Future of Work
Last week, I attended an executive forum hosted by Marketing AI Pulse featuring Julie Lowrie, Partner at McKinsey & Company. The topic was AI in marketing — strategy to execution.
The value of a session like this isn’t always the new information. Sometimes it’s the confirmation that the patterns you’ve been seeing are real, that others with very different vantage points are arriving at similar conclusions. That’s what this session gave me.
Here’s what stood out — and what I think it means for leaders, whether or not you’re in marketing.
The Leader Shaping AI Adoption Across Your Organization Might Be Your CMO
Marketing has become the proving ground for AI inside most organizations.
The reason is simple: marketing use cases are measurable. Campaigns, personalization, content, customer insights, sales enablement — all of it produces visible results fast enough to justify the next investment. That gets AI use cases approved in marketing before almost anywhere else. (mckinsey)
I expected the conversation to center on C-suite leadership. What I hadn’t fully considered was the specific reach the CMO has, or should have, right now. The CMO isn’t just an early adopter of AI. They’re positioned to shape how it moves through the entire organization.
The role of the CMO is expanding from steward of brand and demand to the orchestrator of data, technology, and AI-enabled execution. In practice, that means the CMO who is running agentic content workflows today is also the one setting the template for how other functions will eventually adopt them. They’re the ones negotiating data access across silos, defining what good human-AI collaboration looks like, and building the case with real numbers for where AI investment should go next. The marketers who will stand out are the ones who know how to combine AI’s speed and scale with uniquely human strategy, creativity, and leadership and who have enough technical fluency to lead across functions and ask harder questions about what actually needs to change. (mckinsey) (northwestern)
Pilots Are Not a Strategy.
Nearly 90 percent of CMOs are experimenting with AI use cases across various points of the marketing process, but less than 10 percent have captured value across end-to-end workflows. (mckinsey)
Point to almost any organization struggling to capture value from AI and you’ll find the same culprit. Pilots. And pilots have a default setting: efficiency. Save time. Cut cost. Automate the repetitive work. Those are reasonable goals. They are not transformation.
Realizing AI’s potential requires reimagining and rebuilding workflows, not layering new tools onto old processes. That requires a different question than most leadership teams are asking: Where are we losing ground to competitors because our people are buried in work that AI could handle, and what would they build if they weren’t? (mckinsey)
Efficiency is a floor, not a ceiling. When every competitor has access to the same AI tools, and they do, operational efficiency stops being an advantage. It becomes the price of admission.
The organizations that will pull ahead aren’t winning on efficiency. They’re winning because they freed up the human capacity that was buried in repetitive work and redirected it toward the one thing competitors can’t easily copy: customer experience. Not just good experiences, the kind that make a company a household name. Consistent, reliable, aligned, and transparent at every touchpoint. The solution itself can be replicated. The messaging can be replicated. But the experience a customer has when they interact with your brand and the trust that builds over time. That is something that has to be designed into an organization as part of the transformation.
If AI is fundamentally changing what people are capable of and what they should be focused on, then the organization built around the old version of that work is already obsolete. The structures, the roles, the reporting lines, the assumptions baked into how decisions get made — all of it was designed for a world where human time was the scarce resource and repetitive execution was the job. That world is gone. The leaders who recognize that aren’t asking how to fit AI into their existing organization. They’re asking what kind of organization they need to build now.
The Org Chart Hasn’t Changed. The Work Has. That’s the Problem.
During the session, Julie talked about how marketing and sales are working more closely together, how CMOs need to become genuinely tech savvy, and how the changing nature of brand discovery — the shift toward AI-powered search and a world where stories and earned media matter more than ever — is pulling marketing and PR into ongoing collaboration.
That’s a lot of different moving parts.
During Q&A, I asked: Is this actually changing how organizations are structured?
Her reply was that teams are coming together around projects, but the reporting structure hasn’t changed.
I’ll be direct about my reaction to that. It sounds exhausting and stressful.
People are being asked to work in fundamentally new ways, across functions that have their own goals, their own leadership, and their own priorities, without any of the structural support that would make that collaboration sustainable. When that shift happens organically, without design or intention, opportunities get lost. Teams slip back and forth between outdated ways of working and new ones that don’t yet have the support structure around them. The result is confusion, friction, and momentum that stalls right when it should be accelerating.
The Competitive Advantage Was Never the Technology.
The session covered a lot of ground on where AI-powered commerce is heading, from generative search to agentic buying to what’s being called autonomous commerce on the horizon.
The technology can increasingly be found everywhere, except on the bottom line. The data backs that up. MIT found that 95% of AI pilots deliver zero measurable P&L impact. Only 29% of organizations see significant ROI from generative AI, despite individual productivity gains of up to five times. The wins are real at the individual level. They are not translating to the organization.
The irony is that the two problems feed each other. Organizations are struggling to capture ROI because they haven’t changed how they work. And while they’re busy running pilots and measuring individual productivity gains, the technology itself is commoditizing. By the time most organizations figure out how to capture real value from the tools they have today, every competitor will have access to the same ones. The advantage was never going to come from the technology. It was always going to come from what the organization was capable of doing with it.
If the technology is a commodity, it can’t be your edge.
AI raises the floor by making high-quality analysis and first drafts accessible to more people. It raises the ceiling by enabling the best leaders to move faster, explore more options, and spend more time on judgment and strategy. The organizations that pull ahead will be the ones that use that ceiling wisely, investing in the human capacity, the leadership culture, and the organizational design that technology can enable but never replace. (northwestern)
What I’m Still Thinking About
I didn’t leave the session thinking about AI.
I left thinking about the assumptions underneath it.
The assumption that efficiency is a strategy. The assumption that transformation starts with technology. The assumption that changing the org chart changes the organization. The assumption that being a large company means you’ll figure it out in time.
Every one of those is getting tested right now, not in theory, but in the competitive pressure leaders are already feeling in their numbers.
The future won’t reward yesterday’s playbook.
It will reward the leaders who are willing to question the assumptions that made them successful. The ones who stop asking how to adopt AI and start asking what kind of organization they need to become. That’s a harder conversation. It’s also the only one that matters right now.
This is the work I do with leadership teams — helping organizations move from assumption to action, and from pilots to transformation. If any of this is landing close to home, find me at amplifiedconcepts.com.
