
Again, the concept of curation and taste plays a huge role here. You find your voice, in part by the ways in which you critically consume. But it’s also about experimentation. It’s about testing things out in front of an audience. It’s about identity and your self-story. As we think about student writing, voice and originality will play a more significant role if we want their work to stand out in a sea of sameness.
Creative work will be about story as much as finished products. In terms of problem-solving, the most expensive options will be the experts who can solve wicked problems and look deeply at unintended consequences. Here empathy and contextual understanding become more important than ever. Which leads to the next idea . . .
4. Human Elements Will Become More Important Than Ever
AI agents do a fantastic job taking on distinct roles when we give them clear prompts. But they aren’t sentient. They exist in a space that’s . . . Actually, they don’t exist in a space at all. And that’s a challenge for creative work. Because chatbots are doing so in a way that’s predictive they can’t understand the nuances of space and place. In other words, AI can’t read the room. It doesn’t know the local context of your school, your city, your region.
Similarly, you can program chatbots to be pro-social and even pretend to understand how a group feels or what they think. But it takes a human to demonstrate true empathy.
Whether you’re writing a novel, painting a picture, or solving a problem, context and empathy are more important than ever. I’ve written before about how I’ve worked with English and Social Studies teachers to rewrite their writing prompts to be more AI-resistant by focusing on context and empathy. But there’s a bigger trend at work. We want students to develop contextual understanding and empathy as mindsets, habits, and skills for the future.
We might also see a greater emphasis on synchronous, in-person elements. In the same way that people spend money on concerts rather than albums, we might see a greater emphasis on people experiencing creative work in a deliberately human, “here and now” way.
5. Co-creation will begin to look invisible
Right now, AI usage feels overt. We can typically tell when videos are AI-generated and we are already starting to see a newer form of information literacy where people are more curious and skeptical when they see grainy camera footage or an outlandish video of a politician. We are also in the midst of an AI backlash. We are seeing big concerns about what AI is doing to our brains, to our mental health, to our jobs, and to the environment. We are starting to explore some of the unintended consequences of AI. These concerns are all valid but there’s also a sense of moral panic that can creep in.
From our current standpoint, it’s hard to recognize that we will hit the boredom stage with AI. We are currently using the least advanced versions of AI platforms. But as platforms integrate AI into productivity software and we start using generative AI to streamline key tasks, so much of the AI will feel invisible. And, in fact, tasks that once seemed easier than might even feel laborious. That’s what happens with automation.
Case in point, there was a quote from Joanna Maciejewska that went viral about a year ago. “You know what the biggest problem with pushing all-things-AI is? Wrong direction. I want AI to do my laundry and dishes so that I can do art and writing, not for AI to do my art and writing so that I can do my laundry and dishes.” But here’s the thing. We already automated laundry and dishes. We literally have machines that do both and it now feels like a huge chore to set clothes or dishes in a machine and then put them back away.
So, as we think about creative work, it’s important to recognize that the AI will slowly feel more and more invisible to us. In all likelihood, we will take on what Ethan Mollick describes as a “cyborg approach,” where we work in partnership with the AI rather than completely outsourcing our work to the machines.
6. The line between curation and creation will get blurry
I once listened to a podcast interview with the legendary producer Rick Rubin. He mentioned that he didn’t have a ton of musical talented. He wasn’t the world’s greatest audio engineer, either. His secret talent was his taste. As he puts it, “The confidence that I have in my taste and my ability to express what I feel has proven helpful for artists.” His taste is part of what makes that Johnny Cash cover album so great and the iconic Red Hot Chili Peppers album, Tom Petty album, and my personal favorite the Beastie Boys’ License to Ill album so great.
As AI-generated content grows more sophisticated and creative, our tastes will become much more important. I sometimes wonder if the role of an artist might evolve toward being more like a producer in some respects (or a producer who then heavily modifies the work as an artist). It has me wondering if curation will become more important as a bridge between critical consuming and creating.
So, if we think about curation, it’s this overlap between being a critic and being a fan. A curator pays careful attention to context and larger trends and stories. Curators situate the work in a time and place in a way that then makes it timeless. They might add their own description of spin to the work. Often, curators connect works to one another as they organize information and artifacts.
But that’s also what we want with our students. We want them to have both an excited passion and a nuanced care for what they are learning. We want them to pay attention to context and purpose in the information they consume. We want them to make connections and provide their own lens.
This is more important than ever in a world of AI. I find fascinating that so many people who generate AI images have suddenly started paying attention to art history. And they’ve gotten really intricate in using AI to combine styles and then refine that over and over again. I realize that this might not seem like “true art.” Then again, photographers weren’t considered true artists at first as well. And many “true artists” have teams of other artists who do the work for them (think Jeff Koonz). They’re essentially the producers or creative directors.
7. AI Will Actually Fuel and Sustain Creativity
This is actually something I hadn’t really thought of until I was talking with creativity expert Dr. Brett Fischer. I reached out to him after reading (well, perusing) his dissertation and he shared this idea of AI as a form of friction.
“AI actually fuels and sustains creativity and reinvestment in work by giving you the same productive friction, alternative perspectives, and rapid iteration that defined the partnership between Daniel Kahneman and Amos Tversky. It helps you think more deeply by challenging assumptions, generating counter-models, offering multiple framings of the same idea, and accelerating the refinement of drafts and concepts. Because it can shift roles – devil’s advocate, co-writer, synthesizer, or parallel thinker – it becomes a consistent source of intellectual dialogue that expands your thinking rather than replacing it. With memory and continuity across projects, AI supports sustained, evolving collaboration, giving you a reliable partner who strengthens clarity, creativity, and insight.”
I love this idea of generative AI as a dynamic thought partner who can change roles in a way that actually adds friction and leads to deeper thinking rather than merely replacing tasks. Here, generative AI is hitting the higher Redefinition level of SAMR rather than functioning as a transactional platform for tasks that we don’t want to do. It’s less about automation and more about reimagining what can be done. Instead of leading to cognitive atrophy, AI as a dynamic thought partner actually deepens our thinking.
In the end, the exciting is that our students will get to be a part of reimagining how to use AI in creative ways. As educators, we can fight against academic dishonesty and cognitive atrophy but we can also provide a compelling alternative that will draw students in.
