The Execution Layer Is Collapsing
And AI is changing what kind of leader survives.
Before the main story, signals from the week point in the same direction.
OpenAI is moving Codex from developer tool to enterprise work layer. The latest update adds role-specific plugins for analytics, creative production, sales, product design, investing and banking, along with shareable “Sites” that turn work into dashboards, planners and lightweight apps. For marketers, the signal is important: AI is moving from answering questions to generating the actual workspaces, assets and decision tools teams use every day. More from OpenAI.
Anthropic’s Claude Opus 4.8 is pushing the model race toward agentic reliability, not just raw intelligence. The release improves coding, tool use, long-running workflows and model honesty, while adding effort controls and dynamic workflows that can coordinate many subagents on large tasks. The bigger point: the frontier model race is increasingly about whether AI can carry work through to completion with judgment, not just produce a strong first answer. More from Anthropic.
Google is turning search advertising into an AI conversation. Its new Gemini-built ad formats in Search include Conversational Discovery ads, Highlighted Answers, AI-powered Shopping ads and Business Agent for Leads, which puts a brand agent directly inside an ad. For marketers, this is another step away from keyword-first advertising and toward intent-rich, AI-mediated persuasion. More from Google.
AI Trailblazers is hosting Cannes Reworked on Monday, June 22nd, during the Cannes Creativity Festival. The closed-door summit will focus on creativity, workflows, and the AI-enabled marketing model, with leaders from JCPenney, Mastercard, U.S. Bank, Microsoft AI, Google, and others. Request an invitation and view the agenda and the speakers here.
Taken together, these stories point to the same underlying shift: AI is no longer just changing the tools marketers use. It is changing the shape of the work, the teams, and the leaders who will matter.
Preparing for Extinction?
AI is changing what kind of leader survives.
A roughly 6-to-9-mile-wide asteroid slammed into Earth near the Yucatán Peninsula 66 million years ago. It triggered a global impact winter, blocked sunlight, halted photosynthesis, cooled the planet rapidly, and set off fires, tsunamis, and acid rain. Roughly three-quarters of plant and animal species disappeared, including all non-avian dinosaurs.
The species that survived were different. They were smaller, more adaptable, more flexible in their diets, and often better able to live in or near water. Some could endure starvation. Some reproduced quickly. Some depended less on fresh plant matter and more on detritus-based food chains. They ate insects, seeds, roots, and carrion. Being nocturnal helped in a darker, colder world.
The lesson is not that small always beats big. It is that the traits that make you dominant in one environment can become liabilities when the environment changes suddenly. That is the part worth sitting with. Corporate America may be entering its own global winter. Not literally, of course, but we are in a period in which the assumptions sustaining careers, functions, titles, team structures, and leadership identities are changing faster than most people are prepared to admit.
And marketers may be more exposed than they realize. The AI story in marketing is no longer just about better tools or faster content. It is about the collapse of the execution layer. As AI takes on more production, coordination, synthesis, intelligence, memory and reporting work, the value shifts upward to orchestration, judgment, taste, governance, industry context, and commercial leadership.
The Job Market Is Already Telling Us Something
It seems like every few days there is another dispiriting report about the job market. Some early fears of an AI-driven job collapse may prove overstated. The honest answer is that none of us really knows.
But too much is changing at once to ignore the direction of travel. AI capability is improving rapidly. Agentic systems are becoming more practical. Companies are under pressure to do more with less. Senior roles are being combined. Management layers are being questioned. Teams are being rebuilt around fewer people, more technology, and the expectation that AI will become a direct collaborator rather than just a tool. A trend that began in Silicon Valley is now starting to spread across Corporate America.
Uber offers one example of this shift. The company reportedly cut a significant portion of its People and Places team while promoting Jill Hazelbaker into a broader role spanning HR, recruiting, real estate, marketing, communications, public policy, and safety operations. Uber says the cuts were not driven by AI. That may be true. But the organizational logic is hard to miss. Functions are being consolidated, leadership spans are expanding, and senior executives are being asked to manage increasingly broad portfolios.
OpenAI offers another example. Colin Fleming, one of the most accomplished B2B marketers in the country, joined the company as CMO, Business, a newly created role that reflects a growing divide between consumer and enterprise needs. Consumers want access, utility, delight, and affordability. Enterprise customers want trust, control, governance, privacy, and confidence that the technology can be deployed safely with sensitive data.
In one case, the executive span broadens. In the other, the role is redesigned around a new market reality. Both point to the same conclusion: the traditional org chart is becoming a less reliable guide to where leadership value sits.
That tension inside OpenAI is structural, not cosmetic. Trying to manage it with a single marketing leader and a single unified brand story would be the old playbook applied to a situation it was never designed for. Splitting the role may look messy from the outside, but it also reflects reality. That is not weakness. It is adaptation.
Fleming’s decision to step into this is particularly interesting. OpenAI is not a stable company with a finished operating model. It is a fast-moving organization under extraordinary scrutiny, facing intense competitive pressure, unresolved trust questions, significant financial obligations, and an operating model that could look very different a year from now. That is not comfortable. It is also where some of the most consequential work of this era is happening.
This is the new executive math: fewer people doing the work, more systems helping produce it, and greater pressure on leaders to orchestrate across increasing complexity with less organizational certainty beneath them.
Credentials Are Not a Survival Strategy
One of the harder parts of this moment is watching accomplished people navigate career uncertainty. When friends or peers ask for help finding their next role, I am often struck by how much of the story they tell about themselves is rooted in the world that got them here.
They talk about the brands they managed, the teams they led, the campaigns they launched, the budgets they oversaw, and the functions they built. All of that matters. But, unfortunately, it may not be enough.
The next opportunity will not simply reward people for having succeeded in the previous operating model. It will reward those who can prove they are ready for the next one.
This is not about age or seniority. Some of the most adaptive leaders I meet are very senior. Some of the least adaptive are much younger. The distinction is psychological and operational. Are you still defending the old model, or are you learning how to operate in the new one?
The Collapse of the Execution Layer
The reason this matters is that the execution layer of the organization is starting to collapse. Which tools should we use? How do we create more content? How do we help people write briefs faster, summarize research, generate ideas, personalize emails, build decks, and save time?
These are reasonable questions. They are also too small. They assume AI is primarily a way to help marketers do their existing jobs better. The copywriter becomes a faster copywriter. The strategist becomes a faster strategist. The team becomes more productive. The whole moment gets framed as another version of the digital marketing revolution.
That framing is useful, but increasingly incomplete.
Most corporate functions were built around the same architecture. There were people who set strategy, managed the process, coordinated stakeholders, created the work, reviewed it, routed it, reported on it, and turned all of it into slides. AI puts pressure on every one of those layers.
If AI can draft the brief, summarize the research, generate the first round of creative, write the email variants, build the presentation, synthesize the data, and recommend the next action, organizations need fewer people whose primary role is to produce, translate, route, and repackage work.
What they need more of is judgment. People who can frame the problem, define what good looks like, orchestrate the right systems, manage risk, evaluate the output, and connect the work to commercial outcomes.
That is why functions are collapsing into broader leadership portfolios. Not because the work disappears, but because the production layer becomes more automated and the remaining work shifts upward into orchestration.
Systems of Reasoning, Not Systems of Record
Most companies already have systems of record: CRMs, data warehouses, marketing automation systems, dashboards, research archives, and financial reporting. They have systems that store the facts of the business.
What they often lack are systems that help the organization think.
That is the bigger AI opportunity. The real value is not asking a model to write ten headlines. It is building systems of reasoning on top of systems of record. Systems that understand context, remember prior decisions, surface relevant history, connect strategy to execution, and make institutional learning usable in the moment work is happening.
Imagine a campaign planning process where the system can see the prior year’s brief, the creative rationale, the performance results, the customer research, the budget constraints, the legal issues, the sales feedback, and the executive decisions that shaped the work. Imagine if it could then help a team reason through what should be repeated, what should be challenged, what assumptions have changed, and what risks need to be considered.
In that world, the advantage does not come from having more people chasing more information across more meetings. It comes from giving a smaller number of people better memory, better context, and better decision support.
That is very different from one-off productivity. It is the compounding of organizational intelligence. AI changes how organizations think, create, remember, decide, and act. That is why this moment is different.
The New Leaders May Come From Anywhere
Lasherelle Morgan, SVP of AI Innovation and Acceleration at NBCUniversal, is a good example. She grew up in legal and now leads AI innovation across the company. That matters because the AI era does not only reward the person closest to the technology. It rewards the person who can move across risk, governance, workflow, brand, consumer trust, and business strategy.
Her work also points to a more mature view of AI governance. Governance should enable AI use, not block it. The right guardrails help people move faster without going off track. The smartest leaders start with the workflow, not the tool. They map the process, identify where AI can add leverage, and focus review on higher-risk use cases with meaningful legal, business, brand, or consumer implications.
That is what new AI leadership looks like. Not functional purity. Not title preservation. The willingness to take on new responsibilities because the work itself is moving.
What the Marketer Has to Become
It is not enough to be a marketer anymore.
That may sound harsh, especially from someone who has spent much of his career in marketing, written books on marketing, and still believes deeply in the function. But I think it is true.
To thrive as a marketer in 2026 and beyond, core marketing skills need to be complemented by five fluencies that would have felt peripheral just a few years ago.
The first is industry fluency — you need to understand how your category actually works, not just how to market within it. If you are a CPG marketer, that means understanding inventory, store operations, retail media, merchandising, margins, loyalty economics, and channel conflict. If you are in financial services, it means understanding regulation, compliance, risk, FICO scores, and the emotional dimensions of money. If you are in healthcare, it means understanding reimbursement, patient journeys, providers, payers, and the ethics of communication. For years, marketers told themselves that skill was portable. There is still truth in that. But AI is changing the equation. Generic marketing expertise is becoming easier to access by the day, while deep contextual judgment is becoming more valuable and more differentiated.
The second is AI fluency — you need to understand AI as a workflow engine and an emerging labor force, not a writing assistant. It means knowing how agents can be built, deployed, governed, and evaluated. It means understanding how AI changes briefs, approvals, research, media planning, creative development, campaign execution, and reporting. Many marketers are still using AI as a personal assistant when they need to learn how to build with it. The future marketing leader cannot only orchestrate work through people and agencies. They need to become comfortable building agentic systems, testing workflows, and leading combined human and AI teams.
The third is taste fluency, you need taste because AI is about to make competent average work abundant. As AI floods organizations with competent, polished, average work, someone has to know what is worth making. What feels true, what feels borrowed, what feels culturally alive, what feels strategically sharp, and what feels like a slightly better-formatted version of the past. You cannot outsource that. If you are asked a question in a leadership meeting, the answer cannot always be something you text your agency contact to get or your ChatGPT instance to generate. You need your own point of view, your own cultural read, your own sense of what the brand should and should not do. AI is already good at producing plausible work. The leader’s job is to prevent plausible work from becoming the standard.
The fourth is commercial systems fluency — you need to understand how the business sells, serves, distributes, partners, and makes money. In B2B, this means being genuinely close to sales: the pipeline, the buying committee, the sales cycle, the objections, the procurement process, and the economics of the deal. In consumer businesses, it means getting closer to channels, retailers, marketplaces, distributors, and supply chain relationships. The customer promise often depends on realities that sit well outside the traditional boundaries of marketing.
The fifth is financial fluency — you need enough financial fluency that the CFO would want you in an investor meeting. Not to show a campaign reel. Not to talk about impressions or brand love. But because you can explain growth, demand, how customer behavior is changing, how AI is improving the operating model, where the company has advantage, and where it is exposed.
That is a different kind of marketing leader. More commercial. More technical. More operational. More strategic. And ultimately, more valuable.
Resistance Is Rational
For every vocal AI advocate inside an organization, there are many more skeptics. Some are quiet. Some say the right things publicly and resist privately. Some are curious but overwhelmed. Some are worried about their teams. Some are worried about themselves.
Their concerns are not irrational. People are worried about becoming less relevant precisely when they have finally figured out how to do marketing well. They are being asked to learn new tools, build new relationships, take on new roles, let go of certain partners, and bring on new ones. That is a lot.
It is also why AI transformation cannot be treated as a software rollout. It is a human transformation. People do not need another generic prompt training session. They need to understand how their function is changing, how their role may evolve, what capabilities they need to build, and how they can remain valuable in a system where intelligence is increasingly shared between people and machines.
Preparing for Survival
Marketing has already lived through several professional extinction events. Digital changed distribution. Search changed intent. Social changed participation. Mobile changed behavior. Programmatic changed media buying. Each wave created new leaders and left others behind.
AI is different because it does not just change channels or formats. It changes cognition inside the company. How ideas are generated. How work is coordinated. How decisions are supported. How knowledge is retrieved. How execution happens.
This is not digital marketing again. Not social media again. Not programmatic again. Those transformations mostly changed the architecture of attention, distribution, data, and measurement. AI changes how organizations think, create, remember, decide, and act.
That is why this moment feels less like a new channel and more like a global winter.
So what does it take to thrive? Not certainty. There is too much we do not know. But the traits that matter are becoming clearer: adaptability over credentials, industry depth over generic expertise, AI fluency over AI enthusiasm, taste over output, systems thinking over tool usage, commercial understanding over functional purity, ecosystem management over agency management, and executive presence over marketing performance theater.
The future belongs to marketers who can become broader without becoming shallow, more technical without losing humanity, more commercial without losing creativity, and more operational without losing imagination.
Colin Fleming stepping into OpenAI is not a cautionary tale. It is a case study in the posture this moment demands. The job is messy. The org chart is unusual. The odds are not obvious. He took it anyway.
The dinosaurs did not disappear because they were unimpressive. They disappeared because the world they were built for no longer existed.
That is the question every marketer should be sitting with now.
Am I built for the world that existed, or am I adapting to the one that has just been hit by an asteroid?
Where I’ll be
Next week, I’ll be speaking at the Financial Times Board Summit in New York, where these questions will continue to be front and center. From there, I’ll head to the Cannes Lions International Festival of Creativity for three distinct speaking engagements while also participating in sessions myself.
On Monday, June 22nd, I’ll be hosting the Cannes Reworked Summit. We have some of the smartest leaders in marketing and technology coming together for a serious conversation on where AI is taking business. I’ll also be sharing my mid-year Marketing with AI trends from that stage. Click the link to view the speakers, agenda, and request an invitation.
I’ll also be joining Agents, Signals, and the Self-Driving Funnel, a Brand Innovators panel with Susan Grossman, Executive Vice President, Consumer Acquisition and Engagement at Mastercard; Elav Horwitz, Chief Innovation Officer at WPP; and Lindsey Slaby, Founder of Sunday Dinner. The panel will be moderated by Isabel Perry, EVP, Global Strategy at DEPT, and will take place on Wednesday, June 24th.
And finally, also on Wednesday, I’ll be joining Winning The AI Discovery Era: Marketing to Minds and Machines, a LinkedIn official Cannes programming panel on AI discovery with Jessica Jensen, Chief Marketing Officer of LinkedIn; Denise Dresser, Chief Revenue Officer at OpenAI; and Carla Hassan, Chief Marketing Officer of JPMC.
What I’ve written lately
The End of the Segment (May 2026)
When Intelligence Enters the Org Chart (May 2026)
A Public Company Goes All In on AI (April 2026)
AI Is Rewriting Who Decides (March 2026)
Shiv Singh is the CEO of Savvy Matters, which helps business teams translate AI disruption into practical business and marketing strategies, organizational design, executive-ready roadmaps, and bespoke education programs. He is also the Co-Founder of AI Trailblazers, a vibrant community uniting marketers, technologists, entrepreneurs, and venture capitalists at the forefront of AI.
A former two-time Chief Marketing & Customer Experience Officer and author of Marketing with AI for Dummies (4th print run, translated into five languages), Shiv built his career at LendingTree, Visa, PepsiCo, and The Expedia Group, and serves as a public-company board member of a Fortune 300 company and private investor.
Excellent post. Timely and one of your best!