As the AI landscape continues to change across analytical, procedural, and generative work, these tools are becoming increasingly practical for creative professionals. AI can take on repetitive tasks, process large amounts of information, and solve production problems that would have been difficult or time-consuming only a few years ago.

The tools are also becoming easier to integrate into existing workflows. Generative features now live directly inside applications like the Adobe suite, while platforms like ChatGPT and Claude can assist with research, organization, ideation, and task execution. In production, AI can help when a line of dialogue needs repair, an image is slightly out of focus, an unwanted element needs to be removed, or a missing piece of motion needs to be created from an existing still. These are practical applications where the technology can solve a specific problem without replacing the creative process around it.

I believe the strength of creative work comes from making a connection with the viewer and telling a story from a human point of view. Fully generative work is not always the best tool for that. Audiences can recognize when something feels disconnected from real experience, and there are also legitimate questions around the financial, environmental, and creative implications of how generative AI is developed and used.

At the same time, ignoring these tools does not make sense to me. I continue to experiment with AI to understand what it does well, where it fails, and where it can improve an existing creative process. The work shown here is part of that exploration.

I expect these tools to become increasingly commonplace. My goal is to understand them well enough to use them deliberately, while keeping concept, judgment, storytelling, and human connection at the center of the work.