Expert Mode: The New CMO-CIO Alliance: Navigating the AI Frontier Without Fracturing the Org Chart
This article was based on the interview with Renu Upadhyay, SVP & CMO at Omnissa by Greg Kihlström, AI and MarTech keynote speaker for The Agile Brand with Greg Kihlström podcast. Listen to the original episode here:
The greatest risk to your AI marketing strategy isn’t the technology, the data, or even the competition. It’s the fault line running directly between your marketing department and your IT organization. For years, we’ve talked about agility, but the current wave of generative AI demands something more profound: a framework of collaborative trust. Marketing teams are, rightly, adopting powerful, often low-code tools at an astonishing pace to drive results. This velocity, however, creates a vortex of new complexities and risks, disrupting traditional processes and challenging established governance. The old “service desk” model, where marketing submits a ticket and IT eventually delivers a solution, is not just inefficient; it’s a liability.
Success in this new era is no longer measured by the sophistication of your martech stack alone. It’s measured by the strength of the strategic partnership between the CMO and the CIO. This alliance is the bedrock upon which innovation and governance, productivity and security, can coexist and thrive. To navigate this critical tension, we need to move beyond tactical requests and build a shared operational language. Based on a recent conversation with Renu Upadhye, Chief Marketing Officer at Omnissa—a leader with a unique background spanning engineering, product, and marketing—we can map out a new path forward. Her perspective offers a clear-eyed view on how to transform this internal friction into a powerful, strategic advantage.
The Catalyst: It’s Not Just AI, It’s the Speed of AI
The relationship between marketing and IT has always been a necessary one, but the urgency for a true partnership has never been greater. The single biggest catalyst forcing this evolution is not the existence of AI, but its sheer, unadulterated speed—the velocity of its development and, more importantly, its accessibility. This isn’t a slow-moving enterprise technology rollout; it’s a consumer-grade revolution happening inside the enterprise walls, and marketing is on the front lines. Renu points out that this acceleration is fundamentally reshaping the buyer’s journey, forcing marketing to adapt in real-time or risk becoming irrelevant.
“The biggest catalyst for this change, honestly, is the speed at which this is happening. The speed at which AI is accessible to everybody and therefore how do you leverage it appropriately is a question that both CMOs and CIOs are grappling with at the same time… Marketing is moving, like you said, at the speed of AI. Sometimes faster than the governance, the processes, the operational models, you know, all of that for an organization has been able to keep up with.”
This speed creates a dilemma. Marketing leaders are under immense pressure to innovate, personalize, and drive pipeline more efficiently. AI offers a tantalizing solution. A recent Mayfield Fund survey Renu shared underscores this, finding that line-of-business leaders, like CMOs, are now the largest decision-making group (46%) for AI tool adoption. This is a significant power shift. However, as she wisely notes, no marketing tool exists in a vacuum. Every new AI-powered platform, from a content generator to a lead scoring engine, must eventually connect to the core enterprise IT infrastructure. Ignoring this reality is a recipe for security vulnerabilities, data silos, and technical debt that will eventually cripple the very agility you seek. The first step toward a solution is acknowledging this shared pressure and the shared ownership that must follow.
Reframing Shadow IT: From Threat to Business Signal
For many CIOs and CISOs, the term “shadow IT” conjures images of rogue actors and unchecked security risks. In the age of low-code and SaaS, marketing departments have often been the primary culprits. But it’s time for a more sophisticated conversation. The proliferation of unsanctioned tools isn’t born from malicious intent; it’s a direct symptom of the business trying to solve a problem faster than the official channels allow. As Renu explains, this phenomenon has a long history, but its current acceleration requires a new response.
“Shadow IT isn’t intentional. It’s the line of business, you know, marketing trying to accomplish a business outcome, for which they’re leveraging this technology… My goal is, sure, I want to try, but my goal is to truly realize the value at scale. So how can I build the right guardrails infrastructure in place up front? At Omnissa… we established an AI council… to really start to put a process in place so we can have these dialogues from the get go, before we go too far down the road and then it’s back to that shadow IT.”
Instead of playing a perpetual game of whack-a-mole, leaders on both sides of the aisle should view these instances as valuable signals. When a marketing team spins up a new tool, it’s a data point indicating an unmet need or a cumbersome process. The enlightened CMO doesn’t hide these experiments; they bring them to their IT counterparts as a conversation starter: “My team is using this because we need to solve X. How can we do this safely and at scale?” This approach transforms the dynamic from adversarial to collaborative. Renu’s example of establishing an AI Council—a cross-functional group including risk, privacy, IT, and business leaders—is a brilliant, practical model. It creates a formal, proactive forum to evaluate tools and establish guardrails before they become entrenched problems, allowing innovation to flourish within a safe, scalable framework.
The Human Element: Upskilling and Augmenting for an AI-Powered Future
Technology is only one part of the equation. The most sophisticated AI tools are useless without a team that has the skills and mindset to leverage them effectively. This rapid technological shift is fundamentally changing the roles and responsibilities within our marketing organizations. It’s not about replacing marketers with machines; it’s about augmenting their intelligence and freeing them from rote tasks to focus on strategy, creativity, and customer understanding. For marketing leaders, this requires a dual-pronged approach to talent development.
“It’s making sure the current teams are ready for this and investing in that, and then also complementing and augmenting when needed through these external skills.”
First is the critical task of upskilling. Renu emphasizes the need to build “AI literacy” across the entire team. This isn’t about turning every content writer into a data scientist. It’s about building a foundational understanding of concepts like prompt engineering, AI workflows, and conversational interfaces. When your team understands the art of the possible, they become more discerning consumers of technology and more creative problem-solvers. The second prong is sourcing new talent—not necessarily by hiring a siloed “AI expert,” but by strategically augmenting the team with consultants or vendor expertise to fill specific gaps. This approach helps the existing team upskill through osmosis while immediately accelerating progress on key initiatives. The goal isn’t to hire for a tool; it’s to build a team that can adapt to any tool.
A New Metric for a New Partnership: Time to Value
We live and die by our metrics. Campaign performance, pipeline velocity, and customer lifetime value will always be paramount. But when measuring the success of a cross-functional AI initiative—and the health of the CMO-CIO partnership itself—we need to look beyond traditional marketing KPIs. Renu proposes a powerful shared metric that aligns both marketing and IT around a common objective: Time to Value.
“I think that time to value of the projects that we decide and anchor on quickly is for me a new success metric, especially when you are onboarding a new technology. And so that you can ensure you’re getting the outcome you wanted, but you’re also doing it at the speed at which you wanted that AI is promising.”
This metric measures not just the end result, but the efficiency and effectiveness of the entire implementation process. How quickly can you move from a pilot to a scalable solution? Did you have to backtrack because of unforeseen security or compliance issues? Did the project deliver on its promised efficiencies at the speed it promised? Tracking Time to Value forces both teams to be accountable for the entire lifecycle of a project. It incentivizes IT to build enabling frameworks rather than restrictive gates, and it encourages marketing to think through implementation and governance from day one. It’s a metric that reflects the reality of modern technology adoption: the win isn’t just in the outcome, but in the ability to achieve that outcome with speed, safety, and scale.
The path forward is not a mystery. It begins with a conversation. As Renu urges, the most practical first step a CMO can take is to sit down with their CIO, not with a list of demands, but with a shared vision for what AI can do for the business. Be transparent about the experiments already underway. Establish trust by showing you understand their mandate for security and stability. From there, you can align on a single, high-impact use case, define what success looks like—perhaps using Time to Value as a shared KPI—and build a system for ongoing dialogue.
This isn’t about marketing ceding control to IT, nor is it about IT stifling innovation. It’s about forging a strategic alliance that becomes a competitive differentiator. The marketing leaders who master this internal collaboration will be the ones who can fully and responsibly harness the transformative power of AI. They will move faster, innovate smarter, and ultimately, deliver more meaningful value to their customers and their business. The time to get out of the shadows and build that bridge is now.
