Marketing is at a tipping point.
Across the industry, CMOs are no longer asking whether AI will transform marketing, but rather how quickly they can move from experimentation to impact, and how they can restructure their work so that AI is present in the places where decisions are actually made.
This question is at the heart of Microsoft’s CMO AI Innovation Forum at CES and Cannes Lions, with one purpose: to help marketing leaders navigate frontier transformation: moving from tools and pilots to AI embedded in the flow of work to drive measurable business outcomes.
Frontier transformation starts with the flow of work
It’s incredible to see how much things have changed in the months between last year’s Cannes Lions and CES. Six months ago, the question was “Where can I use AI?” Today, it is “How can AI deliver real business value and prove it?” As we headed back to Cannes, the bar became even higher. The era of experimentation is over. Boards and CEOs are no longer interested in pilots; they expect tangible results: monetization, measurable growth, and a clear line from AI investment to business impact.
At the same time, most organizations are not equipped to do so. At least not yet.
CMOs say their teams operate between 25 and 30 disconnected applications, with AI pilots layered on top but rarely integrated end-to-end. The results are predictable. That means disconnected workflows, inconsistent insights, and limited scale. But the real challenges run deeper than technology.
What we consistently hear from marketing leaders is that AI efforts fail if they are limited to a single feature. It can be a success in marketing, but it will fail if the workflow is not connected to other functions within the company.
That’s why the next stage of transformation is not about deploying AI around your business, but embedding it throughout your business. Because AI transformation is ultimately business transformation.
And let’s face it, the stakes are rising fast.
- Monetization is mission critical. Investments in AI should go beyond productivity gains and be directly tied to revenue acceleration, margin expansion, or customer lifetime value.
- Agent commerce is changing the shape of the funnel. Discovery, consideration, and even purchasing decisions are increasingly mediated by AI agents, disrupting traditional attribution models and forcing CMOs to completely rethink their influence.
- Trust is a brand asset and is becoming a defining competitive advantage. As AI-generated interactions expand, consumer trust in data usage, content authenticity, and brand integrity will become competitive differentiators.
- A reset is required for measurement. Traditional metrics cannot capture the non-linear, AI-driven journey. We need new protocols that reflect intent-based engagement, agent participation, and real-time orchestration.
CMO initiatives are accelerating
So, as we think about how these changes are impacting the role of the CMO, I wanted to invite you to the CMO Forum to share what leading CMOs are doing. These leaders are not holding back. In fact, quite the opposite. They are accelerating the integration and operationalization of AI to rewire processes and empower their workforces. Four patterns are emerging:
1. Measuring AI value has become non-negotiable, but it’s still not settled.
Efficiency and time savings are important. CMOs are under pressure to directly link AI to growth, effectiveness, and company outcomes. To achieve this, they are moving beyond surrogate metrics (time savings, content production) to value-based measurement frameworks such as:
- Connect AI-powered personalization to increased revenue and quality of conversions.
- Measure time to market as a competitive advantage, not just an operational KPI.
- Understand how to measure attribution using agent commerce as a medium in the buying process.
CMOs agree that measuring productivity and effectiveness end-to-end is a critical and unresolved problem.
2. Cross-functional workflow is more important than functional excellence
When sales, commerce, service, and supply chains are not connected, marketing wins are no longer enough. The major organizations are:
- Incorporate AI into the end-to-end process from demand to fulfillment, not just campaign execution.
- Connect marketing signals directly to sales prioritization, supply chain planning, and service resolution.
- Use AI to coordinate real-time decision-making across functions, not just optimization within silos.
We learned that marketing blunders can fail if other organizations aren’t aligned.
3. AI is changing who marketers serve and how they serve them
It’s clear that we’re no longer just marketing to consumers. This results in significant changes, including:
- Brands need to optimize not only human attention, but also machine understanding and recommendations.
- Content strategies must evolve toward structured, verifiable information that AI systems can trust.
- Influence change as a model I believe When it comes to your brand, it’s just as important as what your customers see.
Customer and consumer engagement is not limited to human audiences; LLMs and agents shape discovery, consideration, and purchases in real-time.
4. Agentic AI reveals gaps in operating models
As teams try out agents, undocumented processes, tribal knowledge, and governance gaps quickly surface, forcing a rethinking of roles, incentives, and accountability. Leading companies are taking decisive action to:
- Redesign roles around human-agent collaboration rather than task ownership
- Establish a clear governance model for AI decision-making and accountability.
- Create shared data and process standards to ensure agents perform reliably.
- Investing in a trust framework that includes transparency, explainability, and responsible AI practices.
The fourth item is especially important because trust is important not only externally with customers, but also internally. Can teams trust AI output enough to act quickly? And can leaders scale AI without posing risk to the brand?
Take-out
Throughout these conversations, one thing is clear. That means CMOs don’t just need more technology. They need clarity. They need connection. And you need confidence in how you scale. They’re looking for real-world patterns, proven approaches, and a practical path from pilot to enterprise value. Because the next chapter isn’t about experimenting with AI. It’s important to operationalize it across your business to have real, measurable impact.
