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86% of marketers are excited about AI. Only 28% are actually rewiring how their teams work. That gap is where your competitors will eat your lunch. The Three Rewires Every CMO Needs to Make.
Jim Lecinski, clinical professor of marketing at Northwestern University’s Kellogg School of Management and author of The AI Marketing Canvas, lands a message that most CMOs aren’t ready to hear: layering AI onto your existing team structure is not a strategy. It’s procrastination dressed up as progress.
The real move? Rewire the work. Rewire how humans and AI collaborate. Rewire the org itself.
Let’s break down exactly what that means and more importantly, what it means for you right now.
The Honest State of AI in Marketing Today
Before we get tactical, let’s sit with the data for a second, because it tells a story that should make you uncomfortable.
According to the McKinsey research, Lecinski collaborated on:
- 86% of marketers say they’re excited about what AI makes possible
- 60% use AI multiple times per week
- 57% report feeling anxious about what AI means for their role
- Only 28% say their companies are pursuing a fundamental rewiring of marketing teams and workflows
Read that last number again. Nearly three quarters of marketing organizations are running AI on top of the same org chart, the same processes, and the same job descriptions they had before any of this started. They’re using AI to do the old work faster not to do fundamentally better work.
That’s not transformation. That’s automation of the status quo. And the organizations that figure that out first will have an enormous structural advantage over the ones still congratulating themselves for using ChatGPT to write subject lines.
What Actually Changed: From Chat Assistant to Agentic Execution
Here’s the shift that makes everything else necessary.
Six months ago: Most marketers used AI as a chat-based assistant. Prompt in, output out. You directed every step. The AI was a fast intern.
Today: AI is moving toward agentic execution. Marketers define the task, provide inputs and guardrails, hand the work to an AI agent, and evaluate the output. The AI doesn’t wait to be asked. It works.
This is not a tool upgrade. It’s a structural change to how marketing work actually gets done, which means the teams designed to do that work need to change too. Job descriptions written for the chat-assistant era are already out of date. Org charts designed around who-does-what in a human-only workflow need to be redesigned around who-does-what in a human-AI workflow.
Lecinski frames it clearly: this is “no longer just a technology issue. It’s an operating model issue. It’s a talent issue. It’s an org design issue.” And increasingly, it’s what your CEO and CFO are going to be asking you about.
The Three Rewires Every CMO Needs to Make
Rewire #1: The Work Itself
Before you touch job titles or org structures, you need to understand your workflows better than you currently do. And most marketing leaders don’t.
Here’s a line from the piece that should stop you cold: “Most marketing organizations still know their org chart better than they know their workflows. In the human-AI era, that’s backward.”
The workflow is now the real unit of change not the role, not the team, not the department. If you can’t map how a piece of work actually moves from start to finish, you can’t redesign it for AI. And if you don’t redesign it, AI just gets bolted onto yesterday’s process, which means you’re paying for AI horsepower while driving on the same old road.
The move: Pick three to five high-value, high-frequency workflows and map them end to end. Not twenty. Not your entire marketing operation. Just three to five. Think: how you segment audiences, how you plan promotions, how you test creatives, how you score leads, how you report on performance. Map the actual steps. Who does what. Where decisions get made. Where rework happens. Where the bottlenecks live.
That map is your starting point. Everything else builds from it.
Rewire #2: Human-AI Collaboration
This is where the real complexity sits and where most organizations are getting it wrong.
“Humans and AI will work together” is not a management model. It’s a bumper sticker. A CMO needs to define the hybrid partnership with surgical precision: What should humans own? Where should agents act autonomously? Where must a human review before anything moves forward? Where should judgment stay 100% human, no exceptions?
Lecinski uses a concrete example that illustrates the shift perfectly. Take the task of turning focus group transcripts into an executive recommendation. Old model: a researcher manually works through hours of material, clusters themes, writes the narrative, packages the output. New model: an AI system ingests the transcripts, extracts themes, synthesizes, and produces a first-draft management readout.
What changes for the human? Everything shifts upward. Less time spent on the execution layer assembling intermediate output. More time at the beginning (framing the right business question, defining what good looks like) and at the end (reviewing the synthesis, exercising judgment about what actually matters, deciding what to recommend).
The human moves from doing the work to setting the standard and evaluating the result.
The move: Take one of the workflows you mapped in Rewire #1 and define the human-AI handoffs step by step. Not in broad strokes. In writing, for each stage: Who commissions this work? Who performs it human or agent? Who checks it? Who approves it? What happens if the output is weak or wrong? What happens if inputs conflict?
Don’t skip this. The most common failure mode right now isn’t bad AI. It’s bad role clarity. Teams are told to “use AI” without anyone redesigning how the work actually flows. The result is duplication, fuzzy accountability, anxiety, and surface-level adoption, which is exactly what that 57% anxious stat is telling you.
The underlying principle: As execution gets cheaper and faster, human vision and judgment get more valuable, not less. The scarce resource in an AI-powered marketing team isn’t content or copy or data pulls. It’s sound judgment applied at the right moments in the workflow. That’s where humans win. That’s where you should be spending your best people’s time.
Rewire #3: The Organization
Only after you’ve mapped the work and defined the human-AI partnership should you touch the org chart.
Most CMOs start by asking whether AI will shrink their team. That’s the wrong question. The right question is: what shape and skill mix does the team now need?
Here’s what Lecinski’s framework points toward:
Execution-heavy roles will shrink. If a role is primarily about producing intermediate outputs, pulling data, drafting first versions, building reports, managing repetitive tasks expect those to contract as agents handle more of that work.
Orchestration roles will expand. You’ll need more people who can design hybrid workflows, supervise agents, define quality standards, connect functions, and translate strategy into operating rules an AI system can actually follow. This is a new skill set that barely existed two years ago.
Judgment roles become more critical. Brand stewardship, strategic interpretation, weighing trade-offs, protecting tone and quality, reading weak signals these expand in importance because they’re the things agents genuinely cannot do. The standard-bearer for creative vision and brand integrity becomes more valuable in an AI-heavy org, not less.
The move: Don’t redraw the full org chart. Pick one team where AI is already changing the work and redesign that team first. Ask four questions: Which responsibilities are becoming automated? Which roles are focused on coordinating human-AI workflows? Which workflows require stronger human strategic vision and judgment? What skills now distinguish a strong performer from an average one?
The answers will tell you more about your future org design than any framework can.
What This Means for Hiring (and It’s Not What You Expect)
If you’re still writing job descriptions for roles that were designed before agentic AI, you’re already behind on hiring.
Lecinski’s guidance here is specific and worth taking seriously. For early and mid-career candidates: ask them to show you an end-to-end fully automated AI workflow they’ve built. Not a prompt they’re proud of. A workflow they designed, deployed, and evaluated. Many recent MBA graduates now have this skill set as programs integrate AI into their marketing curricula.
For senior candidates: ask them to walk you through how they’d redesign and lead a real human-AI marketing workflow. Where would automation sit? Where should human judgment remain? What guardrails would they establish? How would they manage the team and measure results?
These questions immediately separate candidates who are talking about AI from candidates who are operating with it.
And for your existing team: quarterly AI training seminars don’t cut it anymore. Teams need clearer expectations about what good everyday hybrid performance actually looks like. They need career paths and performance evaluations that reflect AI orchestration, workflow supervision, and quality judgment not just traditional marketing outputs.
The Bigger Picture: Why This Is Now a CEO-Level Conversation
Here’s the business case framing you need if you’re taking this to the C-suite.
Marketing organizations that get this transition right will move faster, make better decisions, shorten cycle times, reduce rework, and scale best practices more consistently. They become more legible to the CFO because their operating model is cleaner and their results are more predictable.
Marketing organizations that don’t get this transition right will remain bottlenecked by human bandwidth, running AI on top of inefficient processes that were never designed for it, and watching their competitors close the gap on campaigns that used to take them months.
Lecinski’s framing of the CMO’s expanded role is the sharpest part of the entire piece: “The job is no longer only to drive demand today and build brand over time. Now frontier leaders must also shape the human-AI system through which modern marketing increasingly runs.”
That’s the job now. System architect, not just brand steward.
The Monday Morning Moves (Straight from the Research)
If you leave this piece with nothing else, leave with these three actions one per rewire:
For the work: Identify three to five high-frequency, high-value marketing workflows. Map every step end to end. Don’t rationalize why you don’t have time. The map is the prerequisite for everything that follows.
For human-AI collaboration: Take one mapped workflow and write down explicitly, for each stage, who commissions, who executes, who reviews, who approves, and what escalation looks like. Eliminate the ambiguity that’s generating anxiety and duplication in your team right now.
For the org: Pick one team where AI is visibly changing how work gets done. Run the four redesign questions on that team before touching anything else. Use it as your template and your proof of concept.
The Bottom Line
The gap in the McKinsey data is the business opportunity. 86% excited, 28% actually rewiring. That gap is where competitive advantage gets built or lost.
The organizations that handle this transition deliberately mapping workflows, defining human-AI hand offs with precision, redesigning roles for what the work actually requires will compound their advantage every quarter. They’ll run faster, waste less, and produce better outcomes with the same or smaller headcount.
The ones that keep layering AI onto 2019 org structures will eventually get there. But they’ll arrive late, having spent two years moving slowly while their more adaptive competitors redefined what a marketing organization can do.
The work is changing. The collaboration model is changing. The organization has to change too.
The only question is whether you’re leading that change or reacting to it.
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