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Why measuring AI's true financial impact remains elusive despite measurable productivity gains

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TLDR

Most marketing teams struggle to prove ROI on AI investments because they measure task productivity instead of workflow outcomes and overlook costs spread across departments.

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MARTECH explains why calculating true AI return on investment has become harder even as the technology delivers measurable gains in productivity and operational efficiency. While AI boosted sales productivity by 14.1% and customer satisfaction by 10.8% year-over-year, only 16% of CMOs could confidently measure their AI investment results; nearly 70% lacked precision in measurement, and 21% had no measurement infrastructure at all. The core problem: organizations measure the activity AI performs rather than the change it produces, fail to account for hidden costs like data preparation and human review that shift work between departments rather than eliminating it, and miss the cross-departmental expense distribution that makes departmental ROI calculations look better than they actually are. The outlet recommends measuring entire workflows before and after AI deployment, including all integration and governance costs wherever they appear in the organization.

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