People First. AI Forward: How Meet the People Is Operationalizing AI

AI is forcing a redefinition of how we work. It’s showing up in meetings, briefs, workflows, and pitches faster than most people expected. But while the pace of adoption is accelerating, the need for clarity and alignment on how to use it, and when to use it.

These incredible tools can process more information than we’ll ever hold in our heads. They remember everything, synthesize at speed, and operate at a scale we can’t touch. But they have no imagination beyond their training. No ethics. No ambition other than to satisfy a prompt. They can’t see what hasn’t already happened.

That’s where we come in.

Humans imagine what doesn’t exist yet. We create ideas from lived experience. We ask questions with no precedent. The challenge now is: How can we use the power of AI to support the people behind the work, so we can reimagine how we create, collaborate, and scale in smarter, more sustainable ways?

How do we extend our thinking without overriding it?
How do we protect our data, live our values, and still make space for creativity to lead?

At Meet the People, we’ve chosen a guiding principle for this new era:
People First. AI Forward.

So how do you operationalize that kind of ambition across ten independently run agencies?

We created the MTP AI Council.

To start with the end in mind, we built our Council around a simple matrix that reflects how our network actually operates. Across the MTP network, we organize our work into three core verticals: Creative, Commerce, and Media. Our agencies; VSA, Public Label, True Media, Saltwater, Coegi, Radar, Match Retail, and Swell Media, live and breathe these specialties. That means each one has different needs, different workflows, and different entry points for AI. To make sure we’re addressing all of it, the Council aligns each agency vertical against three key pillars: Governance, Education, and Implementation.

This framework gives us a clear way to focus on real use cases with value instead of getting stuck in broad conversations about “the future of work.”

We don’t romanticize AI. We recognize the risks; from data safety to biased output to regulatory ambiguity. These systems don’t come with a moral compass. They don’t understand context, consequence, or nuance. That’s why governance isn’t a side conversation. It’s a critical foundation for how we work with AI tools and technology.

Our Governance group is made up of legal, IT, and operational leaders who are building the guardrails: smart policies, ethical standards, and clear communication frameworks for how we use AI both internally and externally. Their work helps ensure we move with intention, not just momentum.

While many people have now interacted with a large language model in some way, training and education are still essential if we want to build a team that can meaningfully wield these tools and innovate beyond the basics.

Some people learn by experimenting. If they’re following our governance guidelines, we encourage that. It’s a great way to build confidence and inspire future use cases. Others may need structured training to be set up for success. And not everyone wants to build their own tools. That’s fine. We’re creating space for all of it.

We recognize that across our agencies, people will play different roles. Some will envision what the tools should do. Others will build them. Many will simply operate them as part of their daily workflow. And to be clear, we’re not talking about developers. We’re talking about regular people using plain English to create powerful tools, no coding required.

Moving from rule-based software to language-based collaboration is a fundamental change in how we work with technology. That means education isn’t just about learning. It’s a completely new way of thinking about how work gets done. A complete mindset shift.

The Implementation pillar is where we stop talking about what’s possible and start defining what’s actually worth doing. This is where real tools, real workflows, and real value meet.

The work here isn’t about testing AI against how we’ve always done things. It’s about reimagining the workflows themselves. Where can automation, augmentation, or AI-driven insight unlock better output, greater efficiency, or free up time for deeper thinking? That’s the lens.

Of course, it takes time. There’s upfront effort required to rethink how work gets done, and that effort can feel slower than the headlines suggest. But the long-term payoff is the point. If AI offers anything close to “unlimited time,” the only way to get there is by investing the time now to save the time later.

The teams working on implementation are building playbooks and protocols that shape how AI gets operationalized. And since each agency in our network works a little differently, we’re able to learn fast, share insights, and pressure-test across disciplines. Some use cases will be universal. Others will push the boundaries of what’s possible for our clients. Both are essential. Both are happening.

This isn’t about mastering AI. It’s about building a mindset, a process, and a shared language to explore what’s worth doing and why. The biggest shift isn’t technical. It’s cultural. It’s about learning to work with technology that doesn’t follow rules but learns from patterns. Technology that doesn’t understand your values unless you teach it.

At Meet the People, we’re not waiting for a perfect roadmap. We’re figuring it out in real time with the people already inside our agencies. Some of us are experimenting. Some are building. Some are still asking questions. That’s exactly the point.

We’re doing the upfront work now because we believe the teams who take this seriously, ethically, creatively, operationally, will be the ones who get the biggest return later. Not just in efficiency or margin, but in talent, opportunity, and momentum.

AI isn’t replacing us. It’s requiring us to get sharper about what makes our work matter.
People First. AI Forward.