Why AI spending isn’t boosting marketing

Imagine a company investing heavily in faster ambulances while ignoring the pothole-riddled road that keeps causing accidents. It sounds weird, but, according to a new survey, this is happening in marketing AI investments across the private sector. Executives pour money into downstream solutions like personalization engines and content generators while the real marketing processes bottlenecks continue to slow everything down.

The numbers are from a small sample but can tell a stark story. According to recent GrowthLoop survey data, 51% of executives say their marketing cycles are “fairly fast” or “extremely fast.” Only 28% of non-executive marketers agree. This isn’t just a minor disagreement. It’s a fundamental disconnect is driving millions of dollars in AI spending.

The information asymmetry loop: a vicious cycle

That is an “Information Asymmetry Loop”—a self-reinforcing cycle where executives and marketing teams operate with different information sets, leading to consistently misaligned AI investment decisions.

Here’s how the survey shows this cycle working: 

• First, executives see strategic KPIs that mask operational inefficiencies in marketing cycles. Dashboard metrics might show solid conversion rates and revenue growth, but not reveal the weeks spent waiting for data analysis or the bottlenecks in campaign execution. 
• Second, this incomplete picture drives investments toward visible AI applications, such as “shiny” personalization tools and content creation platforms that executives can easily understand and demonstrate to boards.
• Third, if/when these investments fail to deliver expected ROI (because the underlying operational problems remain), measurement systems can’t properly attribute the performance issues to their possible causes (was it the personalization tool or any delays in taking the campaign to market?)
• Fourth, the persistent bottlenecks continue to limit the effectiveness of all marketing efforts, including those expensive new AI tools. 
• Finally, poor AI ROI reinforces executives’ belief that they need to make even more “strategic” AI investments, and the cycle continues.

The irony is profound: addressing the operational bottlenecks could deliver the strategic outcomes executives want, but the information disconnect prevents optimal investment allocation.

Dig deeper: 3 MOps bottlenecks killing your campaign velocity

What the data really shows

The GrowthLoop survey reveals the depth of this misalignment. Beyond the gap on cycle speed, it shows that marketing teams feel increasing pressure from executives pushing personalization initiatives “that aren’t supported in daily operations.” Meanwhile, companies with faster marketing cycles demonstrate measurably better AI ROI—validating the hypothesis that operational efficiency is the key to AI success.

That aligns with broader industry data from PwC’s 2025 research, which found that 49% of technology leaders reported AI as “fully integrated” into their companies’ core business strategy, while 33% stated AI was fully integrated into products and services. These numbers indicate executives see AI through a strategic, customer-facing lens and not as an operational efficiency tool. This is a lost opportunity, as AI can also shorten marketing cycles, which, as we’ve seen, correlates to better AI ROI. 

The GrowthLoop data comes from surveying marketing executives and operational marketers across various company sizes and industries. While the sample provides valuable insights into perception gaps, it’s worth noting that the survey doesn’t control for company size, industry vertical or AI maturity levels, which could influence results. Also, the binary nature of the “fast vs. slow” cycle assessment may not capture the nuanced reality of marketing operations.

Breaking the cycle: A path forward

The solution isn’t abandoning strategic AI investments. It’s aligning them with operational reality. 

Here is how to break the Information Asymmetry Loop:

1. First, conduct operational bottleneck assessments before making AI investment decisions. What are the actual time-consuming steps in your marketing cycles? Where do campaigns get stuck? What manual processes consume the most hours? 
2. Second, revise AI ROI metrics to value marketing cycle improvements properly. Current measurement systems often miss the compound benefits of operational efficiency gains, but marketers are well-positioned to quantify these gains. 
3. Third, create executive visibility into day-to-day marketing operations (help ensure these operational efficiency gains are periodically tracked). Regular operational reviews can help bridge the information gap that drives misaligned investments. 
4. Fourth, using that data, prioritize the AI investments that address upstream bottlenecks. For example, you need to understand your customer data points before buying the personalization engine.

Realigning executive understanding and AI investment toward operational bottlenecks maximizes AI’s business impact and achieves the strategic outcomes executives ultimately desire. When marketing cycles accelerate, those personalization tools and content generators will deliver an even larger ROI.

The ambulances run much better once we fix the road.