marketing leadership

One of the CEOs I spoke with wanted a CMO who could walk into a board meeting and make a credible case for where the market was heading: what customers were telling them, what was changing around those customers, what it could mean for the business, and what the company should consider doing next.

A couple of CEOs asked me recently what to look for in a CMO now, given what AI is making possible.

I spent years leading marketing. My work since then with CMOs and GTM teams, founders, leadership teams, and PE and VC partners has given me a view of what AI is changing in the role and what companies increasingly expect.

Three areas consistently come up: knowing the customer and market at a depth that wasn’t practical before, leading brand and trust across the company, and carrying customer context across the GTM journey.

Quick Take

What connects these three areas for me is an outside-in view of the business, starting with the customer and market rather than the marketing function.

• Know the customer and market at a depth that wasn’t practical before – AI can connect signals teams couldn’t reasonably track at the same scale or timing.
• Lead brand and trust across the company – AI brings customer, employee, leadership, community, and company signals into the same view.
• Carry customer context across the GTM journey – AI can connect context across Marketing, Sales, and CS and help close the gaps customers experience.
• Bring people through the change – The CMO still has to build trust, influence across functions, and help teams change how they work.
• Connect all of this to business and financial outcomes – A broader view of the customer, market, company, and customer journey gives the CMO more to bring to business decisions.

These are observations from current work and conversations, rather than a best- practice model.

Watch Or Listen Instead

This newsletter is also available in two additional formats for different learning styles. The 6-min cinematic AI video explainer is a broad overview of the argument. The 18-min AI podcast goes deeper. Both were made with Gemini Notebook and personally reviewed for accuracy and responsible AI use.

What Experience Gives Us

Experience builds judgment. You’ve seen enough situations to recognize patterns, ask better questions, and identify problems earlier. That experience is useful, but it can also make us rely too heavily on what worked before.

CMOs have always been expected to understand customers, earn trust, know the business, and work across the leadership team. AI is making more of that practical at a scale and cadence that were hard before: working across far more customer and market information, helping teams rethink workflows, roles, handoffs, and the customer journey.

Katy Keim has lived the CMO-to-CEO path more than once. She was CMO at Lithium Technologies and EVP of Marketing at ServiceSource before becoming CEO of LQ Digital and most recently LeanData.

“I’ve been in the CMO seat, and I know how easy it is to default to what worked before. The leaders who stand out aren’t running a playbook. They’re curious. They’re learning from their peers, picking up new signals from the market, and connecting it all back to the customer. It’s about pattern recognition from their experience, not stale tactics. This market demands a new growth mindset from marketing leaders.”

In my work, three areas show how AI can make this broader CMO role more practical:

1. Know the Customer and Market at a Depth that Wasn’t Practical Before

AI lets us bring together more customer and market information, more often, then connect signals that would otherwise stay separate.

A few examples I’m seeing:

• Bring more customer signals together – Usage, support tickets, call notes, engagement, renewal history, and other internal data can be analyzed alongside public information such as funding, acquisitions, leadership changes, or industry news. Declining engagement and usage mean something different when they happen alongside a leadership change. An acquisition may signal an expansion opportunity.
• Keep market and competitive intelligence current – AI can watch competitor positioning, pricing, reviews, category conversations, analyst commentary, and the language buyers use. Teams can move from periodic competitive updates to a much more current view. I’ve found this to be one of the clearest examples of work an all-human team couldn’t keep up with at the same cadence.
• Pressure-test decisions with simulated buyers – Before a pricing change, repositioning, or campaign, teams can build AI advisors trained on what they know about buyer priorities, challenges, roles, objections, communication styles, and sources they trust. They use them to challenge the thinking before it lands in market.

Human judgment stays central. AI handles collection, synthesis, analysis, and scale. People decide what applies, where the AI may be wrong, and what the business should do.

That gives the CMO a richer view of customers and the market to bring into product, GTM, strategy, and board conversations. I went deeper on several of these workflows in 5 Reimagined Workflows: Work We Skipped That AI Now Does.

2. Lead Brand and Trust Across the Company

Brand is what people experience and say about a company.

Marketing contributes to that experience. So do Product, Sales, Customer Success, HR, leadership, partners, and employees.

AI makes those connections easier for people outside the company to see. Ask an AI to search about a company and it can pull from the website, customer reviews, analyst coverage, community conversations, press, employee experiences, and other public information. Buyers increasingly get a full view assembled from many sources, not just the story marketing publishes.

That gives the CMO a broader leadership opportunity: help the company understand what those experiences add up to, where they reinforce the brand promise, and where they don’t.

Anna Griffin has led brands across complex enterprise environments including CA Technologies, Smartsheet, Intercom, and now Commvault. Her experience spans the parts of the company that create the brand and the people outside it who ultimately decide what to believe.

“Brand has never been what you say about yourself. It’s what every customer, employee, partner, and prospect experiences and says about you. That’s always been true. What AI has done is make it visible all at once, at scale, in ways that are very hard to ignore. You either build it intentionally across the whole company, or the market and AI build it for you.”

A few ways I’m seeing this show up in the work with AI:

• Look at the company from the outside in – Search as a buyer, customer, candidate, or partner. Look at the situations they’re in, the problems they’re trying to solve, what they hear about you, and where the story feels unclear or inconsistent.
• Be useful and honest about where you fit – Create content around customer situations, questions, and outcomes rather than leading with features and capabilities. Be clear about who you’re ideal for, where you’re not, and what customers actually achieved. That gives people and AI clearer evidence about when to recommend you.
• Find gaps marketing can’t close alone – If the brand promises “easy to work with” but onboarding is painful, that requires work with the team responsible for onboarding. If the company talks about transparency while candidates experience something different, changing the careers page only fixes one part of the problem.

AI search is part of this too: make owned properties clear, create useful content, structure information so machines can understand it, and monitor how AI represents the company. I went deeper on this outside-in view in When AI Judges Your Brand Before Humans Do.

But AI is also picking up experiences marketing doesn’t control. I saw a post recently where a job candidate asked for the salary range before an interview. The CEO responded that if money was their main driver, they weren’t the right fit. I wondered how that same CEO would respond if a buyer asked for a price range before agreeing to a sales call.

Marketing has been trying to explain what brand is for years. AI search may have just shown it for us.

Anna also uses a phrase I like: brand is rented, not owned. You keep earning it through the experiences people have with you and the evidence those experiences leave behind.

3. Carry Customer Context Across the GTM Journey

Customers experience one company, even though we organize ourselves into Marketing, Sales, and Customer Success. They experience the marketing, sales conversation, handoff, onboarding, product, support, renewal, and everything between.

AI is particularly useful here because it can carry context from one part of that journey to another.

There’s also evidence that AI can help people work across those boundaries. A Harvard-led field study with P&G professionals found that AI helped commercial and R&D specialists produce more balanced solutions that drew on both areas of expertise. Wharton professor and AI researcher Ethan Mollick described the result this way: “The distinction between specialists virtually disappeared in AI-aided conditions.”

The harder part is getting people to trust new inputs, change workflows, and reconsider practices that have worked for years. A sales leader may trust instinct built over decades. A CS leader may trust the data their team already uses. The CMO has to bring people along through real work, shared wins, and clear human judgment.

• Carry context across the customer journey – AI can look across calls, CRM notes, onboarding feedback, support tickets, usage, and renewal data so the customer’s story doesn’t keep restarting as they move between teams.
• Find where the experience breaks – Something showing up as a CS problem may have started with expectations set during the sales process. An adoption problem may trace back to positioning or onboarding. AI makes those connections easier to see.
• Work toward shared customer outcomes – When I ask Marketing, Sales, and CS what success looks like for the same customer, the answers come back as functional metrics: qualified leads, sales-cycle length, churn. Then we ask what result the customer needs from all three, such as time to first value, adoption, satisfaction, retention, or expansion. The conversation changes.

I explored what this could look like organizationally in No Daylight: How AI is Reorganizing GTM Teams Around Customers, Not Departments.

Changing shared goals, workflows, and long-standing ways of working still requires trust between leaders and compassion for the people doing the work. Some people move quickly with AI. Others need more time, support, practice, or evidence.

AI can help connect the work. Leaders still have to bring people along.

What This Adds Up To

CMOs are also being held more accountable for the results of the business. In the Spring 2025 CMO Survey, 63% reported increased pressure from the CFO and 61% from the CEO to prove marketing’s value. IBM’s 2025 CMO Study found that 64% of CMOs globally are accountable for profitability and 53% for revenue growth.

That requires connecting what customers experience and what GTM does to the economics of the business.

I often start with time to value, customer satisfaction, and net revenue retention because they begin with outcomes the customer experiences. From there, we use the company’s data to connect those outcomes to adoption, retention, expansion, referrals, payback, efficiency, and growth. That’s a more useful board conversation than trying to force every dollar of revenue back to a marketing touch.

Kate Bullis, Global Marketing Practice Leader at ZRG, runs 20 to 25 executive marketing searches a year and sees firsthand how the hiring conversation is changing.

“The most successful GTM leaders aren’t just functional experts; they’re business leaders who think like GMs. CEOs are expecting GTM to show up this way. Great GTM leaders optimize entire customer and market experiences, not just their department, because they understand customers don’t care about your org chart. The importance of this is not new, but AI has made it increasingly important.”

Much of this broader role depends on influence. Product, Sales, CS, HR, Finance, and other leaders bring expertise and accountability of their own. The CMO earns influence by bringing something useful to the table: customer intelligence that changes a decision, a clearer view of the market, a gap in the customer experience, or evidence that connects the work to the business.

The company has a role too. Some leadership teams want the CMO operating this broadly; others have a different mandate. Company stage, business model, goals, and leadership relationships will affect what makes sense.

Some CMOs will want to stay focused on leading the marketing function, and some companies will continue to want that. A more functional role brings clearer boundaries and deeper focus within marketing, but potentially less influence over the customer experience, market decisions, and business outcomes beyond the function.

The broader role comes with tradeoffs too: more shared ownership, more influence without direct authority, and more accountability for outcomes the CMO may not fully control. If CEOs want that kind of business leader, the mandate, measures, decision rights, and relationships around the role need to support it.

Both sides have to want the broader version. It takes two to tango.

A Few Questions Worth Asking

If I were advising those CEOs today, these are some of the questions I’d suggest they ask:

1. What’s a playbook you believed in that you no longer use? What evidence changed your mind?
2. Tell me something AI helped you see about customers or the market that changed a business decision.
3. Describe a cross-functional change that required people to work differently. How did you bring them along?
4. Walk me through a time AI helped you connect a customer or GTM issue to a financial outcome. What did you do with that insight?

I’d pay as much attention to the follow-ups as the first answer. Can they get into the actual work, explain what AI helped them see or do, where it fell short, what they changed, and what they learned?

Nobody has all the right answers yet. I’d look for intellectual humility, curiosity, ability to bring people through change cross-functionally, and evidence that they’re learning from real work. That can be hard at this level because we’ve spent our careers being rewarded for what we know and what has worked before. AI keeps asking us to question both.

I’m still learning with the leaders and teams working through this. What I see so far is an opportunity for a broader business role, with deeper accountability for customers, the market, the company experience, and business outcomes.

For CMOs, the question is whether that’s the role you want to grow into, and whether you understand what comes with it.

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