A24 and Google DeepMind: How AI Is Reshaping the Film Industry — and Who Stays in Control

July 5, 2026

A director sits alone in a darkened room, surrounded by monitors. On the main screen, a scene takes shape — one he sketched out only minutes ago, in moving images, in the visual language he had imagined. An AI tool read his notes and rendered them into footage. This isn’t science fiction. It’s the everyday reality the film industry is moving toward.

In the summer of 2026, A24 announced a research partnership with Google DeepMind. The industry took notice. The indie label behind Hereditary, Midsommar, and Everything Everywhere All at Once — signing a deal with one of the world’s leading AI research labs. To many, that sounds like a contradiction in terms. A24 built its reputation on championing filmmakers with a strong creative vision. That identity is now at the center of a debate that reaches far beyond Hollywood.

The partnership is designed to develop AI tools that reshape the entire production workflow — from development through post-production. This isn’t a niche conversation for tech enthusiasts. It’s a test case. One that reveals where the film industry is heading, and who pays what price along the way.

A note on perspective: The analysis below draws on publicly available statements from A24 and Google DeepMind, as well as industry observations from production professionals and artists’ organizations. This piece examines both the opportunities and the risks with a critical eye — without either condemning or celebrating the partnership outright.

What the Partnership Actually Involves

Google DeepMind published an official announcement (Google The Keyword) outlining a collaboration to build AI tools specifically designed for creative film production — tools tailored to the sensibility of an arthouse studio.

That’s a meaningfully different approach from what we’ve seen so far. Studios like Warner Bros. and Disney have primarily deployed AI in post-production: VFX optimization, dubbing, trailer assembly. A24 and DeepMind are targeting an earlier stage in the process — story development, idea visualization, and potentially storyboarding and previsualization.

For production teams, this means AI as an integrated toolkit from the very start of the creative process, not a finishing tool bolted on at the end. Anyone already working with text-to-video platforms will recognize the logic. The question is no longer whether AI enters the workflow, but how deep that integration goes.

Opportunities for Production and Development

The potential here is real. Three areas stand out:

Previsualization and pitching: AI can render scenes before a camera is ever set up, compressing development cycles and giving directors a way to make their vision tangible — and presentable to investors.
Faster story development: Tone, structure, and visual language can be tested far more quickly. What once took months can now be evaluated in weeks.
More targeted use of resources: AI tools can handle routine tasks — color grading, editing assistance, sound design drafts — freeing up creative budgets for the decisions where human judgment genuinely makes the difference.

These aren’t abstract promises. There’s already evidence of this shift in recent productions. The marketing campaign for The People’s Joker used AI-generated imagery. Late Night with the Devil incorporated AI-generated visuals. Major brands — Nike, Coca-Cola, BMW — are using text-to-video shots in advertising, demonstrating how generative AI is already changing visual language, production design, and post-production.

What sets the A24–DeepMind partnership apart is its scale. This isn’t one department experimenting with new tools. It’s an entire studio rethinking how it works, from the ground up.

For smaller production companies, that’s a signal worth taking seriously. If A24 commits to this path, the pressure on everyone else to develop comparable workflows — or at least evaluate them seriously — will only grow.

The Identity Question: What Happens to the “A24 Feel”?

This is where things get complicated. A24 built its brand on something harder to quantify than a logo or a genre: the ability to identify and support filmmakers with a distinctive authorial voice. That’s the studio’s real capital.

The question many creatives are now asking is whether that ethos is compatible with AI-first workflows — or whether the tools will, over time, quietly reshape the output.

This isn’t an argument against AI. It’s a question about balance — about maintaining the equilibrium between innovation and ethical responsibility toward the filmmakers who made A24 what it is. When development tools are optimized on training data, what kinds of stories are deemed to “work”? By what criteria? Based on past A24 successes? Streaming performance? Festival awards?

Google DeepMind has stated that the partnership brings DeepMind researchers to work “side by side” with A24 filmmakers, so that future AI tools are shaped by the creators themselves and designed to support authentic storytelling. (Google)

The risk isn’t in any single tool. It lies in accumulation — AI-assisted decisions compounding over years, a studio drifting imperceptibly from its original strengths while believing it’s simply becoming more efficient. That’s not a certainty, but it’s not a remote possibility either.

Copyright and Data Provenance: The Unresolved Questions

Alongside the identity question, the legal dimension is pressing. Every AI model built for creative film production requires training data. Which data DeepMind is using is anything but a minor detail.

Specifically: Were existing screenplays, production stills, soundtracks, or editing patterns used without licensing? Who holds rights to outputs generated by such models? How does that interact with the contracts that writers, directors, and composers have signed with A24?

The WGA and SAG-AFTRA strikes of 2023 brought these questions into public view. The 2023 WGA agreement prohibits AI from writing or rewriting literary material and reserves the right to bar the use of writers’ work for AI training. The 2023 SAG-AFTRA agreement requires informed consent and separate paid contracts for digital replicas. But these clauses were written for a different context — AI used within existing productions, not studios developing proprietary models from scratch.

Similar questions arise around voice cloning and stylistic fingerprinting. If an AI model learns to visualize “in the style of A24,” whose work forms the basis of that stylistic understanding? This is not an academic debate. It’s a question that courts will be working through for years to come.

The transparent path forward would be a clearly communicated data provenance standard: which sources were licensed, which rights holders were compensated, and how outputs will be classified legally. Until those questions are answered, the partnership rests on uncertain ground — legally and ethically.

What Other Studios Are Watching

The A24–DeepMind partnership is a key moment in determining which model of AI integration gains traction across the industry.

Studios face a fundamental choice: they can invest in proprietary, closed systems — models developed and controlled internally, with clear safeguards for production confidentiality and creative integrity. Or they can build on more open infrastructure and bring creatives more directly into the tool development process. That trade-off is one every major studio is currently weighing.

The implications extend across the industry. If this partnership delivers on its promise, others will follow. If it falters — because creative quality and AI optimization turn out to be in genuine tension — it will serve as a cautionary example.

For filmmakers outside the major studios, this matters in a specific way. The tools that emerge from partnerships like this one won’t necessarily be available to everyone. Proprietary systems create competitive advantages, but they also create new dependencies.

A Test Case Still in Progress

The A24–DeepMind partnership opens up real possibilities: faster development cycles, stronger previsualization, more efficient use of resources. These are genuine advantages that can meaningfully support creative work.

At the same time, the open questions are too significant to set aside. Whose data feeds the models? How are creative identities protected? What rights do filmmakers hold over outputs generated by AI tools trained on their work?

The answers won’t only shape A24. They will set the terms for AI-first workflows across the film industry. Anyone following this development — as a producer, screenwriter, director, or creative strategist — would do well to pay close attention. How these questions get resolved will determine who has a voice in the new architecture of filmmaking, and who doesn’t.