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The Promise, the Pitfalls and the Price: How AI Video Generation Really Differs From Traditional Video Editing
The early promise of generative AI (GenAI) tools for business included assurances that this technology would soon be able to produce fully featured video content. The assumption that this capability was close to ready may have influenced decision-makers to deemphasize traditional video content production.
Thus far, the reality hasn’t matched the hype, which leaves companies in an awkward position. Those who have cut down on their production infrastructure are now left with neither conventional nor GenAI workflows in place.
AI’s role in video production doesn’t currently feature the promised full video generation based on text prompts, and even an idealized version of the technology could have issues with legal liability and licensing. With that said, there are jobs for GenAI within production and editing workflows. Realizing these true use cases is a worthy goal for today’s businesses.
How AI video generation works: Hype vs. reality
While the early promise of GenAI video creation involved nearly limitless creative freedom, the reality has included a series of disappointments. Producing videos for brand use comes with a need for strict controls and precise branding. The technology in its current state has proven unable to deliver these measures, with issues like scene-to-scene consistency and continuity proving especially challenging.
Some of the prominent issues that are keeping GenAI from being a cure-all technology for corporate video production include:
- Legal corporate citizenship questions around fair use, copyright and responsible use of images and likenesses.
- Potential pushback from audiences, content creator organizations and corporate partners who disapprove of GenAI use.
- Continuity problems and other quality matters created by AI algorithm shortcomings affecting the finished product and detract from the videos’ appeal.
- Emerging skill gaps on companies’ internal teams due to large-scale or over-aggressive staff cuts or hiring freezes around traditional methods of production.
Some of the conditions facing companies are tied closely to their corporate, contractual needs — for instance, clients specifying in their contracts that creative agencies not use GenAI, so as to avoid potential legal entanglements.
Even in the consumer world, these issues are coming to the fore, with users encountering functional limitations on Sora 2. This is the latest video generation model from OpenAI, which acts as a sort of social media network and involves AI avatars of real users.
What these challenges collectively add up to is a gap between expectation and reality. Companies can’t presently use GenAI to create finished-quality videos, and doing so can be legally precarious. This means they need to find another way forward.
AI’s role in video editing
AI video tools, ranging from GenAI to machine learning, do have a role within traditional methods of video production, though potentially not the one leaders have been envisioning. By seeking efficiency gains throughout the video editing process and publishing workflow, companies can put AI tools to work for them.
Tasks such as transcription and storyboarding can move more quickly and efficiently when editors are supported by GenAI tools. Production software and editing suites equipped with this technology can be a difference-maker for video crews that have made the upgrade and familiarized themselves with the latest offerings, climbing the potentially steep learning curve and integrating new equipment.
Part of the video editor’s toolkit
Adding speed to the editing process through rough adjustments is an approach that lets a human content creator assert greater control over their artistic vision. Compared to fully AI-generated video footage, the output is more human.
Turning raw footage into finished video clips involves several rounds of editing — everything from color grading and the application of visual effects to the addition of sound effects and choice of transition styles. These choices are part of a human’s artistic vision, but automating some of the technical aspects is a way to combine creative control with tech-driven efficiency.
The overall findings from the early years of AI use include the revelation that the most immediately impactful use cases often involve small functional improvements. While big-swing, game-changing uses, such as generating whole, finished videos from text prompts, are more likely to grab headlines, crews are better able to achieve success by making incremental progress.
Working with video producers and editors who are on top of the latest technological developments can give a brand a functional advantage compared to competitors. While this progress may not look like the revolutionary change promised by early GenAI hype, it has the potential to deliver real results for companies across industries.
Use technology to empower your video workflows
The early months of GenAI promotion may have done a long-term disservice to AI algorithm use as a video production tool. Dissonance between promises and reality is causing issues for companies that actually do have AI use cases within their video workflows.
Companies that embrace the latest tech trends for their real potential rather than their hype can gain powerful new capabilities in their efforts to keep up with the never-ending demand for more video content from corporate audiences. By mastering different platforms as they emerge, these editors can add speed and efficiency to their visual storytelling without compromising their creative vision.
Working in tandem with a video production partner organization is a way to tap into the latest trends without making large capital investments. These experts have built up their knowledge of the latest tools and tricks of the trade and can bring these methods into play to help businesses keep up. The end goal is producing clips that audiences will appreciate: while equipment changes, this objective stays the same.
Read our eBook for much more on video production in the era of GenAI.
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