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Artificial intelligence is often framed as a productivity tool. Organizations evaluate AI based on its ability to automate tasks, accelerate workflows, and improve operational efficiency. Those outcomes are important, but they represent only one dimension of AI's potential.
A more interesting question is what happens when AI becomes part of the creative process itself.
That question sits at the center of It Writes Itself, an interactive experience created by Mike and Sammi Jacobson that explores the relationship between human creativity and artificial intelligence. In Episode 1 of Why Isn't This AI Thing Working?, host Jesse Lampe sits down with the duo to discuss how the project came to life, what they've learned from experimenting with AI, and why the future of creativity may be defined less by replacement and more by collaboration.
While their work exists in the world of storytelling and entertainment, the lessons extend far beyond the stage. Their experience offers a compelling perspective on how people interact with AI, where human creativity still matters, and what leaders should consider as AI becomes increasingly integrated into everyday work.
Like many AI projects, It Writes Itself began with curiosity.
Mike and Sammi were not trying to optimize a process or solve a specific business problem. Instead, they wanted to explore what might happen if AI became an active participant in a creative experience. Could it contribute to storytelling in real time? Could it influence narratives in unexpected ways? Could audiences interact with AI as part of the performance itself?
Those questions eventually evolved into an experience that blends audience participation, storytelling, and AI-generated content into a collaborative creative process.
What makes the project interesting is not simply the technology behind it. It is the willingness to experiment without knowing exactly what the outcome would be.
That mindset often gets lost in enterprise AI conversations. Organizations understandably focus on business cases, ROI projections, and operational efficiencies. However, many of the most valuable AI use cases are not obvious at the outset. They emerge through exploration, experimentation, and a willingness to test new possibilities.
The history of innovation is filled with examples of technologies that became valuable in ways their creators never initially anticipated. AI may prove to be no different.
One of the strongest themes from the conversation is the distinction between generating ideas and creating meaning.
Generative AI is remarkably effective at producing content, concepts, and possibilities. It can generate hundreds of ideas in seconds, identify patterns across large amounts of information, and make connections that humans might overlook.
But generating ideas is not the same as understanding which ideas matter.
The value of AI often comes not from the output itself, but from the human judgment surrounding it. People provide context, evaluate quality, recognize relevance, and determine what will resonate with a particular audience.
This dynamic becomes especially apparent in creative work. AI can help expand the range of possibilities, but humans remain responsible for shaping those possibilities into something meaningful.
As AI tools become more capable, this distinction becomes increasingly important. The question is no longer whether AI can generate content. The question is how people use that content to create value.
There is a common assumption that advances in AI will reduce the importance of human creativity. Mike and Sammi's experience suggests the opposite.
When content generation becomes easier, creativity becomes more valuable.
The ability to ask thoughtful questions, identify compelling ideas, understand audiences, and connect seemingly unrelated concepts becomes a differentiator. These are the skills that help transform raw outputs into experiences that people find useful, memorable, or impactful.
In many ways, AI raises the ceiling on what is possible while simultaneously increasing the importance of human judgment.
Technology can generate options at scale. Humans determine which options are worth pursuing.
Technology can produce information. Humans provide meaning.
Technology can help create. Humans decide why creation matters.
For leaders navigating AI adoption, this is an important perspective. The conversation should not focus exclusively on what AI can do. It should also focus on the uniquely human capabilities that become more valuable because of it.
Much of the public discussion around AI centers on replacement. Will AI replace jobs? Will it replace writers, designers, developers, analysts, or marketers?
The experience behind It Writes Itself points toward a different possibility.
Rather than replacing human creativity, AI can become a collaborator that expands what people are capable of producing. The most interesting outcomes often emerge when humans and AI contribute different strengths to the same process.
AI offers speed, scale, and the ability to generate possibilities.
Humans bring judgment, experience, empathy, taste, and purpose.
Together, those capabilities can create something neither could produce independently.
This lesson applies well beyond creative projects. Whether organizations are using AI to support product development, customer engagement, decision-making, or innovation efforts, the most successful outcomes often come from combining human expertise with machine capabilities rather than viewing them as competing forces.
While It Writes Itself is a creative experiment, it highlights several lessons that business leaders should consider as they evaluate their own AI initiatives.
First, experimentation still matters. Not every valuable AI use case begins with a detailed business case. Some of the most impactful opportunities emerge when teams are given the space to explore what is possible.
Second, human judgment remains essential. AI can accelerate idea generation and expand possibilities, but people are still responsible for determining what is relevant, useful, and meaningful.
Third, organizations should think about AI as a collaborator rather than simply a tool. The greatest value may come not from replacing human effort, but from augmenting human capability.
Finally, curiosity remains a competitive advantage. The organizations that learn the most from AI will likely be those willing to experiment, adapt, and discover new applications as the technology continues to evolve.
Conversations about AI often focus on productivity, efficiency, and automation. Those outcomes matter, but they are only part of the story.
Projects like It Writes Itself highlight another dimension of AI's impact: its ability to influence how people create, collaborate, and explore new ideas. They remind us that some of the most interesting questions surrounding AI are not about technology alone. They are about how humans choose to engage with it.
As organizations continue to experiment with AI, the most valuable lesson may be a simple one: technology can generate possibilities, but people are still responsible for turning those possibilities into something meaningful.
▶ Watch Episode 1: "It Writes Itself"
Artificial intelligence is often framed as a productivity tool. Organizations evaluate AI based on its ability to automate tasks, accelerate workflows, and improve operational efficiency. Those outcomes are important, but they represent only one dimension of AI's potential.
A more interesting question is what happens when AI becomes part of the creative process itself.
That question sits at the center of It Writes Itself, an interactive experience created by Mike and Sammi Jacobson that explores the relationship between human creativity and artificial intelligence. In Episode 1 of Why Isn't This AI Thing Working?, host Jesse Lampe sits down with the duo to discuss how the project came to life, what they've learned from experimenting with AI, and why the future of creativity may be defined less by replacement and more by collaboration.
While their work exists in the world of storytelling and entertainment, the lessons extend far beyond the stage. Their experience offers a compelling perspective on how people interact with AI, where human creativity still matters, and what leaders should consider as AI becomes increasingly integrated into everyday work.
Like many AI projects, It Writes Itself began with curiosity.
Mike and Sammi were not trying to optimize a process or solve a specific business problem. Instead, they wanted to explore what might happen if AI became an active participant in a creative experience. Could it contribute to storytelling in real time? Could it influence narratives in unexpected ways? Could audiences interact with AI as part of the performance itself?
Those questions eventually evolved into an experience that blends audience participation, storytelling, and AI-generated content into a collaborative creative process.
What makes the project interesting is not simply the technology behind it. It is the willingness to experiment without knowing exactly what the outcome would be.
That mindset often gets lost in enterprise AI conversations. Organizations understandably focus on business cases, ROI projections, and operational efficiencies. However, many of the most valuable AI use cases are not obvious at the outset. They emerge through exploration, experimentation, and a willingness to test new possibilities.
The history of innovation is filled with examples of technologies that became valuable in ways their creators never initially anticipated. AI may prove to be no different.
One of the strongest themes from the conversation is the distinction between generating ideas and creating meaning.
Generative AI is remarkably effective at producing content, concepts, and possibilities. It can generate hundreds of ideas in seconds, identify patterns across large amounts of information, and make connections that humans might overlook.
But generating ideas is not the same as understanding which ideas matter.
The value of AI often comes not from the output itself, but from the human judgment surrounding it. People provide context, evaluate quality, recognize relevance, and determine what will resonate with a particular audience.
This dynamic becomes especially apparent in creative work. AI can help expand the range of possibilities, but humans remain responsible for shaping those possibilities into something meaningful.
As AI tools become more capable, this distinction becomes increasingly important. The question is no longer whether AI can generate content. The question is how people use that content to create value.
There is a common assumption that advances in AI will reduce the importance of human creativity. Mike and Sammi's experience suggests the opposite.
When content generation becomes easier, creativity becomes more valuable.
The ability to ask thoughtful questions, identify compelling ideas, understand audiences, and connect seemingly unrelated concepts becomes a differentiator. These are the skills that help transform raw outputs into experiences that people find useful, memorable, or impactful.
In many ways, AI raises the ceiling on what is possible while simultaneously increasing the importance of human judgment.
Technology can generate options at scale. Humans determine which options are worth pursuing.
Technology can produce information. Humans provide meaning.
Technology can help create. Humans decide why creation matters.
For leaders navigating AI adoption, this is an important perspective. The conversation should not focus exclusively on what AI can do. It should also focus on the uniquely human capabilities that become more valuable because of it.
Much of the public discussion around AI centers on replacement. Will AI replace jobs? Will it replace writers, designers, developers, analysts, or marketers?
The experience behind It Writes Itself points toward a different possibility.
Rather than replacing human creativity, AI can become a collaborator that expands what people are capable of producing. The most interesting outcomes often emerge when humans and AI contribute different strengths to the same process.
AI offers speed, scale, and the ability to generate possibilities.
Humans bring judgment, experience, empathy, taste, and purpose.
Together, those capabilities can create something neither could produce independently.
This lesson applies well beyond creative projects. Whether organizations are using AI to support product development, customer engagement, decision-making, or innovation efforts, the most successful outcomes often come from combining human expertise with machine capabilities rather than viewing them as competing forces.
While It Writes Itself is a creative experiment, it highlights several lessons that business leaders should consider as they evaluate their own AI initiatives.
First, experimentation still matters. Not every valuable AI use case begins with a detailed business case. Some of the most impactful opportunities emerge when teams are given the space to explore what is possible.
Second, human judgment remains essential. AI can accelerate idea generation and expand possibilities, but people are still responsible for determining what is relevant, useful, and meaningful.
Third, organizations should think about AI as a collaborator rather than simply a tool. The greatest value may come not from replacing human effort, but from augmenting human capability.
Finally, curiosity remains a competitive advantage. The organizations that learn the most from AI will likely be those willing to experiment, adapt, and discover new applications as the technology continues to evolve.
Conversations about AI often focus on productivity, efficiency, and automation. Those outcomes matter, but they are only part of the story.
Projects like It Writes Itself highlight another dimension of AI's impact: its ability to influence how people create, collaborate, and explore new ideas. They remind us that some of the most interesting questions surrounding AI are not about technology alone. They are about how humans choose to engage with it.
As organizations continue to experiment with AI, the most valuable lesson may be a simple one: technology can generate possibilities, but people are still responsible for turning those possibilities into something meaningful.
▶ Watch Episode 1: "It Writes Itself"
