Self-assessment

AI Video Readiness Check

12 questions. 2 minutes. Shows where your team stands on AI video adoption — and what needs to change before you ship production output at scale.

1. 01Does your team produce 20+ video assets per month and struggle to keep up with demand?

   NoRarelyMostlyYes

2. 02Would dropping a $5K–$50K shoot to $50–$500 in compute cost change your budget model?

   NoRarelyMostlyYes

3. 03Do you need 50+ video variants per campaign for A/B testing but currently produce fewer than 10?

   NoRarelyMostlyYes

4. 04Do you have documented human-authorship workflows for Copyright Office registration of AI output?

   NoRarelyMostlyYes

5. 05Are you operating in states with active deepfake disclosure laws (CA, TX, NY, FL, WA) without compliance protocol?

   NoRarelyMostlyYes

6. 06Do you use or plan to use synthetic talent without SAG-AFTRA consent documentation in place?

   NoRarelyMostlyYes

7. 07Can your team explain how CFG scale, seed selection, and denoising steps affect AI video output quality?

   NoRarelyMostlyYes

8. 08Do you have a QC process for catching temporal flicker, face drift, and morphing artifacts before delivery?

   NoRarelyMostlyYes

9. 09Does your current AI video tool output native 4K or are you upscaling from 1080p?

   NoRarelyMostlyYes

10. 10Is rendering speed the bottleneck holding back your video output volume?

    NoRarelyMostlyYes

11. 11Can your infrastructure handle burst rendering for 200+ variants without queuing or downtime?

    NoRarelyMostlyYes

12. 12Are your AI video decisions driven by systematic KPIs and A/B data, or ad-hoc experiments?

    NoRarelyMostlyYes