Enterprise marketers love talking about AI, automation, and cutting-edge martech. Yet a new survey suggests most of that hype falls apart at the foundation: the data feeding those tools. According to fresh research from Intermedia Global (IMG), only 2% of UK marketing leaders rate their data quality as strong and flowing cleanly through their martech stack. In other words, 98% are operating with data that slows them down—or worse, derails their ambitions.

The study, which surveyed 250 C-suite executives running marketing technology budgets within mid-sized UK enterprises (£100m–£500m in revenue), exposes a deep operational gap. Despite a decade of martech expansion, data remains the weakest link.

Data Inefficiencies Are Draining Budgets—and Patience

Marketers often blame slow performance on tools, teams, or budgets. Yet IMG’s findings point to something far simpler: poor data flow. And the consequences show up everywhere.

Nearly half of respondents waste time manually pulling reports. Forty-four percent say weak data slows learning cycles and triggers repeat mistakes. Even more concerning, 42% admit they lose budget because existing tech is underused or misused. Another 40% struggle with broken targeting and wasted media spend—a costly issue in a market where every click is scrutinised.

These pain points reflect a deeper structural problem. Martech stacks have grown rapidly, but integration rarely keeps pace. When the pipes are clogged, nothing downstream works as promised.

AI’s Value Hinges on Data Readiness

IMG’s data planning lead, Emily Crisp, points out that the problem isn’t a lack of awareness. In fact, 91% of CMOs say data quality directly affects campaign performance. What’s missing is action—and the discipline required to fix foundational issues before adding new technology.

Crisp also highlights a growing disconnect: brands are pouring money into AI tools while ignoring the data requirements those tools depend on. MIT’s recent findings show that 95% of companies have yet to see ROI from generative AI pilots. The issue isn’t AI—it’s the poor-quality data feeding it.

Tools powered by machine learning amplify whatever they ingest. If the inputs are messy, the outputs will be worse. In short, AI cannot rescue bad data. It only exposes it.

The Real Path Forward: Fix the Data, Not the Stack

The martech industry has long been obsessed with adding new platforms, integrations, and “next-gen” capabilities. IMG’s research is a blunt reminder that innovation without operational discipline rarely delivers value.

Crisp puts it plainly: improving data flow is the first step toward better performance. Ignoring it creates friction at every stage of the marketing lifecycle. Before CMOs chase new AI promises, they must address the fundamentals—governance, hygiene, enrichment, and cross-platform consistency.

It may not be glamorous, but it is transformative. Strong data turns existing martech into high-performing assets. Weak data turns even the most advanced tools into expensive clutter.

For marketing teams under pressure to prove ROI, this is the wake-up call. AI will not fix the martech ecosystem. But clean, efficient data just might.

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