CEOs want AI to deliver. how marketing drives adoption that works

How marketing fuels AI adoption for success

AI isn’t just dominating leadership conversations – it’s showing up in every corner of the business. From operations to marketing, finance to customer service, teams are asked how they use AI to drive impact. CEOs are under pressure to make their business remain competitive, reduce costs, grow revenue, and be forward-thinking.

But with urgency comes risk. Delayed initiatives, increased cost to implement, unknown future investment, and reputational exposure are becoming common side effects of rushed or siloed AI adoption.

Gartner predicts that 30% of generative AI projects will be abandoned by the end of 2025. Not because the technology failed but because the business wasn’t ready. These aren’t IT issues. They’re leadership gaps.

Marketing has a critical role to play in closing those gaps. Not as the sole owner of AI, but as part of a cross-functional leadership team that thinks ahead, putting in place the strategies, governance frameworks, and execution models to avoid failure.

When businesses bring marketing into the leadership layer of AI adoption – and treat AI as a tool to transform, not just automate – that’s when progress happens.

Where most AI adoption breaks down

AI adoption rarely fails because of the technology. It breaks down in how initiatives are approached, led, and coordinated across the business. The challenges aren’t technical, they’re structural.

Too much data, not enough clarity – some teams struggle with data availability. But increasingly, marketing teams are facing the opposite challenge – too much data and not enough clarity. At a recent Google workshop on the Future of AI, Data and Technology, the recurring theme was overload: too much data, disconnected systems, too many dashboards, and not enough time to analyse or act. For others, data quality remains the issue. AI can help make meaning of the mess but only when there’s clear focus on what to measure and why.
Starting with the solution instead of the problem – AI pilots can be launched without a defined business objective. Someone in the organisation sees a demo or hears about a shiny tool and wants to test it. Sometimes, teams experiment in isolation. But when there’s no shared understanding of the problem being solved, tools become disconnected from business outcomes and stall.
Lack of shared leadership and coordination – AI adoption can suffer from fragmented leadership. Some projects are over-engineered by tech teams with little business input. Others are pushed forward by marketing without proper governance or support. Neither works.

Success depends on coordinated, cross-functional leadership and clear communication. If no one owns that integration, marketing leaders can, and should, step in to help shape it. They’re well-placed to connect the dots between execution, business value, and internal engagement.

Marketing can also play a crucial role in aligning expectations across the business: clarifying what AI is meant to deliver, how success will be measured, and what timeframes and risks look like. Beyond execution, they can influence adoption by driving education, training, and internal messaging to build confidence and cultural momentum.

How marketing can lead AI adoption that works

AI is a business tool. Yet it often shows up first in marketing: automating tasks, generating content, analysing customer patterns. That makes Marketing the test case, whether they’re ready or not.

Here’s where marketing leadership matters:

Strategic integration – AI should support campaign performance, customer experience, and team productivity, not create parallel workflows.
Data clarity – Marketing needs to lead on data quality, what data matters, where it lives, and how it’s interpreted. Poor data quality, disjointed platforms, and siloed systems make it harder to gain real value from AI. Marketing should take full responsibility for data within their remit – owning the structure, flow, and interpretation to ensure it supports better decision-making and outcomes.
Practical application and ownership – Within Marketing’s control is its tech stack. Teams should be taking the lead on how AI is integrated to support their workflows, ensuring solutions are aligned with marketing objectives, campaign processes, and strategic goals, not bolted on as an afterthought. A key part of this is making smarter use of their existing platforms: integrating tools to create a single view of marketing performance and enabling faster, more informed decision-making across the business.
Internal communication and enablement – Marketing has a crucial role in communicating the benefits and purpose of AI adoption across the business. That means clear, honest messaging about expectations, outcomes, timeframes, and business objectives. It also includes leading or supporting practical training, encouraging experimentation, and building confidence across teams. This cultural layer of adoption is often overlooked, but it is where long-term success is shaped.

AI adoption isn’t Marketing’s job. But it won’t succeed without them

Generative AI tools are everywhere. But integrating them well takes coordinated, cross-functional leadership from the start.

Successful businesses are aligning:

Marketing (to lead use cases, execution, communication, and training)
IT (to ensure infrastructure, governance, security, and upskilling)
Legal & Risk (to manage data, privacy, and compliance)
Business leadership (to define success, create a culture of innovation, and encourage testing and experimentation)

This kind of alignment can’t happen in isolation, and it doesn’t come from external consultants alone.

It needs someone operating inside the business – embedded, trusted, and across teams – who can clarify priorities, manage risk, and drive outcomes. That’s where an interim CMO can make a measurable difference. We take on the culture of the organisation, work as part of the team, and help turn good intentions into practical results.

One CEO told me recently, “We had five AI tools in play—but no one could tell me what problem any of them were solving.”

That’s exactly the kind of problem I’m brought in to fix.

Takeaways

AI won’t deliver value if it’s driven by tech first, business second
Data isn’t the problem—quality, lack of clarity, and structure is
Marketing needs to be involved early, not brought in after the fact
Without cross-functional leadership, AI efforts remain fragmented—alignment is what drives results
A strong marketing lead (interim or embedded) can turn AI from confusion into a competitive edge

If your business is exploring AI adoption and needs to bridge the gap between strategy and execution, let’s talk. I work with leadership teams to bring clarity, structure, and practical momentum to initiatives that matter.