Earlier this week, former 360i and Profitero executives Bryan Wiener and Sarah Hofstetter launched a new CMO-focused consultancy called 37Arc. The company describes itself as “an AI-native workflow intelligence company that helps enterprises map and rewire how marketing work flows across teams, tools, and partners.”
Joining the duo are President Adam Broitman, CPO/CTO John Swords, and former LinkedIn executive Penry Price.
Read: “Bryan Wiener and Sarah Hofstetter launch CMO-focused AI firm” (April 7) – Ad Age (subscription)
Mr. Wiener answered a selection of follow-up questions from tipsheet via email.
tipsheet: In an AI-driven world, what does it actually mean to scale a consulting business — more people, more software, or something else?
Bryan Wiener: We do not think of ourselves as a traditional consulting firm.
Our diagnostic shares elements with how top consulting firms approach problem solving. It is a structured way to understand how marketing actually operates. We build on that by combining voice-based analyst agents with experienced marketing operators to map workflows quickly and with far more depth, compressing what used to take weeks into days.
Where the model differs is in how it extends beyond the diagnostic. We are structured to work alongside the organization to rewire and implement those workflows, connecting systems and automating coordination. That is where the model starts to look more like Palantir.
AI also changes the nature of the work itself. Every operator effectively has a co-pilot with the full context of the business. It can process large volumes of data, transcripts, and history in minutes, not weeks. These systems also get smarter over time as they learn the client’s workflows, decisions, and patterns.
So scaling is not about adding more people or just deploying software. It is about combining AI and operators to continuously improve how work flows, and scaling that system.
Do large language models meaningfully change marketing workflows today, and where are they still mostly noise for CMOs?
In enterprise marketing, LLMs do not fundamentally change workflows on their own.
Most organizations are layering AI onto systems that were never designed for this level of speed or complexity. The result is faster outputs moving through the same fragmented processes, which leads to more activity, not better outcomes.
This is not a technology problem. The underlying AI is already good enough. It is a visibility and change management problem. Until companies can see how work actually flows and redesign it, AI will remain underutilized.
As Nick Turley, head of ChatGPT, has said, enterprises need to “get proximate to the problems.” That is exactly right. AI only creates value when it is embedded directly into how work gets done, not layered on top.
We are starting to see that realization take hold more broadly. Anthropic is reportedly in talks with major private equity firms to form a roughly $200 million dollar joint venture focused on helping enterprises actually implement AI. That is a signal that the bottleneck is not model capability. It is execution inside the enterprise.
Where have you seen AI fail inside marketing workflows, not because of model limitations, but because of how the work itself is structured?
Most failures have little to do with the models themselves. They come from applying AI to workflows that are fragmented, poorly defined, or dependent on manual coordination.
You see it in very practical ways. Decisions that should take hours still take days because they require pulling reports, checking with agencies, and getting approvals. Marketers wait on analytics teams instead of having data at their fingertips. Across dozens of tools, there is no clear view of what is being used or how it connects.
AI gets layered onto that environment and accelerates parts of the process, but the bottlenecks remain. You get faster insights and more content, but not better outcomes.
That is why you see the gap in the data. McKinsey reports that 88 percent of enterprises are using AI, but fewer than 10 percent are scaling it in sales and marketing. The issue is not adoption. It is that workflows have not been rewired.
Fixing this is operational. Instead of waiting days to shift spend, AI can monitor performance and trigger pre approved reallocations automatically. Instead of relying on analytics teams, real time insights can be surfaced directly to marketers in the flow of work. Instead of managing disconnected tools, systems can be simplified and connected so there is a clear view of what is actually driving performance.
AI exposes what is broken. The value comes from rewiring how the work runs so those improvements can actually take hold.
What does the agency model realistically look like one to three years from now?
In an AI-driven world, the real differentiator is not who has the most tools. It is creativity, taste, judgment, and the ability to produce ideas that resonate.
The traditional agency model is built around labor intensive execution. Planning, producing, and optimizing across fragmented channels. AI compresses a lot of that work. If everyone is using AI to optimize the same things in the same way, marketing becomes a race to the bottom. Execution gets commoditized, and differentiation erodes.
At the same time, the economics are changing. The cost of producing marketing work is collapsing, while the volume is exploding. There will be more campaigns, more variations, more testing, and more decisions.
That creates a new kind of pressure. Trying to manage that level of scale with legacy workflows is like sending faxes in a world that has moved to email. It does not work.
What matters more is the ability to break through that complexity. Developing differentiated ideas, finding new ways to reach audiences, and adapting quickly. AI can assist with all of that, but it does not replace it. This is not autopilot.
So the value shifts in two directions at once.
- Toward higher order thinking, creativity, insight, and ingenuity.
- And toward designing and managing how execution actually happens across systems.
You will see fewer people doing manual work, and more emphasis on operators who understand both the business and the system. How data flows, how decisions get made, and how to continuously improve performance.
The firms that thrive, whether agencies, consultancies, or software platforms that evolve, will be the ones that can deliver both. Differentiated thinking and measurable outcomes, not just more activity.
The model will evolve, but the bar will be higher. In a more complex and fast moving environment, marketers will continue to rely on external partners, just with greater expectations around impact, speed, and accountability.