The Future of Production Is More than a Prompt

by Jake Sugarman, SVP, Head of Partnerships and Growth, ROOM42, a part of Real Chemistry

Research shows that writing something down makes it 42% more likely to happen. So this is worth putting in writing: the next chapter of creativity, craft, and production excellence will be defined by strategic execution—knowing what to make, how to make it, who needs to make it and see it and which tools are right for the job.

Many large networks are increasingly positioning AI as the singular solution for the future of production, all through the lens of scalability. That ambition is understandable: AI, automation, and emerging technologies should underpin how modern production works. They should make processes smarter, faster, more connected, and more scalable. But they should not replace the need to define the right approach in the first place. When the conversation starts with the tool and works backward, production risks becoming narrower, not smarter. The more important strategic questions are what should be made, why it matters, where it will live, what level of craft it requires, and what risks need to be managed. Then we can move to the how.

AI is transforming production in important ways by creating efficiency, automation, intelligence, and new forms of possibility. The point is not to keep AI separate from the work; it is to embed it into the way work gets made. AI and other technologies should underpin production processes, helping teams brief better, version smarter, streamline reviews, accelerate execution, and improve consistency. The value comes from knowing how to apply those tools with the right human expertise, workflow, and level of craft.

That distinction matters even more in healthcare, where the method is part of the product. Outcomes are judged through the lens of trust, precision, and regulatory reality, which means how the work is made is inseparable from what the work ultimately says. Process is not operational background; it shapes quality, credibility, and mitigates risk.

Content volumes are increasing, attention is fragmenting, and production teams are being asked to move faster without lowering standards. The answer cannot be to treat AI as an isolated shortcut, or assume that one execution model can solve every challenge. The more useful question is how to build AI and other technologies into the process in the right way: choosing the right talent, the right tool, the right workflow, and the right level of investment for the audience, channel, risk, and creative ambition.

Current trends and questions about AI are forcing brands to explain whether, and how, AI was used in their work. That conversation is often framed as an either/or: human or machine, authentic or automated. But the more productive lens is both/and. AI can accelerate creativity, remove friction, expand what teams can make, and improve the systems behind the work. It cannot replace emotion, empathy, intuition, or craft. Those remain human responsibilities.

The strongest production models will be the ones that understand this balance. They will not define themselves by a single method, platform, or technology. They will build fluency across all of them: AI tools, live action, post-production, design systems, modular content, offshore and nearshore models, specialist craft, and high-touch creative problem solving. The future belongs to production partners who can use all of these intelligently, not indiscriminately.

The production challenge ahead is not simply about adopting AI. It is about embedding AI and other technologies into systems that can manage compliance, speed, fragmentation, and creative quality at the same time. In healthcare especially, the guardrails are not obstacles to creativity; they are part of the creative brief. That makes production less of a downstream function and more of a strategic discipline: the place where ambition, regulation, budget, timing, technology, and execution have to be reconciled without weakening the work.

The future of production will not belong to the teams that treat AI as a bolt-on, a shortcut, or the answer to every execution challenge. It will belong to the teams that know how to embed AI and other technologies across the full production process, while still choosing among the full range of tools, models, and craft disciplines available. The best production partners will use every tool available, but they will understand that the real advantage is not the tool itself. It is the strategic judgement to know what the job requires, and the executional discipline to make it work.