Why Everyone’s Talking About MCP Connections, and Why You Should Care
Hot take (because when have I ever not got one?):
I’m willing to bet most of you reading this have some complicated way of connecting your data and trying to keep up with the management of it is a burden. And, you probably haven’t used MCP yet to try to solve it.
Not the sexy, buzzword-friendly “we need AI to save us!” problem. The you can’t stitch revenue and journey data without breaking a sweat problem. The why-is-the-pipeline-question-still-a-slog problem.
Enter MCP connections between data sources — quietly evolving into the unsung hero of modern analytics stacks. If it sounds like just another acronym du jour, stay with me. This one actually matters. And yes, I’m going to explain it like your fellow MarTech pro who knows you’re tired of jargon.
What I’m Seeing on the Front Lines: How Generative AI Is Actually Changing Marketing, AdTech, and RevOps Data Work
Hot take…many marketing, advertising, and revenue teams are getting ahead of the data problem, but they still have an insight problem. Despite powerful platforms and endless dashboards, getting from signal to understanding still takes too long. From my perspective working at Adobe and with many high-tech customers, generative AI is finally changing that. By enabling teams to ask natural-language questions, auto-generate insight narratives, and connect web, media, and revenue data more intuitively, GenAI is shifting analytics from reporting to reasoning. The real impact is helping humans understand their data faster, communicate insights more clearly, and make better decisions across the entire customer journey.