Why AI Spending Isn’t Boosting Marketing
Picture a company investing heavily in faster ambulances while ignoring the pothole-riddled roads that keep causing accidents. It seems odd, but recent survey data shows a similar mismatch in how businesses invest in marketing AI. Leaders pour budgets into downstream tools like personalization engines and content generators, while the real operational bottlenecks remain unaddressed.
This disconnect means AI investments often miss their mark, failing to solve the critical issues slowing marketing performance.
The Information Asymmetry Loop: A Vicious Cycle
There’s a cycle at play here—what we can call an “Information Asymmetry Loop.” Executives and marketing teams operate with different views of marketing realities, leading to misaligned AI spending.
- Executives see strategic KPIs like conversion rates and revenue growth, which often hide delays and inefficiencies in marketing execution.
- This incomplete picture drives investment toward flashy AI tools that are easy to explain and show off, such as personalization platforms and automated content creation.
- When these tools don’t deliver expected ROI, it’s hard to pinpoint whether it’s the tech or persistent operational delays causing the underperformance.
- Operational bottlenecks continue limiting results, dragging down the value of all marketing efforts, including new AI investments.
- Executives respond by doubling down on more strategic AI spending, perpetuating the cycle.
The irony is clear: fixing the operational slowdowns would unlock better marketing outcomes, but the disconnect keeps investments focused elsewhere.
What the Data Really Shows
A recent GrowthLoop survey highlights this gap. While 51% of executives say their marketing cycles are “fairly fast” or “extremely fast,” only 28% of marketers agree. This signals a serious perception gap that impacts where money goes.
Marketers also report rising pressure from executives to push personalization initiatives that daily operations can’t support. Companies with faster marketing cycles consistently show better AI ROI, suggesting operational efficiency drives AI success.
This aligns with PwC’s 2025 research, where nearly half of tech leaders see AI integrated into core business strategy and a third into products. The focus is on strategic, customer-facing AI rather than operational improvements—a missed chance to speed up marketing cycles and improve ROI.
Note that the GrowthLoop data comes from a broad mix of company sizes and industries, so individual results may vary. The simple “fast vs slow” cycle measure also doesn’t capture every nuance of marketing operations.
Breaking the Cycle: A Path Forward
Abandoning strategic AI investments isn’t the answer. The key is aligning AI spending with real operational challenges. Here’s how to break the loop:
- Assess operational bottlenecks first. Identify the slowest steps in your marketing cycles and where campaigns stall. Pinpoint manual tasks consuming the most time.
- Update AI ROI metrics to value cycle speed. Traditional ROI measurements often miss the cumulative benefits of faster marketing execution. Marketers can help quantify these gains.
- Increase executive visibility into daily marketing work. Regular operational reviews create transparency and keep efficiency goals top of mind.
- Prioritize AI investments that tackle upstream issues. Before buying a personalization engine, ensure your customer data and processes are ready. Focus AI spend on removing bottlenecks first.
When marketing cycles speed up, tools like personalization engines and content generators will deliver bigger returns. Fixing the road before upgrading the ambulance is the smarter investment.
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