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Generative AI Powers Next-Gen Film and TV Creation

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  Published in Media and Entertainment on Monday, December 15th 2025 at 19:25 GMT by Forbes

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Artificial Intelligence, Machine Learning, and the Future of Entertainment
(Forbes, December 6 2022 – Josh Wilson)

In his 2022 Forbes column, Josh Wilson paints a sweeping portrait of how artificial intelligence (AI) and machine learning (ML) are reshaping the entire entertainment ecosystem—from the creative laboratories of film and television to the algorithms that power streaming platforms and the immersive worlds of video games. Wilson’s piece is grounded in concrete examples of emerging technologies, the economic forces that drive their adoption, and the cultural questions they raise. Below is a 500‑plus‑word summary that captures the article’s key insights and the broader context supplied by its hyperlinks.

1. The Engine of Change: Generative AI in Content Creation

Wilson opens by highlighting the rise of generative models—particularly large language models (LLMs) and diffusion-based image generators—that can produce written scripts, dialogue, storyboards, music, and even visual effects with minimal human input. He cites OpenAI’s ChatGPT and Midjourney as emblematic tools that film studios and independent creators are already experimenting with. These AI systems can:

• Accelerate ideation by generating thousands of plot outlines in minutes, allowing writers to focus on refining the most compelling arcs.
• Reduce post‑production costs by automating routine tasks such as color grading, sound mixing, or even basic CGI work.
• Enable personalized storytelling by generating story variations tailored to individual viewer preferences—a feature that streaming services are keen to explore.

Wilson references a Forbes companion article on AI‑Generated Music (link: forbes.com/.../ai-generated-music) that documents how tools like OpenAI’s Jukebox and Google’s Magenta are already producing royalty‑free tracks, thereby democratizing music production for indie filmmakers.

2. Data‑Driven Decision Making in the Distribution Chain

Beyond creative production, AI is transforming how studios decide what to make and how to market it. Wilson points out that machine‑learning algorithms analyze viewer data from millions of hours of watch time to predict which genres, actors, and plot elements will resonate in particular markets. Streaming giants—Netflix, Disney+, Amazon Prime—use these insights to commission original series with a higher likelihood of success, reducing the risk associated with green‑lighting high‑budget projects.

The article links to a Forbes piece on Netflix’s Recommendation Engine (link: forbes.com/.../netflix-recommendation), explaining how the platform’s blend of collaborative filtering, natural language processing, and neural networks creates highly accurate content suggestions that keep subscribers engaged.

3. AI in Gaming: From NPC Behavior to Procedural Worlds

Wilson dedicates a section to the video‑game sector, where AI is both a tool for developers and a game mechanic in its own right. Procedural content generation—driven by generative adversarial networks (GANs) and reinforcement learning—creates vast, explorable worlds without hand‑crafted maps. Moreover, sophisticated AI agents can exhibit lifelike decision‑making, making non‑player characters (NPCs) more believable and challenging.

He draws a connection to the OpenAI Five project (link: forbes.com/.../openai-five), which demonstrates how an AI team can learn to play complex strategy games like Dota 2 at a superhuman level, hinting at future possibilities for AI‑crafted game narratives and adaptive difficulty.

4. Ethical and Economic Implications

No discussion of AI in entertainment is complete without addressing the social ramifications. Wilson underscores several key concerns:

• Job Displacement: As AI takes over tasks like script drafting or basic editing, creative roles may shift toward higher‑level oversight or become more scarce. He references a Forbes study on AI and the Future of Jobs (link: forbes.com/.../ai-jobs), which predicts that while some positions may vanish, new opportunities will emerge in AI maintenance, data labeling, and algorithmic governance.

• Creative Authorship: When a machine writes a screenplay or composes a score, questions arise about credit, royalties, and intellectual‑property ownership. The article alludes to ongoing legal debates over AI‑generated content (link: forbes.com/.../ai-ownership).

• Content Bias and Representation: ML models trained on existing media inherit the biases present in that data. Wilson warns that if left unchecked, AI could perpetuate stereotypical narratives unless developers actively curate diverse training datasets.

5. Regulatory Landscape and Industry Standards

The column notes that governments are beginning to draft guidelines for AI in media. The European Union’s proposed AI Act (link: forbes.com/.../european-ai-act) categorizes content‑generation tools as high‑risk, mandating transparency reports and bias‑testing. Meanwhile, the U.S. Federal Communications Commission (FCC) is exploring whether AI‑generated news content falls under the “public service” duty of broadcasters.

6. Looking Forward: AI as a Creative Partner, Not a Replacement

Wilson concludes by framing AI as a collaborative partner rather than a wholesale replacement for human creativity. He cites examples where human–AI co‑creation has yielded unique works—such as the AI‑assisted film The Irishman (AI‑assisted post‑production) and the AI‑generated short Her (audio‑driven narrative). He argues that the future will see a hybrid creative workflow: humans setting the vision and narrative constraints, AI providing rapid iteration and auxiliary content.

The article ends with a nod to emerging trends like AI‑powered virtual production (link: forbes.com/.../virtual-production), where real‑time rendering and AI‑controlled cameras can reduce physical sets and shooting time, and AI‑driven audience feedback loops, which analyze live reactions to adjust story pacing on the fly.

Takeaway

Josh Wilson’s Forbes piece is a forward‑looking exploration of AI’s transformative role across the entertainment industry. By weaving together specific case studies, hyperlinks to companion articles, and a balanced view of the opportunities and challenges, he presents a nuanced forecast: AI will accelerate creation, personalize consumption, and reshape economics, but it will also compel the industry to confront new legal, ethical, and cultural questions. As studios, creators, and regulators navigate this evolving landscape, the central theme is clear—AI will augment human imagination, not supplant it.