The hype around generative AI has done its job: it opened minds, unlocked budgets, and pushed enterprises into a new phase of digital ambition. But moving from excitement to execution requires something deeper — a rethinking of how work is structured, how systems connect, and how creativity can thrive at scale with intelligence embedded from the start.
In Brazil — one of the most dynamic and fast-paced advertising markets in the world — we’re at the beginning of that transformation. Here, agencies often operate as fully integrated structures, combining creative and media under the same roof. This model, quite different from what’s common in the US or Europe, brings both advantages and challenges when it comes to enabling AI-driven transformation at scale.
We’ve tested AI in different creative and operational contexts over the past years — from automated content adaptation to trend analysis — but we’re now piloting an enterprise-grade platform that brings orchestration and intelligence to the entire content supply chain.
The platform we chose is Adobe GenStudio, which is helping us rethink how we create, manage, and activate content across teams. We’re still early in the implementation — running live pilots, testing real workflows — but it’s already clear: this isn’t just about using new tools. It’s about working differently.
Why GenAI Needs Structure to Succeed
There’s a tendency to treat generative AI as a plug-and-play solution. But the reality inside large organizations is far more complex. Without the right architecture — connected workflows, modular teams, content taxonomies, governance frameworks — AI becomes another silo, another shortcut that doesn’t scale.
That’s the shift: from isolated use cases to embedded systems. From ad hoc acceleration to end-to-end orchestration.
AI is not just here to help with tasks. It’s becoming part of the operational backbone — something you build around, not on top of.
What We’re Learning as We Build
Even in the early stages, some key insights are already shaping how we move forward:
- Pilots Must Be Real
We chose to test in real-life conditions — inside live workflows, with actual campaigns and real deadlines. That means accepting a bit of risk to unlock real learning. AI needs tension to be useful — and that only shows up in the live environment. If it only works in a sandbox, it doesn’t really work.
- Don’t Rush the Tools
Resist the urge to fully commit to any solution too early. Pilots are not just a checkbox — they’re a strategic phase for adoption, iteration, and internal alignment. A well-run pilot reveals what matters most: usability, integration, and actual impact on the team’s daily work.
- It’s Not Just About Roles — It’s About the Way We Work
AI doesn’t necessarily replace roles, but it reshapes how we operate. It changes the tempo, the expectations, the interfaces. From creative leads to strategists and operations managers, everyone is adjusting. So instead of redesigning org charts, we’re focusing on evolving the way of working — with more fluidity, modularity, and collaboration across silos.
- Governance Must Be Seamless
If governance feels like a burden, people will work around it. That’s why it has to be invisible and automated — version control, usage rights, approvals, compliance — all handled in the background. Not as bureaucracy, but as part of the flow.
- Efficiency Comes from Integration — Inside and Out
One of the biggest opportunities lies in connecting the broader ecosystem — clients, partners, collaborators — into the same operational logic. When systems talk to each other, when inputs are centralized, and when workflows extend beyond the agency’s walls, that’s where real efficiency and responsiveness can scale.
The Real KPI Is Relevance at Scale
What we’re ultimately building toward is relevance — at scale, in context, and at speed. That means creative operations that are not only efficient, but meaningful. Where personalization and consistency are not trade-offs, but parallel goals.
Generative AI helps us get there — but only if it’s integrated from the foundation. When intelligence is embedded in the system, not added as an extra layer, we create a structure where content adapts, teams move faster, and the work stays connected to culture.
Looking Ahead: A Work in Progress, Not a Playbook
We’re not presenting a finished case. We’re still in the early chapters — testing, adjusting, listening. But even now, one thing is clear: the future of creative operations won’t be built on tools. It’ll be built on systems that connect creativity, data, and technology with clarity and purpose.
The real innovation isn’t in what AI can do on its own. It’s in how we design the environment around it — so that talent, intelligence, and structure move in sync.
Final Thought
AI is not the strategy. The strategy is to deliver faster, more consistent, more relevant work. And AI — when embedded with intention — helps enable that.
It allows us to reduce the noise, scale what matters, and shift our focus from managing complexity to amplifying creativity.
