83% of Demand Gen Marketers Use AI Daily. Why Aren't Results Matching?
Scott Schnaars
83% of Demand Gen Marketers Use AI Daily. Why Aren't Results Matching?
An Exit Five poll found that eighty-three percent of demand gen marketers use AI as a core part of their daily workflow. Most people I talk to believe it is probably accurate. Most also admit they are not sure results have meaningfully improved.
The Exit Five community (https://www.exitfive.com/community) explored why. The answer is uncomfortable but accurate: most daily AI use is concentrated in productivity tasks, and productivity tasks are not where the pipeline impact lives.
Writing a brief faster does not change whether it is targeting the right audience. Summarizing a performance report does not identify the anomaly buried in the data. Generating ten ad headline variations in thirty seconds does not change whether the campaign is reaching the right companies.
The AI use cases that actually move pipeline:
- AI that monitors your campaigns continuously and flags when performance deviates from expected range, before the end-of-month review catches it
- AI that compares your campaign data against historical patterns and recommends specific changes based on your actual program, not generic best practices
- AI that pulls data across multiple paid channels and identifies correlations between channel activity and deal velocity that would take hours to find manually
- AI that models the pipeline impact of budget reallocation scenarios based on your actual cost-per-pipeline-dollar across channels
These use cases require connected data. If your AI tools are working from platform-native data in siloed dashboards, they cannot do any of these things. That is the constraint. Not the model quality.
Yirla applies AI to your connected paid data to surface insights that change decisions, not just accelerate tasks. (https://www.yirla.com/integrations)
