Artificial intelligence has become one of the most polarizing forces in modern filmmaking. Public conversations often frame AI as either a miracle tool that will democratize creativity or a looming threat that will erase artistic labor entirely. But inside the industry, the reality is far more complex.

Through interviews with writer Alex Meenehan, editor Jeff McEvoy, and filmmaker, author, and former SAG board member Justine Bateman, a clearer picture emerges: AI is not replacing creativity overnight, but it is altering workflows, labor pipelines, and the ethical foundations of entertainment. The danger is not that machines will suddenly make better art than humans, but that economic incentives will quietly reshape the industry in ways that devalue human experience.

What People Really Mean When They Say “AI”

One of the first problems, all three interviewees agreed, is that “AI” has become a catch-all term. McEvoy, who works daily in post-production, emphasized that many people conflate AI with computer-generated imagery.

“CGI has been around forever,” McEvoy explained. “AI is something else entirely. People don’t always understand that difference.”

Bateman went further, calling artificial intelligence primarily a marketing term. “We’ve been using machine learning tools for decades,” she said, citing examples like GPS systems, Photoshop masking, and chess engines. “Now companies slap the AI label on everything because they want to look like they’re on the cutting edge.”

This confusion allows studios and tech companies to obscure what kinds of tools are being used and why. As Meenehan noted, not all AI tools are inherently harmful. “Some of it is just automation,” she said. “That’s not the same as replacing creativity.”

Generative AI and the Illusion of Creation

The most contentious form of AI is generative AI, which produces text, images, audio, or video based on massive datasets. Tools like ChatGPT, MidJourney, and Sora create the impression of originality, but all three interviewees stressed that this originality is illusory.

Bateman described generative AI as “a blender.” “It can’t create anything on its own,” she said. “If the blender is empty, nothing comes out. But if you fill it with 100 years of films, books, and essays, it gives you a Frankenstein mix of what’s already there.”

Meenehan echoed this assessment from a writer’s perspective. “I’ve tried to get it to do what I do professionally,” she said. “It can write things that look like writing, but there’s no soul. If I turned it in, I’d get fired.”

This lack of humanity is not accidental. Generative models do not understand emotion, intention, or meaning. They recognize patterns and replicate them. According to Meenehan, that makes AI particularly good at producing work that feels familiar. “It’s all trope,” she said. “Sometimes that’s useful as a reference, but it’s not art.”

Plagiarism, Training Data, and Ethical Fault Lines

One of Bateman’s strongest critiques of generative AI centers on how these systems are trained. She argued that most models were built using copyrighted material without permission.

“They’ve ingested everything,” Bateman said. “Books, films, essays, social media posts, videos—none of that was free.”

She rejected the argument that publicly available content is fair game. “If my car is parked on the street, that doesn’t mean you can take it,” she said.

Meenehan acknowledged that AI can sometimes produce compelling ideas, but raised concerns about their origins. “The good ideas might already belong to someone,” she said. “It could be pulling from web novels or scripts written by people who never consented to that use.”

This blurring of inspiration and theft creates legal and ethical uncertainty. While lawsuits from authors and journalists are beginning to challenge AI training practices, Bateman believes much of the damage has already been done. “I’d love to see licensing fees,” she said, “but that ship may have sailed.”

Disappearing Pipeline

Beyond ethics, AI poses a structural threat to the film industry. Bateman warned that eliminating early-career roles could cause the entire system to collapse.

“In any industry, if you remove too many jobs from the pipeline, there’s nothing holding it up,” she said.

McEvoy has witnessed this erosion firsthand. “Negative cutters are gone. Telecine operators are gone. Film colorists are gone,” he said. Tasks that once required teams of specialists are now handled by software.

Meenehan pointed out that writing rooms face similar pressures. Research, outlining, and continuity tracking—often handled by assistants or junior writers—are increasingly automated. “That’s how people learned,” she said. “If those jobs disappear, so does the next generation of writers.”

The concern is not just job loss, but skill loss. Without apprenticeships, future filmmakers may lack the lived experience that once shaped storytelling.

Writers Aren’t Being Replaced—Yet

Despite fears, Meenehan does not believe AI can fully replace writers. During the 2023 writers’ strike, one of the most important protections secured was the definition of a writer as a human being.

“Studios can’t credit AI as a writer,” she explained. “That means they can’t use AI to write a first draft and then pay us less to fix it.”

This distinction matters because first drafts often account for the majority of a writer’s compensation. Without that protection, studios could have drastically reduced costs by outsourcing early drafts to AI.

However, Meenehan acknowledged that AI may influence what gets written. “High-concept ideas sell,” she said. “I could see studios using AI to generate loglines and then hiring writers to develop them.”

Editors, Efficiency, and the Limits of Automation

In post-production, AI’s influence is more visible but no less controversial. McEvoy described AI as a powerful assistant that still requires human oversight.

“AI can land a plane,” he said, “but you still need a pilot.”

Editing is not just about assembling footage; it’s about rhythm, emotion, and instinct. While AI can analyze scenes and suggest cuts, it cannot understand subtext or intention.

McEvoy also emphasized that faster workflows do not necessarily produce better films. “Just because you can do something faster doesn’t mean you should,” he said.

Unions, Contracts, and Guardrails

All three interviewees agreed that unions play a crucial role in regulating AI. Bateman praised the Writers Guild of America and Directors Guild of America for clearly defining creative roles as human.

She was far more critical of SAG’s approach. “They allowed studios to use AI performers,” she said. “That creates non-union labor. It undermines the purpose of a union.”

According to Bateman, contracts exist precisely for moments when ethics fail. “Agreements aren’t for when everyone’s being reasonable,” she said. “They’re for when one or both parties lose their minds.”

Meenehan added that regulation must evolve alongside technology. “AI is still amorphous,” she said. “We don’t fully know what it’s going to become.”

Audience Perception and Cultural Memory

Do audiences care whether AI is used? Bateman believes many people already consume AI-generated content without realizing it.

“They think it’s CGI,” she said. “They don’t know.”

However, she warned that prolonged exposure to hyper-polished, emotionally empty content could lower standards. “We’ve forgotten what real films look like,” she said. “A normal face now looks ‘wrong’ to people.”

Meenehan sees a potential backlash brewing. “People respond to originality,” she said. “That hasn’t changed.”

Lessons for Emerging Creatives

For young filmmakers and writers, Bateman’s advice is blunt: do what AI cannot.

“If you can’t do what AI does cheaper and faster, why would anyone hire you?” she asked.

She criticized schools that allow AI-generated work. “If you get a degree using ChatGPT, the job you qualify for can be done by ChatGPT,” she said.

Meenehan agreed, encouraging writers to embrace experimentation. “AI can’t write something new,” she said. “That’s your advantage.”

AI, Risk Aversion, and the Homogenization of Storytelling

One of the less obvious but more consequential impacts of AI on filmmaking is how it may influence creative risk-taking. While none of the interviewees believed AI is capable of meaningful artistic innovation, all three expressed concern that executives may rely on it to justify safer, more predictable decisions.

Meenehan noted that the industry is already operating from a place of fear. “A lot of what’s selling right now is driven by marketing rather than storytelling,” she said. In that environment, AI-generated analytics could reinforce trends instead of challenging them. If algorithms are trained on past successes, they may discourage originality in favor of repetition.

Bateman drew a parallel to the superhero era, arguing that over-reliance on data eventually hollowed out the genre. “It’s what happens when numbers choose what gets greenlit,” she said. “Everything gets duller.”

McEvoy agreed, adding that filmmaking has always relied on instinct. “Some of the best decisions aren’t logical,” he said. “They’re emotional.” AI, by contrast, is incapable of intuition. It cannot sense when a moment should linger, when silence is more powerful than dialogue, or when an unconventional choice might resonate with audiences.

The risk, according to Bateman, is not that AI will make films directly, but that it will be used as an authority. “If a studio runs their slate through AI and asks which films to make, that’s a problem,” she said. “Because art isn’t supposed to be optimized.”

The Illusion of Productivity

Another recurring theme across all interviews was the idea that AI can feel productive without actually producing better work. Meenehan described AI tools as “seductive,” particularly because they respond instantly and confidently.

“You can spend hours thinking you’re working,” she said, “and you’re not.”

This illusion is especially dangerous in creative fields, where progress is often slow, nonlinear, and uncomfortable. Writing, editing, and directing all require periods of uncertainty. AI removes that discomfort by offering immediate answers, even when those answers are wrong or shallow.

Bateman argued that this avoidance of struggle is part of AI’s broader appeal. “A lot of people want a life without friction,” she said. “This is being sold as a way to remove challenge.”

McEvoy warned that this mindset could lead to worse films, not better ones. “Struggle is part of the process,” he said. “That’s where good ideas come from.”

Historical Parallels and False Panics

All three interviewees acknowledged that fear surrounding AI echoes earlier technological shifts. Film editing once transitioned from physical reels to digital timelines. CGI replaced practical effects in many productions. Each innovation sparked anxiety about job loss and artistic decline.

McEvoy pointed out that many of those fears were partially justified. “Some jobs never came back,” he said. “But new ones appeared.”

However, Bateman cautioned against assuming AI follows the same pattern. Unlike previous tools, generative AI does not simply change how work is done. It challenges who is doing the work and whether compensation is required at all.

“This isn’t like switching from film to digital,” she said. “This is about replacing human labor with something that was built from human labor without consent.”

Meenehan added that the scale of AI adoption also sets it apart. “It’s not incremental,” she said. “It’s everywhere, all at once.”

Education, Authorship, and Skill Erosion

The conversation around AI inevitably extends into education. Meenehan and Bateman both expressed concern that allowing AI-generated work in schools undermines learning.

“If students use AI to write essays,” Bateman said, “they’re training themselves out of a job.”

She argued that the purpose of education is not efficiency, but skill development. Writing poorly, revising drafts, and making mistakes are essential parts of learning. AI bypasses those steps.

McEvoy added that technical mastery still matters. “You can’t skip fundamentals,” he said. “AI doesn’t understand story structure. You do.”

The long-term concern is that a generation raised on AI assistance may lack the depth needed to push the medium forward.

Why AI Still Can’t Replace Film

Despite these concerns, all three interviewees ultimately expressed confidence in one thing: AI cannot replace genuine filmmaking.

Bateman cited experimental works like House of Leaves and films produced by studios such as A24 as examples of art that AI could never generate. “It’s too weird,” she said. “Too human.”

Meenehan emphasized that the stories audiences remember are the ones that feel specific. “AI can generalize,” she said. “It can’t personalize.”

McEvoy agreed, noting that audiences may not consciously identify AI’s influence, but they can feel when something is missing. “They know when something doesn’t land,” he said.

Conclusion: Choosing Humanity

Artificial intelligence is not an unstoppable creative force, but it is a powerful economic one. Left unchecked, it could reshape the film industry in ways that favor speed, sameness, and short-term profit over originality and craft.

The interviews with Jeff McEvoy, Alex Meenehan, and Justine Bateman reveal a shared belief that technology itself is not the enemy. The real threat lies in how it is used, who controls it, and whose labor it replaces.

At its core, filmmaking has always been about interpretation. Two editors will cut the same scene differently. Two writers will tell the same story in entirely different ways. That unpredictability is not a flaw, but the foundation of art.

As Bateman put it, “What makes us human is mistakes.”

In an industry increasingly tempted by automation, the survival of meaningful storytelling may depend on whether creators, executives, and audiences alike choose to value imperfection, risk, and lived experience over convenience.

For now, that choice remains in human hands.

IMDb Links