Upstream Strategy, Strategic Rigor, and the Fallacy of Fast AI

As a CMO, I'm invited to a lot of industry events, and I'm constantly weighing the value of my time against everything I'm accountable for delivering. I know other marketing leaders are doing the same.

When we started thinking about the next Spark Conversations, I didn't want to create another event where people listened to a presentation, exchanged business cards, and went back to their organizations doing exactly what they'd done before.

I wanted to create something that might genuinely challenge how people think.

There's tremendous value in hearing from industry experts, but there's also incredible expertise in the lived experiences of the people doing this work every day. They're navigating organizational politics, managing handoffs, making difficult decisions, and trying to deliver results within processes that aren't always designed to support them.

We wanted to bring those people together, remove the traditional speaker-audience dynamic, and give them the opportunity to learn from one another. Sometimes all it takes is one conversation or a different perspective to make you go back to your organization and say, "Why are we still doing it this way?"

A. I think we've become so accustomed to talking publicly about our successes, that we don't always create enough opportunities to talk candidly about what's not working. And those are often the conversations we need most.

Brands and agencies are also operating in an environment where what can be shared publicly is increasingly scrutinized. Even when there's a great story to tell, getting approval to speak openly about the work, the challenges, or the lessons learned isn't always straightforward. We wanted to remove some of those barriers.

When you're discussing global campaigns, you're inevitably talking about organizational structures, competing priorities, technology investments, and decisions that haven't always delivered the results people hoped for. A closed-door conversation creates an opportunity to explore those challenges without feeling that every comment needs to be polished, approved, or representative of an organization's official position.

The intention wasn't to bring people together to showcase success stories. It was to give them the space to share real experiences, challenge assumptions, and learn from one another.

I think there's tremendous value in creating opportunities for industry peers to have those conversations, particularly at a time when everyone is trying to navigate what AI means for how marketing operates while managing up.

A. I never expected us to solve the challenges of global campaigns or AI in three hours. That wasn't the objective. What I hoped we could do was get people to question things they've come to accept as simply the way marketing works.

The global campaign process is complex. There are multiple teams, stakeholders, markets, approvals, and handoffs. And when something isn't working, it's easy to say, "Well, that's just how it is in our organization." I wanted to challenge that mindset.

It's easy to continue working within a process you've learned to navigate, even when you know it could work better. Changing it requires questioning established ways of working, challenging assumptions, and sometimes having uncomfortable conversations.

But hearing how others are navigating similar challenges can be a powerful catalyst. Sometimes you don't need someone to hand you a solution. You need a different perspective that makes you rethink your own.

Spark also has an important opportunity to listen and learn. We know the challenges we experience working with brands, but what are brand teams experiencing on their side? What frustrations are they navigating internally? What do they wish their agency partners understood better?

For me, success wasn't leaving with all the answers. It was leaving with better questions, a deeper understanding of one another's challenges, and perhaps the confidence to go back and start doing something differently.

A. What I found interesting was that people kept pointing back to the earlier stages of the process, even when we were discussing challenges much further downstream. The message was essentially, "If we'd been involved earlier, we wouldn't be dealing with so many of these problems now."

People described receiving work with very little visibility into the decisions that had already been made, then being expected to respond quickly, manage revisions, and navigate challenges that potentially could have been avoided. That was one of the most interesting aspects of the conversation for me.

We tend to look at bottlenecks where they become visible, but that isn't necessarily where the problem originated. If adaptation is taking too long or creative is going through multiple rounds of revisions, perhaps the first question shouldn't be how to accelerate that stage. It should be what happened earlier that created the need for all that additional work.

The five-stage framework gave us a way to structure the discussion, but the conversation reinforced that these stages don't operate independently. Decisions made at the beginning have consequences throughout the entire campaign journey.

A. I think we've become a little too enamored with what AI can produce, and I'm finding myself increasingly disappointed by how readily some of that output is accepted. Just because something looks finished doesn't mean the thinking behind it is complete. And just because we can produce ten creative directions in minutes doesn't mean we've identified one genuinely strong idea.

For me, this comes down to the standards we set for the work and the rigor we bring to solving problems. If you have a disciplined approach to understanding a challenge, questioning assumptions, and evaluating what good looks like, you should bring that same discipline to AI. Technology shouldn't change your expectations of the quality of the work.

Something that struck me during the conversation was how little visibility some creative teams have into what happens beyond their part of the process. A brief might tell them that a campaign needs to work across 40 markets, but does it help them understand the considerations that could influence the creative direction in those markets? Do they understand the challenges localization teams regularly encounter?

It's not necessarily about involving everyone earlier. It's about making sure the right knowledge and context are available when decisions are being made. Otherwise, AI may simply help us produce work faster that someone else will have to fix later.

AI doesn't eliminate the need for rigor - it exposes whether you had any to begin with.