Few technologies have reshaped marketing as quickly as AI.
In the less than three years since ChatGPT’s public debut, generative AI has become embedded in many marketers’ workflows, influencing everything from media buying to creative development. And its influence is only expected to grow, with 90.7% of marketing and advertising professionals believing AI will radically transform the industry within the next three to five years.
But widespread use doesn’t guarantee effectiveness. In the rush to implement this new technology, many teams have overlooked one of the keys to its effectiveness: data. When AI runs on fragmented or low-quality inputs, results are unreliable. Insights get blurred, personalization misses the mark, and recommendations fall flat. Such missteps have a direct cost, as they quickly compound into wasted spend and weakened consumer trust. As AI transforms the industry, the organizations that thrive will be those that invest in clean, privacy-compliant first-party data—the foundation AI needs to deliver accurate, differentiated value.
From faster analysis to smarter targeting to more relevant creative and beyond, the potential for AI in marketing is significant. But the reality of implementing AI effectively is that its accuracy hinges on the quality of the data it consumes.
When data is inaccurate, siloed, or inaccessible, the risk of error increases significantly. Poor data not only muddies results but also raises the odds of hallucinations, where AI generates outputs that appear credible but are instead fabricated. Because the technology mimics the information it’s trained on, gaps or inaccuracies in the data increase the likelihood of such mistakes. This is a significant problem, with one recent test finding that newer AI models can hallucinate as much as 79% of the time.
For marketers, those hallucinations can look like real insights: an optimization tool shifting spend toward audiences built on incomplete signals, a personalization engine delivering irrelevant product recommendations with full confidence, or a dashboard surfacing “top-performing” keywords that don’t exist. These aren’t minor errors—they are costly missteps driven by weak data foundations. Even small inaccuracies can snowball, feeding back into models and negatively shaping future decisions.
For all the focus on AI, most organizations are still behind on data readiness. Increasing privacy regulations and signal loss have already made first-party data critical, and AI adoption further raises the stakes. Clean, consented, and unified data is what powers accurate insights and effective personalization.
Yet few organizations are currently treating it that way. Just 21.4% of industry professionals say first-party data is foundational to their AI efforts, while more than a third admit it plays little or no role. That gap between ambition and readiness helps explain why many AI tools underdeliver. Until first-party data is prioritized, real impact will be limited.
Though marketers know data is essential, many face significant barriers to leveraging it effectively. Roughly 34% of industry professionals say their first-party data is limited and fragmented, 11% don’t use it at all, and less than one in five describe it as extensive and well-structured.
Some of the key challenges that hinder marketers’ ability to effectively leverage data are data accuracy and quality, as well as scale and volume of data. While most teams have access to large amounts of data, fragmentation prevents them from forming a reliable single view of the customer. For example, a travel company might struggle to connect loyalty profiles with search behavior and purchase history. Despite having plenty of data, it’s difficult to use and more prone to errors because it’s siloed across platforms and systems. AI trained on only one slice of that picture could misread intent, recommending irrelevant offers or overvaluing the wrong audiences. Multiply that problem across numerous systems and campaigns, and it’s clear how marketers lose both efficiency and accuracy to data problems.
AI delivers its strongest results when it runs on a solid data foundation. Brands that prioritize clean, consolidated, and accessible data systems see stronger AI-powered targeting, personalization, and optimizations. For agencies, reliable data ecosystems fuel creative and strategic outputs that capture the nuances of their clients’ audiences.
This groundwork starts with first-party data itself: ensuring it is collected with consent, stored securely, and structured in ways that make it easy to analyze and share across teams. Data hygiene practices—regularly auditing for accuracy, de-duplicating records, and unifying customer identifiers—are also essential for maintaining quality at scale. Leaders that embed these practices into ongoing workflows, rather than treating them as one-off clean-up projects, see compounding benefits over time.
Equally important is making data actionable. Tools that unify disparate data sources and streamline reporting help address this challenge. By consolidating scattered signals into one source of truth, teams eliminate silos and reduce errors, thus allowing them to give AI models consistent inputs. Platforms that bring together existing media, CRM, and analytics systems into clear dashboards not only improve efficiency but also provide the clarity needed to optimize campaigns in real time. This enables a shared understanding across marketing, sales, and finance teams, which in turn makes it easier to align on strategy and measure impact.
With these foundations in place, teams are better positioned to unlock AI’s full potential.
AI has quickly become embedded in marketing workflows, but its value depends largely on the data that fuels it. Too often, that foundation is fragmented or incomplete.
Organizations that invest in systems to ensure clean, compliant, and unified first-party data will be well-positioned to capture AI’s full value. The payoffs are significant: stronger ROI, personalization that resonates, and long-term differentiation. In the years ahead, it won’t necessarily be the earliest adopters who come out ahead—it will be those who built the strongest data foundations.
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Looking for even more insights into the state of AI in marketing? We surveyed marketing and advertising professionals from leading agencies and brands for our third annual AI and the Future of Marketing report. It’s filled with insights to help industry leaders evaluate how to use AI responsibly, strategically, and with urgency.
