Investors and analysts spend considerable time modeling content economics. They track production budgets, streaming subscriber counts, advertising revenue, and IP valuations. What they are spending less time on is the cost curve that AI is running through all of those numbers. John Chachas is paying attention.
The veteran media banker and CEO of Inyo Broadcast Holdings, who has spent his career structuring transactions in American broadcasting and entertainment, writes in the Los Angeles Wire about what happens when the marginal cost of producing a watchable television program approaches something close to zero. The reference point is not theoretical. Non-Player Combat, a four-part AI-generated reality show that premiered on YouTube last December, was produced for approximately $28,000 in under two months. Its creators claim that represents a 90 percent cost reduction against comparable human-made production.
OpenAI’s Sora 2, released in late September 2025, demonstrated the ability to generate full sequences with synchronized audio and dialogue that film industry executives characterized as qualitatively different from previous generations of AI video. Hollywood Reporter testing with Sora beta users found that entire opening sequences for feature films could be generated in an afternoon by a single person at a workstation.
Chachas watches this from the perspective of someone who knows what content used to cost. A script required a writers’ room. An establishing shot required a crew. A speaking role required a SAG-AFTRA performer and a contract. Background actors required day rates. Each of those costs represented income for someone. The aggregate of those costs, across a production, determined what a streaming platform or broadcast network had to charge to cover its costs.
When AI can generate an establishing shot as a render, when background performance can be replaced with a licensed digital replica at compute cost, when dialogue can be synthesized without a voice actor, the cost structure changes. Not incrementally. Fundamentally. “If AI creates this stuff at almost pennies compared to typical production, what happens to the compensation of writers, videographers, showrunners, and, of course, talent?” Chachas asks. “Their value will be under enormous pressure.”
On the broader question of AI governance, he is equally direct. “AI presents opportunity and enormous risk,” he says. “And I do not think anybody in government is really paying attention.” He returns to the WarGames comparison: a networked defense computer that nearly launches nuclear strikes before being talked down. The scenario, a machine that exceeds its operators’ ability to constrain it, does not register to him as fiction.
The collapse of traditional content production economics is not a forecast. It is a process Chachas is already watching happen on his own YouTube feed. The question for Hollywood is not whether this displacement will occur. It is how quickly it scales, which parts of the value chain get compressed first, and whether human-authored content can differentiate itself once the synthetic baseline becomes abundant.