AI can do a lot in video, but it shouldn’t replace your team’s taste or your brand’s voice. The sweet spot is simple: let AI handle the repeatable, rule-based tasks, and keep people in charge of the creative calls and sensitive decisions.
Think of AI as your production assistant. It can:
That frees your team to focus on story, performance, and client relationships, the things that actually move the needle.
In this guide, you’ll get:
By the end, you’ll know where AI saves hours (and headaches) and where human judgment still matters most. If you’d prefer a done-for-you setup, see the TL;DR for a quick way to get started with Ajax Creative.
AI can save hours in the edit bay. It shouldn’t make your creative calls.
Use it where the steps repeat. Keep people on story, tone, and sensitive decisions.
Marketers know video works. They create more content across more channels on tighter timelines.
Demand is up. Deadlines are tighter. Editors are stretched.
So where does AI actually help? Mechanical steps with clear rules. Captioning interviews. Pulling a rough cut from a transcript. Resizing one edit for many platforms. You press “go,” and the machine lifts the heavy stuff while your team shapes the moments people remember.
There’s a business angle, too. Companies that win with AI start small and measurable.
Skip flashy stunts. Focus on workflows that save time and reduce errors. The 2025 AI picture is clear: narrow, repeatable use cases deliver value; big, showy experiments do not.
Now the reality check. Even the strongest models struggle with control, continuity, and nuance. That matters when your brand voice and context are on the line.
Treat generative video as an assistant, not an editor; the text-to-video capabilities and constraints make that clear.
That’s why every team needs two constants:
On the tools side, editors are getting help where it counts. They can find the right clip faster, without rummaging through endless bins. Assistants are moving directly inside the software.
One example is media-intelligence search in Premiere Pro, which makes retrieval faster and shaping easier.
So yes, AI matters this year. Not because it replaces taste, but because it clears the busywork and speeds the handoffs. Your team can stay with the moments that sell the story: performance, pacing, and that “this feels right” judgment only humans bring.
Let AI do the busywork. People keep the final say.
Speed first
Fewer handoffs
Cleaner first cuts
Turning dialogue into text inside your edit is now a standard step. The machine drafts it, and you fix brand terms or tricky names. It speeds review and doubles as captions when you publish. Try speech-to-text transcription in Premiere Pro.
When the story is interview-driven, you don’t need to scrub endlessly. Highlight the sentences you want, lift the filler, and you’ve got a working draft in minutes. Text-based editing in Premiere Pro makes it possible to assemble a cut straight from the transcript.
Every production repeats the same setup: folders, bins, starter timelines. Automating that build keeps projects consistent, especially when teams are large or deadlines are tight.
Boring but powerful.
Long-form footage can be overwhelming. One file, hours of content. Let AI detect the edit points, drop markers, and give you a head start.
Scene edit detection in Premiere Pro does it in seconds, so editors spend less time hunting and more time shaping.
Less hunting
More cutting
Want concepts and boards that sell the idea before a single shot is taken? Our creative development team helps you visualize the story early, saving time and costly revisions later.
Every platform asks for a different frame. Horizontal for YouTube, vertical for TikTok, square for Instagram. Instead of re-editing each version, let AI reframe automatically. Auto Reframe in Premiere Pro keeps the subject centered and gives you instant 16:9, 9:16, and 1:1 versions of the same cut.
Shoots move fast. It’s easy to forget if cards have been backed up, if a battery is near empty, or if a scene was missed. Simple rule-based reminders send alerts for shot list completion, media offloads, or gear checks.
Those are small nudges that prevent costly reshoots.
Organizing on set saves headaches later. Mark each take with its scene number, shot ID, and talent name while filming. Editors will thank you when clips are searchable instead of being buried in endless folders.
Less confusion
Fewer misses
Cleaner handoffs
When the shoot is complex (multiple cameras, bigger crews, fast turnarounds), human direction matters even more. Explore our production services to see how we handle complex shoots with clarity and control.
As covered in speech-to-text transcription in Premiere Pro, AI can generate a baseline transcript and captions in minutes. A human pass is still needed for names, brand terms, and tone, but it takes a fraction of the time compared to starting from scratch.
Background noise or muffled dialogue doesn’t always mean a re-record. Enhance Speech in Premiere Pro lifts clarity from rough audio, giving editors a stronger base before handing it to a sound mixer.
Editors don’t need to grade every shot manually at the start. Auto Color in Premiere Pro applies a consistent base look, so the colorist can focus on creative choices later.
Time-savers across the suite. From faster subtitles to multicam editing improvements, DaVinci Resolve 20 updates give editors new tools that reduce repetitive setup work and keep post moving.
Technical checks that once ate hours can now run in the background:
Keep audio within range using EBU R128 loudness standards or ITU BS.1770 recommendations.
Flag mistakes like blank frames or dead audio with blackdetect and silencedetect filters in FFmpeg.
Ensure delivery matches platform requirements with YouTube encoding settings for upload.
Fewer technical misses.
Cleaner client handoffs.
When projects demand polish beyond what automation can cover, our post-production services handle finishing at the level brands expect.
A single master video can generate a dozen assets: shorts, reels, text summaries, and thumbnails. Each platform has its quirks, so matching the right export specs matters.
When a cut changes status, it can trigger the right notifications automatically.
Editors, colorists, and sound designers get alerts. Deadlines appear on calendars. Approved edits move to “publish” and final files archive themselves. Rule-based systems keep handoffs smooth.
AI can draft subtitles and translations, but a human should check for tone, culture, and brand voice. Accessibility isn’t optional; publishing with captions is required. See the WCAG 2.2 accessibility guidelines for captions on prerecorded video for compliance standards.
Regulators and platforms are tightening rules on disclosure. Creators must label synthetic or heavily altered content. Review YouTube disclosure rules for synthetic and altered media and TikTok requirements for AI-generated content labeling to avoid flagged posts or takedowns.
Metadata can travel with your files, confirming when and how AI assisted. Adobe Content Credentials for provenance tracking, built on the C2PA open standard for content authenticity, adds that label inside the asset itself. Delivery pipelines can now preserve these markers. Cloudflare’s image pipeline for preserving Content Credentials is one example of ensuring provenance survives across platforms.
Clear labeling
Accessible publishing
Trusted delivery
If it touches trust or taste, keep people in charge.
AI can schedule a call or send a reminder, but it should not be the voice replying to a client’s notes. Cut feedback, sensitive revisions, and big approvals demand a human response. Anything less risks damaging trust.
Story arcs, timing, pacing, and brand tone are emotional signals that shape how a viewer feels. Even advanced systems still trip on nuance, as the limitations of current text-to-video models show. Creative calls need human judgment because audiences notice when it’s missing.
AI can help brainstorm or speed research, but when it comes to likeness, voices, or music, the rules are clear: get consent and use proper licenses. Without it, the risks extend beyond reputation. They’re legal.
Industry rules and union contracts (see Policy, Legal & Platform Compliance Section) are tightening every year, and the safest route is to keep people accountable.
Trust
Taste
Legal clarity
And here’s the bigger picture: audiences can forgive a glitch, but not a brand that feels robotic or careless. That’s why the most memorable work comes from human choices supported by AI, not replaced by it.
See how we handle the balance between creativity and craft in our portfolio of client work.
Think of this as a balanced toolkit: editing features, a few automations that shave hours off routine work, and a trust label stamped on every file.
Keep footage in a shared library where it’s easy to find. Smarter AI-powered search inside editing apps is already arriving, which means editors spend less time rummaging and more time shaping.
This is where AI earns its keep. Features like speech-to-text transcription, text-based editing, and auto reframing for different aspect ratios handle the heavy lifting. Pair them with Resolve’s AI-assisted editing tools for faster rough cuts and subtitles.
Instead of chasing status updates, use workflows that automatically spin up project folders, assign owners or approvers, post Slack/Teams reminders, and archive final masters in your media library once signed off.
Every exported file should carry a digital label proving how it was made. Standards like Content Credentials and C2PA provenance tags help keep that chain of custody intact. Wider watermarking is also emerging, including Google’s SynthID embedded in Veo and Imagen 3. These are critical as platforms tighten synthetic content rules.
Finally, don’t overlook compliance. Regional frameworks like the EU AI Act are moving from proposal to enforcement. Building with disclosure and provenance baked in is future-proof.
Quick takeaway: Build a clear, dependable stack that handles the routine, keeps files compliant, and leaves people free to make the creative calls.
The fastest wins come from tasks that repeat over and over. Automating those is where the payoff shows up quickest.
When you need to resize one video into multiple formats, auto-reframing and batch captioning from speech-to-text transcription turn a single master into platform-ready assets in a fraction of the time (see Pre-Production and Production).
Tools like Enhance Speech for audio cleanup and text-based editing let editors assemble a rough cut quickly, which they can then refine creatively (see Pre-Production and Post-Production).
One strong recording session can feed an entire content pipeline. With smart repurposing for shorts, reels, and thumbnails, teams squeeze more mileage out of every shoot (see Distribution & Ops).
Quick takeaway: ROI doesn’t hide in bold experiments. It lives in the unglamorous but constant tasks (captions, reframes, first passes) that AI can knock out while humans stay focused on story and brand.
Technology only works if people know where they fit. The smartest move is to design the human workflow first, then layer in AI where it makes life easier.
Who does what:
Producer / Project Manager: Handles simple automations, checklists, and keeps status notes current.
Editor: Uses transcripts, rough cuts, and reframes with AI’s help but always makes the final creative calls.
Colorist / Sound Team: Starts with quick AI fixes, then applies the polish that only humans can bring.
Coordinator: Keeps reviews moving, tracks deadlines, and makes sure the right people get notified.
Start small. Measure your results. Keep human decision-makers on anything subjective. AI should never override taste or trust.
Every project should be published with captions. That’s part of accessible video standards for prerecorded captions. Accessibility helps your work reach more people and keeps you compliant.
Move fast, but stay safe. AI in video is also about staying compliant with copyright, likeness rights, and platform disclosure rules.
Here are the essentials:
Ownership of AI-generated work isn’t always straightforward. The U.S. Copyright Office guidance on AI-generated material makes it clear that only human-created elements are protected by copyright. This point was reinforced in the Thaler v. Perlmutter ruling (2025), which confirmed that AI alone can’t be the “author” of a work.
Entertainment contracts are already adapting. SAG-AFTRA’s AI resources and the 2025 Commercials Contract Summary outline how performers’ voices and likenesses must be licensed when AI is involved.
Writers also weigh in: the WGA’s 2023 MBA contract added provisions on AI use in scripted content. And in music, the RIAA lawsuits against Suno and RIAA v. Udio highlight how generative models that mimic copyrighted tracks are under legal fire.
Regulations aren’t the same everywhere. The EU AI Act sets one of the strictest frameworks, requiring transparency, risk assessments, and clear labeling of AI-assisted content. If you distribute globally, you’ll need workflows that account for different regional rules.
Detection tools aren’t foolproof. The NIST AI 100-4 report stresses that watermarking and content credentials are more reliable than trying to “spot” AI output after the fact. Using systems like Adobe’s Content Credentials (see distribution section) builds trust with platforms and audiences alike.
Think of this as a starter playbook. You don’t need to flip your whole workflow overnight. In fact, the fastest wins come from small, predictable changes stacked week by week.
Turn on provenance and disclosure templates (see content credentials and provenance labels) so every file is traceable.
Adopt a captions-first approach using caption accessibility guidelines, and every video leaves your shop with captions by default.
Pick three easy automations to prove value quickly: generate captions, use auto-framing for multiple aspect ratios, and set up a daily progress note.
Automate the “plumbing”: review/approval notifications, starter folder setups, and export presets.
Establish a repurposing rhythm. One master video becomes clips, shorts, text snippets, and thumbnails.
Add checklists for story, brand, and rights compliance (see Policy & Compliance). These become the non-negotiables where humans must weigh in.
Track wins: minutes saved, fewer errors, more posts delivered on time.
Add one more predictable automation to expand efficiency without breaking the flow.
When you’re evaluating partners or platforms for AI in video production, focus on what actually matters. Ask vendors if they support:
Content Credentials and C2PA provenance labels to track how your content was created.
Built-in disclosure tools that make AI-assisted clips transparent to platforms and audiences.
Strong caption support for accessibility compliance.
Audit logs so you know who touched what and when.
Reliable review and approval flows to keep teams aligned.
Export presets for consistent publishing.
EU AI Act readiness if you’re distributing internationally.
Legal indemnities and model/data transparency (no surprises down the line).
Mindset tip: always favor clear, rule-based features over vague promises of “AI magic.”
Want to see how a production partner balances creativity with compliance? Meet the Ajax team or explore the video portfolio.
Not every term is obvious. Here’s a quick primer with trusted references if you want to go deeper:
Generative video for ideation → tools like Runway Gen-3 show how far text-to-video has come (and where its limits are).
Provenance vs. watermarking → Content Credentials and C2PA (covered in distribution) show authenticity better than hidden watermarks.
Rule-based automation - predictable tasks with clear outcomes.
Digital replica - AI-generated likeness of a voice, face, or style.
WCAG captions - an accessibility standard requiring captions for prerecorded video.
For search visibility and client convenience, Ajax’s production and post-production hubs span multiple cities:
Post-Production:
Production: