Traditional attribution assumes a recognisable path from search to website visit, download and sales conversation. B2B buying rarely follows that sequence anymore. Prospects may use AI summaries, recommendation tools, partner websites and private conversations before they ever identify themselves to a brand.
That makes the click a less reliable measure of influence. Marketing teams need to connect behavioural signals with sales activity, partner engagement and eventual commercial outcomes. The report says those connections are often missing, leaving departments with competing versions of performance.
Gunn is quoted as describing the problem bluntly: “None of our data aligned.”
AI can help organise fragmented systems and identify patterns that conventional dashboards overlook. But the technology still depends on consistent definitions, accessible records and cooperation between marketing, sales, finance and channel teams.
An automated prediction built on incomplete partner or customer information may look sophisticated while reinforcing the same blind spots. The immediate priority, therefore, is not another dashboard. It is an audit of where data sits, who controls it and which parts of the journey remain invisible.
BrightEdge chief executive Jim Yu is quoted as warning that blocking AI agents can damage a brand’s visibility at the moment a buyer is seeking information. “It's a lost opportunity for you in real time,” he said.
That shifts discoverability from a search-engine concern to an ecosystem responsibility. Manufacturers and other B2B companies may need to give distributors and partners better digital tools, clearer product information and more useful access to intent signals.
The next measurement cycle will test whether businesses can move from channel scorecards to shared intelligence. Those that connect their internal systems with partner ecosystems should be better placed to understand influence-even when AI makes the customer journey less visible.