AI in MarTech
Where AI actually moves the needle — measurement, creative, personalization, identity, and the agents starting to do real work. Founder interviews and brand-side reality checks, no hype.
Where AI is really working in MarTech
Where is AI actually moving the needle in marketing?
In three places that survive the hype: measurement (behavioral and modeled data that sees what cookies can’t), personalization and merchandising (matching products and experiences to intent at scale), and identity (resolving who customers actually are). The brands winning treat AI as infrastructure that needs clean data — not a feature you bolt on.
Why won’t AI work on a broken data infrastructure?
Because models are only as good as what they’re fed. Several guests make the same point: brands rush to AI use cases while their data sits fragmented across warehouses and tools. Fixing the pipeline — unified, accessible, trustworthy data — is the unglamorous work that determines whether any AI investment pays off.
How are vendors using AI responsibly?
The credible ones are specific: they name the decision the model makes, show the data behind it, and measure lift instead of promising magic. You can compare AI-driven MarTech vendors by what they actually do on Blurbs.
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