OpenAI’s hiring of ServiceNow CMO Colin Fleming to lead its business marketing signals a clear intent: The company plans to compete as a leading enterprise platform and establish a brand on par with the top global technology and services firms.
Fleming joins OpenAI after serving for two years as CMO at ServiceNow; before that, he spent more than a decade at Salesforce, where he rose to executive vice president of global marketing. At both companies, he built a reputation for moving B2B marketing away from safe lead-gen content. He focused instead on narrative campaigns that felt cinematic, human and, at times, deliberately provocative.
The growing presence of AI in marketing has upped the ante even more. In a recent exchange about how AI is changing the CMO’s job, Fleming told me, “AI can move average work faster, so the standard has to go up. Clarity. Taste. Specificity. Discipline.”
Although he called leaving ServiceNow “gut-wrenching,” Fleming is clearly excited about his move to the company that launched the AI boom in 2022. OpenAI’s leadership has made 2026 its pivotal year for prioritizing enterprise, emphasizing that the company’s core challenge is solving for application and product use — not continued model training.
In that context, Fleming’s priority is to translate OpenAI’s advanced research and product plans into a clear enterprise narrative ready for boardroom scrutiny, elevating the brand among the world’s top technology and service leaders. Fleming described the assignment to me as “help[ing] set the standard for putting AI to work safely, usefully and at scale.
The CMO’s recent work at ServiceNow gives an insight into the marketing muscle OpenAI is bringing onboard. Under Fleming, ServiceNow adopted a more opinionated voice on AI. One example: a Wall Street Journal campaign that used satire and future-tense storytelling to pose a serious question. What happens when AI agents make decisions faster than organizations can govern them? The full-page, memo-style ad, written from agents to humans, reframed agents not as magic, but as systems requiring explicit governance and accountability. The message was clear: Enterprises must explain, audit and own their decisions.
When I asked what he wanted that campaign to do, Fleming said the point was “to make the risk feel real.” As AI agents begin to sense, decide and act, he told me, “Governance cannot stay abstract. It has to show up in the work.”
OpenAI has already begun to reorient its enterprise strategy around independent distribution, custom enterprise-grade models and AI agents that sit on top of existing systems. It has also been explicit that its next phase is about high-value professional work and practical deployment — not just general chat interfaces — in areas such as customer service, IT and operations.
For CIOs and technology leaders, Fleming’s appointment suggests that a sharper, more opinionated story is coming, one that connects models and agents to specific workflows, governance patterns and business outcomes. When I asked how trust fits into that, he pushed back on the idea of treating it as a one-off theme: “Trust is earned across the whole experience: product, deployment, security review, documentation, customer proof and every conversation with the people responsible for putting AI into production,” he said. “So, yes, it is product and narrative. Product has to carry the truth. Narrative has to make it clear.”
Based on my conversation with Fleming, I believe that story will show up not only in campaigns, but also in how OpenAI packages its business offerings, how it frames value-based or outcome-based pricing for agents and how closely marketing is tied to sales, customer success and partner motions in the field. As enterprises weigh whether intelligence lives in their cloud, their systems of record, their collaboration stack or a new intelligence layer, OpenAI is clearly positioning itself as a contender to own more of that conversation within the C-suite.
Inside the company, Fleming argues, the marketing function itself has to change in kind. He said that it has to become “AI‑native” — with “faster learning, better sensing, less friction. More clarity. More specific work for more specific audiences.” OpenAI, in his view, “should not simply sound like the next enterprise software company.”
The important work, he said, will now be turning OpenAI’s high brand awareness into confidence among buyers. Fleming framed his team’s task as giving enterprises evidence that decision‑makers can take to their board. “People know the product. They feel the pace. They understand that the technology is powerful,” he said. “The enterprise [marketing] job is to turn that awareness into confidence, confidence into adoption, and adoption into proof. Our best sales tool should have the customer’s name on it.”
This move is also a signal to other CMOs. Fleming has been vocal about the limits of generic B2B storytelling, arguing that brands need a distinct point of view and a willingness to say something that not everyone will agree with. When I asked him what single mindset shift B2B marketing leaders need to make in this new era, he didn’t start with AI features, but with learning and curiosity. “AI changes how fast teams can learn,” he told me. “It lowers the cost of trying things, testing ideas, seeing patterns and improving the work. But speed only matters if the questions get better.”
His campaigns at Salesforce and ServiceNow put story before product specs. They started with human stakes and cultural context, then led audiences back to platforms and products.
In today’s rapid buildout of AI, that discipline becomes non-negotiable. Buyers are flooded with similar promises about copilots and agents, while employees and regulators are asking hard questions about trust, transparency and control. The lesson for CMOs is that credible AI narratives require emotion and clarity, paired with an honest treatment of risk, governance and accountability.
When we discussed how B2B buying actually happens, Fleming brought it back to humanity and curiosity. “B2B buying is still human,” he said. “People bring pressure, ambition, doubt, budget and risk into the room. Curiosity is how you understand that room. It is how you build something worth trusting.”
OpenAI’s deeper enterprise engagement will test its closest partners first. Microsoft has tied its Copilot strategy and parts of Azure’s AI portfolio tightly to OpenAI’s models, even as both organizations court many of the same global accounts. Meanwhile, Zoom and other collaboration providers that use OpenAI are embedding generative features into their own products and, in some cases, partnering with workflow platforms like ServiceNow to deliver AI-enhanced experiences.
As OpenAI builds a stronger business-facing brand and experiments with new ways to package and price its platform, these partners will need to sharpen how they explain their own differentiated value, whether that is in distribution, vertical depth, compliance frameworks or the workflows and records systems that ultimately govern AI decisions. Direct rivals such as Anthropic and Google, which have leaned into safety, control and integration as core enterprise messages, are likely to respond by investing more heavily in their own front-of-house storytelling in addition to their model benchmarks.
All of this is unfolding while OpenAI itself faces scrutiny over safety, concentration of power and long-term vendor stability, which makes Fleming’s narrative work around agents and accountability more than a branding exercise. In this next phase of enterprise AI, technology, governance and narrative will rise or fall together. The brands that endure will be the ones that are best able to explain, with conviction and evidence, what agents are for, who governs them and how they affect work — and that help customers understand, control and trust those systems. That is OpenAI’s opportunity, and that it why it identified Fleming as the right person for the job.
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