IS AI TRULY CREATIVE? : AI might not feel, but it can move us to feel

When I first encountered generative AI, I didn’t expect it to change how I thought about creativity. But like many of us drawn to building, I couldn’t stop experimenting. Could AI help me express ideas more clearly? Could it extend—not replace—my creative process?

The early days were electric. With ChatGPT, I could map out ideas, synthesize research, and get feedback instantly. Soon I was doing the kind of work in hours that used to take days. But I wasn’t just chasing efficiency. I was trying to see whether this machine could be creative with me.

That’s a big word. “Creative.”

What Do We Mean by Creative?

Creativity has long been considered uniquely human. It’s rooted in intuition, emotion, and lived experience. We don’t just generate ideas—we feel them. They come from memories, contradictions, tensions we don’t yet understand. That’s why creativity often feels less like building something and more like uncovering something that was always there.

In 1926, psychologist Graham Wallas proposed a four-stage model of creativity:Preparation, Incubation, Illumination, and Verification.

• Preparation is the groundwork—gathering knowledge, exploring possibilities, immersing ourselves in a domain.
• Incubation is the pause—when the conscious mind steps back and lets ideas simmer in the background.
• Illumination is the spark—the sudden flash where it all connects.
• Verification is the test—refining, evaluating, and bringing the idea to life.

What makes this model powerful is how familiar it feels. It mirrors the actual rhythm of creative flow. The late-night walks. The scribbles. The waiting. The sudden click. It’s not just a process—it’s a human experience. And for the longest time, it was one that only humans could inhabit.

Until now?

A Leap in Capabilities

Over the past year, generative AI has become more than a tool—it’s becoming a co-creator. Systems like GPT-4o and Claude Sonnet have evolved beyond generating content; they now support deeply interactive creative processes. GPT-4o, for example, can write scripts, brainstorm ideas, and create on-brand marketing copy with tone and nuance.

Claude’s vast memory allows it to hold entire book manuscripts in context, helping authors write, edit, and maintain narrative continuity across thousands of words. These tools don’t just finish your sentences—they help shape your story.

For visual creators, platforms like Midjourney and Ideogram have taken major leaps. Midjourney’s Version 6 engine enables artists to generate stunningly coherent and detailed imagery, complete with legible text and refined stylistic controls. You can zoom, pan, inpaint, or even input reference images to guide the AI’s output—turning what once felt like a black box into a real-time creative loop.

And now, we’re entering the era of generative video. OpenAI’s Sora can take a single sentence and produce a short, cinematic video complete with lighting, camera motion, and scene consistency. It’s not Hollywood-ready—but it’s getting close enough to storyboard dreams, test atmospheres, and unlock conceptual worlds.

Perhaps most quietly transformative is GPT-4o’s native image generation. Unlike earlier tools, 4o’s multimodal core allows it to produce highly precise, photorealistic, and context-aware images—right in the flow of conversation. Want a comic strip, a scientific diagram, or a hand-drawn-style menu complete with correct text? GPT-4o can do that, and then refine it over multiple turns, maintaining coherence and design language throughout. It excels at visual communication: images that are not just beautiful, but useful. You can create infographics, iterate on design mockups, and even blend uploaded photos into fresh compositions.

What used to take a graphic designer hours can now be prototyped in minutes. And yet, the spark—the why—is still ours.

Because here’s what matters most: none of these tools work in a vacuum. The magic happens when human vision meets machine fluency. An architect can sketch a design and have AI generate atmospheres. A fashion designer can dream up styles and see variations instantly. A writer can describe a feeling and get ten ways to express it—each one different, each one sparking something new.

Are These Machines Creative?

Here’s the paradox: AI can now produce results that feel creative, even if the process behind them is mechanical. It learns from massive datasets—our art, our music, our writing—and rearranges those patterns in ways that surprise us.

In the Preparation stage, AI excels. It can access and synthesize more information than any human can. It’s a turbocharged researcher. A contextual sounding board.

Illumination is trickier. This is where inspiration strikes—the spark. But every now and then, AI offers a turn of phrase, a visual metaphor, a riff of music that feels… right. Not random, but fitting. Emotional even. It’s not feeling that emotion—but it’s producing an output that evokes it in us.

In my adventures with AI, I’ve had moments that felt like that. Fleeting, but real. One of them even sparked what would become the mission for The Rift. I remember the moment clearly—I sat speechless, staring at a response, feeling something shift. Out of curiosity, I started firing off more questions, trying to bottle the moment. But like all moments of inspiration, it slipped through. It felt human. It felt like a spark.

That’s where the line starts to blur.

Where Do We Go From Here?

AI isn’t dreaming. But it’s helping us dream differently.

The real story here isn’t whether AI can replace human creativity—it can’t. It doesn’t feel, it doesn’t care, and it doesn’t create with intention. The human spark—our curiosity, our contradictions, our desire to say something that matters—still sits at the center.

But the tools are changing. And they’re powerful.

Today’s AI can participate in every stage of the creative process. It can help with Preparation, by researching, curating, and proposing new directions. It can support Incubation, holding ideas in place while we step away and offering a starting point when we return. It can even assist in Verification, helping us refine and test ideas, polish drafts, and push our thinking.

And sometimes—just sometimes—it contributes to the spark.

The future of creativity isn’t about machines becoming more human. It’s about humans learning to collaborate with machines that amplify our reach. It’s about faster feedback loops, broader creative fluency, and new forms of expression that collapse the boundaries between media, time, and space.

We’ll see new creative roles emerge—prompt designers, AI composers, multimodal storytellers. We’ll learn how to navigate abundance without losing originality. And we’ll continue to ask better questions—not just of the machine, but of ourselves.

Because machines might not feel—but they can move us to feel.

And maybe, just maybe, that’s the beginning of something new.