The Strategic Shift: AI as Foundational Infrastructure

The primary strategic evolution in 2025 is the understanding that AI should not be viewed as a mere departmental tool but as a foundational infrastructure layer for the entire content supply chain, a point underscored at IBC 2025.

This foundational role is driven by the industry’s need to meet the insatiable demand for content at a profit margin.

The Adobe 2025 AI and Digital Trends report notes that more than three-quarters (78%) of senior marketing executives face mounting demands to scale content output while keeping it personalized and relevant.

AI is the only technology capable of bridging this efficiency gap. Instead of augmenting the work of a single artist, AI is now architected to automate the entire creative journey, from the first rough cut to the final, multi-language delivery, directly impacting time-to-market and distribution licensing viability.

This systematic approach is fundamentally How AI is Changing Post-Production (A 2025 Report), transforming it from a creative bottleneck into a cost-efficient engine.

AI in the Post-Production Pipeline: Three Critical Impact Zones

The content supply chain is seeing its most profound transformation in three historically labor-intensive areas: VFX/Animation, editorial workflows, and localization/audio.

1. Generative AI in Visual Effects & Animation (VFX)

The most immediate and aggressive cost-reduction opportunity is in VFX and animation. Morgan Stanley Research projects that Generative AI could cut costs in television and film by as much as 30% when fully integrated into post-production workflows.

Industry veteran Jeffrey Katzenberg goes further, predicting a 90% reduction in both labor and schedule for high-end animation once AI pipelines mature.

Key areas of automation include:

• Rotoscoping and Tracking: Automated AI rotoscoping—the labor-intensive process of isolating characters frame-by-frame—is seeing significant efficiency gains. Consulting firm Roland Berger’s analysis shows time savings ranging from 20% to as much as 65% for complex sci-fi and fantasy genres.
• Simulation and Asset Generation: Machine Learning models can automatically track objects, digitally isolate characters from complex backgrounds, and generate realistic simulations of smoke, fire, and water in real-time, which used to require extensive human artist hours.
• 3D Modeling and Rendering: AI can autonomously apply realistic textures and suggest design changes for 3D models. AI-based render engines, like those using NVIDIA DLSS, accelerate the rendering stage with professional quality, allowing artists to spend time creating rather than waiting, according to Arena Animation.

2. Automation in Editing & Editorial Workflow

The traditional Non-Linear Editing (NLE) timeline is rapidly being replaced by AI-assisted tools focused on speed and creative iteration.

• Script-Driven Editing: Platforms like Descript allow editors to manipulate video clips by simply editing the automatically generated transcript, drastically accelerating the workflow for dialogue-heavy content.
• Generative Filling and Extending: Tools like Adobe Premiere Pro’s Generative Extend and Runway enable intelligent manipulation of scenes, such as extending video clips to smooth transitions or even changing weather, camera angles, or props with a text prompt.
• Drafting and Concept Visualization: For rapid prototyping, new tools can generate eight-second cinematic video clips from a simple text prompt, providing directors and editors an alternate reality of shots they didn’t film, according to a guide on video editing tips for 2025.

3. The New Frontier: Localization, Sound, and Color Correction

As streaming platforms prioritize global audience reach, the cost and time of localization are a crucial variable in the content supply chain.

• AI-Powered Localization: AI is now making content truly universal. Adobe and YouTube have announced partnerships that use AI tools to automatically dub videos in multiple languages and synchronize lip movements perfectly, reducing language barriers for global distribution and licensing.
• Sound Design and Restoration: AI-powered audio tools like iZotope RX offer features such as Dialogue Isolate and Repair Assistant, while Adobe Audition offers Enhance Speech, automatically balancing volume levels and boosting tone and clarity, according to Resemble AI.
• Automated Color Correction: AI tools are streamlining the traditionally slow color grading process. DaVinci Resolve Studio and systems like Colourlab AI offer smart suggestions and automatic grading capabilities, ensuring consistent and cinematic quality without hours of manual adjustments.

Strategic Imperatives for M&E Executives

The integration of AI into post-production requires a shift in executive strategy, moving away from simple software procurement to defining a new operational framework. The core challenge is realizing the full potential of AI without generating new compliance and legal risks.

1. Re-Architecting the Content Supply Chain

Executives must treat their entire post-production pipeline—from the ingest of dailies to the final deliverables—as a single, interconnected system, not a series of siloed steps.

A focused approach on Computer Vision use cases, such as auto-rotoscoping and object detection, offers high value at relatively low implementation cost, making it a strategic entry point, notes Roland Berger.

Organizations must invest in modernizing data and asset management systems to ensure the proprietary data needed to train bespoke AI models is clean, tagged, and ready for machine learning.

2. Prioritizing Compliance and Data Licensing

The most significant risk is the use of non-compliant data. As Forbes points out, organizations must confirm that their training datasets carry explicit usage rights to prevent open-ended liabilities regarding intellectual property (IP) ownership. This mandates new internal compliance frameworks that address:

• IP Auditing: Establishing a clear process for auditing and vetting the training data used by AI service providers and internal tools.
• Labor Covenants: Integrating contractual language—stemming from the 2023 WGA and SAG-AFTRA strikes—that specifies residuals and limits the studio’s use of generative tools to augment, not replace, creative labor.
• Risk Mitigation: Allocating budget toward legal and compliance counsel to avoid production stoppages caused by AI disputes.

Conclusion

The shift in post-production in 2025 is not just technological; it is strategic.

AI has moved from a feature to a foundation, offering unprecedented cost savings, accelerated timelines, and expanded global reach through seamless localization.

The successful M&E executive will be the one who moves beyond experimental tool adoption and implements AI as a core, governed infrastructure layer, focusing investments on integrated, compliant solutions that directly streamline the content supply chain and improve profitability.