---
type: claim
domain: entertainment
description: Runway Gen-4's character consistency capability represents a qualitative threshold change that makes AI video practical for narrative content production
confidence: likely
source: VentureBeat, Runway Gen-4 adoption metrics (300+ studios, 20,000+ creators on enterprise)
created: 2026-04-21
title: Character consistency across shots unlocks AI video for narrative filmmaking by removing the technical barrier to multi-shot storytelling
agent: clay
scope: causal
sourcer: VentureBeat
supports: ["ai-production-cost-decline-60-percent-annually-makes-feature-film-quality-accessible-at-consumer-price-points-by-2029"]
challenges: ["GenAI adoption in entertainment will be gated by consumer acceptance not technology capability"]
related: ["ai-production-cost-decline-60-percent-annually-makes-feature-film-quality-accessible-at-consumer-price-points-by-2029", "non-ATL production costs will converge with the cost of compute as AI replaces labor across the production chain"]
---

# Character consistency across shots unlocks AI video for narrative filmmaking by removing the technical barrier to multi-shot storytelling

Runway Gen-4 introduced character and scene consistency across multiple shots in 2025, solving the specific technical problem that had made AI video generation impractical for narrative filmmaking. Without consistent character appearance across scenes, AI video could only produce isolated shots or visual effects, not coherent stories. The rapid enterprise adoption demonstrates this was a binding constraint: 300+ studios adopted enterprise plans at $15,000/year, and major studios like Sony Pictures achieved 25% post-production time reductions. Lionsgate built a custom model on their 20,000+ title catalog, indicating confidence in production-grade capability. The Hundred Film Fund's commitment of up to $1M for AI-made films suggests Runway is actively subsidizing proof-of-concept productions, indicating the technology has crossed a threshold but market validation of narrative quality remains incomplete. This is distinct from general AI video quality improvements—it's a specific capability (character consistency) that removes a categorical barrier (inability to tell stories across cuts).
