When Netflix recently revealed it used generative AI to create visual effects for its sci-fi show The Eternaut, it sent a shockwave through the media industry. The streaming giant confirmed the technology allowed its team to produce complex sequences "faster and at a lower cost," moving AI from a theoretical tool to a practical, budget-impacting reality. For industry veterans it was a defining moment, forcing creatives to face a technology no longer on the horizon but already in the studio.
This new reality is front and center for Daniel Basson, a Senior Lead Producer with over 15 years of experience creating high-quality video content for major global businesses. His perspective is not one of a futurist, but of a hands-on creative professional working in a highly-regulated corporate environment.
Not so scary: While many corporate leaders grapple with the risks, Daniel’s view from the producer’s chair is clear and direct. "AI helps us more than it's scary," he states. For him, the day-to-day benefits are not just theoretical; they are tangible, measurable, and in some cases, borderline miraculous. His team is often "spread quite thin, so it's helped us be a little bit more urgent," he says, framing AI not as a novelty, but as a necessary tool to solve real-world business pressures.
A full day's work: The most immediate impact is on efficiency. Daniel points to the monumental task of transcription, a manual process that has plagued producers for decades. "For a forty-five-minute documentary, it used to take a full day's work just to transcribe," he recalls. Today, AI automates that process in minutes, and the value isn't just the text itself, but the ability to make entire video archives instantly searchable.
The miracle worker: Beyond just saving time, AI is also rescuing work that was once lost forever. Daniel describes running failed, echoey field audio through a tool to get an astonishing result. "I can run that audio through a tool and make it sound as if it was recorded in a professional studio." But he is quick to ground this magic in reality, stressing that AI is an amplifier, not a panacea. "If you put something in there that's good, it will sound a lot better and more professional."
All comes back to data: Despite these clear, game-changing benefits, the professional reality for many in large organizations is one of "cautious innovation." Daniel describes a tentative corporate culture where fear and uncertainty are pervasive. The source of this corporate hesitation, Daniel argues, is a single, persistent problem: the black box of how AI models are trained leaves regulated businesses exposed to legal and ethical risks.
The solution, he believes, is surprisingly simple. "It all comes back to the training data." He points to platforms like Adobe's Firefly, which is built on a model that is designed to be commercially safe. The reason for the trust is explicit. "With Adobe, our data set is trained on data that we actually own, so there's more trust there." This insight reframes the entire debate from a vague fear of AI to a concrete due diligence question about data provenance.
The art of the prompt: Ultimately, Daniel argues that AI will not replace the human creator, because the models are built on a foundation of "human-created work." He believes its current power lies in "replacing some of those tedious tasks," freeing up human capital for higher-level thinking.
The future creative skillset, he says, is mastering the art of the prompt. "There's something to be said about being creative with your prompts. You have to infer the way your request is going to be interpreted." The human creator isn't being replaced; their role is simply becoming more strategic. "It's quite exciting."
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*Daniel Basson's opinions expressed in this article are solely his own, and do not necessarily reflect the views of his employer.