AI is transforming marketing attribution by enabling a more nuanced understanding of what influences deals. Traditional methods, like first- or last-touch attribution, often oversimplify complex journeys, leading to inaccurate assessments of marketing effectiveness. Marketers struggle with incomplete data, which makes it hard to track the full range of interactions that contribute to a sale. A 2025 study by Adverity found that 45% of the data used for decision-making is flawed, with many CMOs doubting the reliability of their marketing data. The introduction of AI allows for capturing unstructured context from various sources, such as emails and calls, which was previously difficult or costly to analyze. This technology shifts the focus from rigid models to answering specific questions about deals. For example, AI can identify that a partner referral significantly influenced a deal, something traditional methods would likely miss. It also reveals insights like the importance of technical evaluators in closed deals, which often go unrecognized in standard contact roles. Data quality remains a critical factor; AI can only generate accurate insights if it has reliable data to work with. This means resolving identity issues across systems and ensuring that timelines are reconstructed from complete touchpoint data. The article highlights that moving towards an AI-driven attribution model requires marketers to rethink how they gather and analyze data, focusing on the richness of the insights rather than relying on outdated frameworks.