When Every AI Tool Looks Like a Layoff

Production Professionals Must Shape AI Before Others Decide Its Role

Film and television workers are being asked to judge technology that is still emerging before us. New tools are arriving faster than the industry's rules and working practices can adapt, and no one has a complete map of how AI should function across a production. That uncertainty gives production professionals a brief opportunity to help decide what comes next.

In conversations across the industry, I have often felt the discussion close down as soon as AI is mentioned. Systems that generate finished work are grouped with tools that organize information or improve communication, ending the conversation before their functions are examined. Many of the people withdrawing possess exactly the knowledge needed to draw meaningful boundaries.

That reaction is grounded in a brutal labor market. According to Bureau of Labor Statistics data reported by The Wall Street Journal, Los Angeles County's motion picture industry lost 42,000 jobs between the end of 2022 and the end of 2024. An April 2026 Otis College report found that AI did not cause California's recent creative-economy contraction, though its full impact may still lie ahead. Even so, for many people living through that collapse, AI feels connected to the jobs already lost—and dangerous to those that remain.

Those dangers deserve direct resistance—and they make engagement more urgent. Adobe has already built generative video into Premiere Pro. The WGA's 2026 agreement requires companies to notify the Guild before licensing writers' work to train a commercial generative system. These changes are moving on timelines practitioners don't control, whether or not they're in the room.

Much remains unsettled despite that momentum. The technology's purpose and authority inside creative work are still open to influence, though that opening will narrow as products and policies harden. Production professionals who engage now can help determine where AI belongs and where it has no place.

Every department holds knowledge that belongs in these decisions. A VFX artist knows the line between automating repetitive cleanup and replacing an artistic choice. An editor knows the difference between a system that surfaces a better take and one that starts choosing the performance itself. Every craft has its own version of that line, and film and television depend on those boundaries being understood across disciplines.

A television editor recently wrote to me after reading my essay about using AI to improve creative alignment before music is written. She was in the middle of a music pass and recognized the problem I had described: imprecise direction can send practitioners through hours of unnecessary work. At the same moment, she was reading a guild warning about AI taking jobs. She was seeing how AI might clarify creative intentions at the same time she was being warned that it could eliminate the people doing the work.

Across more than twenty-five years composing for television, I have watched production technology continually evolve. One problem has survived every shift: a note can name the wrong problem. Someone might say that a cue feels “too emotional.” The composer may keep making the music less emotional, each revision moving it further from what the scene needs.

Several versions later, everyone may discover that the cue began ten seconds too early. The note identified emotion, though timing created the unwanted effect. Moving the start time allows the actor to reach the moment first and can solve the scene with the original musical idea intact. Experience inside the process makes that distinction easier to see.

Chasing the original note can occupy an entire music team. Every revision moves through the production pipeline before anyone can judge it again. The production generally pays the same fee while those practitioners absorb the communication failure through additional hours, often without additional compensation. A more precise note could preserve that time without removing anyone or surrendering a creative decision.

The conversation that uncovers timing as the real issue is productive friction. It challenges an assumption and leads the group toward a better idea. The unnecessary versions created before that discovery are wasted effort. From outside the workflow, both may look like cumbersome process. Practitioners know which exchanges create understanding and which failures merely consume time.

That pattern recognition is what experienced practitioners bring to AI design. They can distinguish systems built to replace paid creative labor from tools that help people reach and communicate their own decisions. They can also see when a promised efficiency would erase the productive friction that allows good work to emerge.

Bruce Holsinger's novel Culpability gives this idea a more human shape. After questioning the desire for machines that are good for us or good instead of us, one character imagines machines that “help us be better ourselves.” In production, that would mean helping practitioners become clearer and more deliberate while authorship remains theirs.

I have begun applying that principle to production through CueMap, a scene-oriented tool for exploring musical direction before a score is written. It produces a collaborator brief and a prompt for a music-generation platform, then stops before final scoring. Interpretation and creative decisions remain with the people doing the work. Building it has forced me to examine how much authority a tool should have and whether its limits can hold under production pressure.

AI is still emerging, and many more practitioners can influence how it functions in production. Every department and guild brings knowledge that technologists and executives may never encounter.

That knowledge needs to reach the places where tools and rules are being designed while decisions can still change. Practitioners should test where tools fail and establish enforceable limits that protect jobs, consent, and authorship. Their expertise should be compensated and represented collectively wherever possible.

Film and television practitioners have always protected the work by bringing their judgment into the rooms where decisions happen. That judgment lives in the music pass that reveals a cue entered ten seconds too early and in the edit bay where a held reaction changes a scene's meaning. AI is already entering those rooms. Experienced production professionals need to shape its purpose and define its limits.

The rules are being written, and production professionals need to help write them. Now.