AI makes technical video skills a commodity

On TikTok, Rourke Heath argues that AI video editing tools will soon make high-end motion graphics a standard rather than a mark of quality. He suggests that as these tools democratise professional editing, most content will begin to feel predictable and generic. While he advises editors to adopt AI to speed up technical workflows, he believes human intention remains the only way to stand out. We agree that technical proficiency is becoming a commodity, but we believe the real value lies in the curation of taste rather than just avoiding generic outputs.

Why it matters

Business owners often view AI as a way to cut costs by replacing skilled creators with automated tools. This is a mistake. If you use AI to produce your entire social media presence, you are effectively choosing to look like everyone else. High production value is no longer a competitive advantage if a machine can replicate it in seconds. The risk is not that AI replaces your editor, but that it makes your brand invisible through sheer uniformity.

True differentiation now depends on the specific aesthetic choices that an algorithm cannot predict. We see this in how audiences react to hyper-edited content; they eventually crave something that feels grounded and deliberate. For a company, the value of a creative partner is shifting from their ability to use software to their ability to exercise judgment. You should use AI to handle the repetitive tasks, but never let it dictate your brand's visual identity.

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technical proficiency is becoming a commodity

— Balkaris

How it actually works

AI video production relies on a combination of pattern recognition and generative models. These systems do not understand your brand or your intent. Instead, they analyse vast datasets of existing media to predict which pixel or sound effect should follow the previous one. As Rourke Heath notes on TikTok, this process tends to produce the most predictable output because the machine is essentially averaging out everything it has already seen. To use these tools effectively, you must separate the mechanical assembly from the creative direction.

1. Data InputYou provide the raw footage, audio, or text prompts to the model.
2. Pattern AnalysisThe AI identifies structures, such as common cuts or rhythmic patterns in existing videos.
3. Generative ExecutionThe software generates motion graphics, sound design, or transitions based on those patterns.
4. Human RefinementThe editor applies specific taste and intention to ensure the result does not feel generic.

What it changes in practice

For most small and mid-sized Swiss companies, the impact of AI video tools is negligible today. You likely do not produce enough high-frequency video content to feel the shift in market saturation. However, if you rely on social media marketing to drive growth, the rules are changing. The barrier to entry for producing polished videos has dropped to near zero. This means your competitors can now generate decent motion graphics without hiring a specialist. To avoid looking like everyone else, you must focus on specific brand nuances that a prompt cannot capture.

• Motion design is no longer a luxury signal; it is a baseline expectation.
• Budget should shift from basic assembly to high-level creative direction.
• Content creators must prioritise unique visual references over algorithmic trends.
• Workflow efficiency increases as AI handles sound design and repetitive cutting.

Where it goes wrong

The danger is not that AI replaces your editor, but that it replaces your taste. Many brands treat generative tools as a shortcut to skip the thinking process. They mistake high-frequency output for high-quality engagement. This leads to a feedback loop where your content looks like every other brand in your feed. You end up spending money to look generic, which is the fastest way to lose audience trust.

• Using AI to automate the creative decision instead of the technical task.
• Relying on hyper-retention editing styles that viewers are already starting to ignore.
• Assuming that a polished aesthetic equates to a meaningful brand message.
• Neglecting the unique visual references that define your specific company identity.

Who should act, and who should wait

You should act now if your growth relies on social media presence. If you are currently building a brand identity through video, you must integrate AI into your workflow to maintain speed. Use it to handle repetitive tasks like sound design or basic colour correction, but do not let it dictate your visual style. Conversely, if you only produce video for internal training or occasional product announcements, you can wait. The current volatility in AI video quality does not affect low-frequency corporate communications. For these companies, the cost of experimenting with unproven tools outweighs the benefit of marginal speed gains.

What we would do

We do not use AI to generate a brand's visual identity. Instead, we use it to remove the friction between an idea and a finished edit. Our goal is to use these tools to increase the volume of high-quality output without losing the specific aesthetic nuances that make a client recognisable. We prioritise human intention over algorithmic speed.

1. Workflow integrationWe assign AI to handle tedious sound design and basic rotoscoping to free up time for creative direction.
2. Reference curationWe build bespoke visual libraries from non-digital sources to ensure motion graphics do not look like standard AI outputs.
3. Quality controlWe review every AI-assisted frame to ensure the movement feels intentional rather than purely reactive to a trend.

Within twelve months, AI will generate entire brand guidelines from a single prompt. This happens if generative models master consistent spatial logic. When that occurs, your only defence against invisibility will be the specific, irrational human choices that machines cannot replicate.