Breaking Silos: Can AI Be Co-Owned within Agencies?
BY AARON KOVAN, EVP CREATE AT PROSE ON PIXELS
By now, we know AI isn’t coming to advertising – it’s already here. It’s writing copy, generating visuals, editing videos, analyzing data, and even pitching ideas. The question is no longer if AI belongs in the agency ecosystem, but where it belongs – and whether it can truly serve both creative and production teams without compromising craft and efficiency.
Traditionally, creative and production have operated in parallel but separate lanes. Creative teams spark ideas; production teams bring them to life. But AI doesn’t respect these boundaries. It’s a tool that flows between ideation and execution, challenging the very structure of how agencies work.
The Case for AI in Production
Production has always been the engine of scale and precision – and that’s why AI fits so naturally here. It’s where ideas are refined, formatted, and delivered, on time, on budget, and on brand. Technology allows smart automation and eases tasks like resizing assets, checking legal copy, and versioning content – while also ensuring governance, consistency, and compliance. It’s measurable, efficient, and cost-effective.
But production isn’t just about logistics. It’s also a creative partner. AI-generated motion graphics, video templates, and dynamic layouts can inspire new directions and expand the creative palette. When used strategically, AI in production saves money and unlocks new possibilities.
Confined to production, though, AI may be seen as a “cheap tool”: useful but uninspiring. To avoid this trap, agencies must show that creativity flows both ways, and that production-led AI can spark just as much innovation as it supports.
The Case for AI in Creative
Recently, AI has become a catalyst for imagination. Writers can prompt it for dozens of campaign lines, designers can generate concept variations in minutes, art directors can build mood boards and storyboards faster than ever before. Undoubtedly, AI enables play, experimentation, and rapid prototyping, fuelling the kind of bold thinking clients expect.
But without production’s guardrails, creative-led AI can be inconsistent. Quality may vary, IP risks may multiply, and outputs may not be scalable or brand-safe. While AI is a front-end innovation engine, production input ensures these ideas are practical, on-brand, and production-ready.
That’s why collaboration is essential. When production feeds into creative workflows – and vice versa – AI becomes a shared tool that enhances both sides of the process.
Maybe It’s the Wrong Question
The real issue isn’t who owns AI, but how we integrate it. While many agencies were built on silos, AI is inherently cross-functional.
A script generated by AI may rely on production insights. A motion graphic created in production may spark a new campaign idea. AI outputs from production often feed directly into creative ideation. Creative prompts often rely on production-ready assets. Clients themselves are experimenting with AI, further blurring the lines.
This back-and-forth proves that AI isn’t owned by one department – it’s owned by how effectively teams collaborate.
So, What Do We Do?
If AI is the connective tissue of modern agency workflows, then fluency across disciplines is essential. Writers must learn to prompt with precision. Producers need to explore generative video and automation tools. Designers should understand how to accelerate creative development without compromising quality or brand integrity. This is about mastering a single platform and, mainly, about cultivating a shared understanding of how AI can elevate every stage of the process.
The establishment of unified guardrails is key. Copyright, bias, transparency – these aren’t just legal or ethical concerns. Governance must be co-owned by both creative and production teams to ensure AI outputs are compliant, consistent and purposeful.
Real transformation happens when teams pilot AI together. When creatives and producers co-lead projects, they uncover efficiencies and imaginative breakthroughs. This kind of collaboration reduces errors and redefines possibilities. On top of that, as roles evolve, new hybrid functions emerge, signalling a shift towards integrated thinking and the rise of new mindsets, designed to bridge the gap between ideation and execution.
AI implementation is about cultural shifts. The real challenge isn’t deciding where it belongs but learning how to let it move freely across disciplines. When creative and production teams co-own AI, they unlock its full potential: work that’s faster, smarter, and more imaginative, delivering both operational scale and creative impact.
So, can AI be both? Yes – but only if we let it.
Comments are closed.