Sara Pethybridge and Izzy Watts: We’re Training AI Faster Than the Producers Who Use It
By Sara Pethybridge (left) and Izzy Watts (right), Co-Founders, MettleLab
AI is being sold to the screen industry as a creative revolution, but the bigger issue is operational: we are training the tools faster than we are training the producers who will decide how, when, and whether those tools get used. If the industry wants AI to expand opportunity rather than intensify inequality, then producer training has to become the priority, not the afterthought. We know this because we just spent the last two days at the AI Masterclass for Women in Screen, and the room was full of producers needing answers about workflow and where we are actually at when it comes to AI in Australia. One thing that was clear – the screen industry is now a tech industry.
We’re training AI but not producers
We’re standing at a tipping point in how AI will reshape screen storytelling, pre-production, creative labour, usage and rights, and the business models that surround them. AI is not simply a new tool sitting inside the old workflow; it’s actually collapsing the workflow itself. Pre-production, production, and post-production are no longer linear stages; they are blurring into a single, fluid process in which planning, making, testing, and refining happen simultaneously.
This shift is exciting but destabilising for creatives who have spent decades honing their craft. Acknowledging this discomfort is vital to navigating the transition. AI is here to stay; to survive, we must pivot from fearing what is lost to seeing what is possible. But the good news is, the best AI output is driven by experienced creatives. While the tools are accessible to everyone, seasoned expertise gets superior results. Ultimately, AI increases industry complexity and complexity rewards those who can organise it. That is the producer’s role.
For decades, producers have been the people who make creativity actually happen. As we approach AI-native workflows, that role becomes even more important. Someone has to decide which tool is used for what, how much it costs, how to document the process, and whether the output is genuinely original or just a fast remix of everything already on the internet. That someone is the producer.
Why process matters
The masterclass highlighted a vital lesson: quality AI work starts with process, not prompts. Define the look and feel before moving into image generation. Build the world before you start making individual assets. Use the tools with intention, not as a shortcut. In practice, that means giving the model a role, asking for specificity, and building from a clear creative framework rather than a vague wish list. The more human the input, the more original the output, and the lower the risk of producing something generic, expensive or legally messy.
Scale, meanwhile, depends on skill. Tools like Leonardo, Runway, and Veo aren’t magic; they are only as effective as their operator. Understanding “lite” vs. “heavy” models, compliance, and pricing evolves the producer’s role from managing a project to managing a creative system.
That process mindset matters environmentally, too. Poor usage wastes time, tokens, and energy. Responsible producers must minimise waste in both budget and computation.
The legal gap
Australia is moving into this new landscape with very little legal clarity. There is no dedicated legislation telling the screen industry what can and cannot be done with AI, no meaningful model licensing framework, and no transparency requirement that makes disclosure simple or consistent. Copyright law still relies on human authorship and original expression but AI muddies all three. If you cannot prove the human creativity behind a work, you may struggle to protect it. If you cannot document ownership properly, you may struggle to exploit or defend it later.
Producers need to know when to add a clause that prevents a script from being used to train a model. They need to know when to require a note that says the material cannot be uploaded to AI without permission. They need to know why saving every prompt matters, why transparency matters, and why a clean digital trail is becoming part of modern production. If producers do not understand these issues, the industry will be negotiating the future blind.
Equity and access
This is where the Women in Screen context becomes essential. The AI conversation is already crowded with tech language, but not enough women are at the table shaping the rules, the workflows, or the culture around these tools. If we do not train producers now, the people who already have access, confidence and technical fluency will move fastest and the existing imbalances in screen will deepen. That is the opposite of democratisation.
Training producers is one of the few interventions that can actually change that. Producers can spread capability through teams, shape budgets, choose collaborators and set standards. If they understand AI well, they can create more opportunities for more voices, more formats and more efficient productions. That matters in a market where the audience is already moving toward shorter-form, vertical and platform-native storytelling. It also matters in a sector where leaner teams are becoming the norm and on-the-job learning is no longer enough.
What the industry should do
The screen industry must shift AI training from a novelty to core professional development. Producers require training in tool briefing, output management, rights protection, contracting, and workflow efficiency to ensure responsible use without exposing projects to risk.
Organisations, agencies, and broadcasters must align on a clear message: in 2026, AI literacy is a mandatory job requirement. The future of advertising won’t be defined by the flashiest models, but by those who use them ethically and efficiently. If we fail to train producers now, we’ll fall behind the worldwide creative revolution.
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