An internal review of our own commentary coverage over a sustained period revealed a skew we hadn't been deliberately tracking: a large majority of pieces referenced or centered on a small handful of large, well-known AI companies, with proportionally little commentary addressing smaller companies, regional players, or less prominent parts of the ecosystem.
Why this skew happened without any deliberate decision to create it
Large, well-known companies are simply easier to write commentary about - more publicly available information, more existing context readers already share, more immediate relevance to a broad audience. Each individual editorial decision to write about a large company was reasonable in isolation, but the aggregate pattern still produced a meaningfully skewed picture over time.
Why this skew matters beyond simple variety
Commentary concentrated on a handful of large companies risks implicitly training readers to associate the entire AI business landscape with those few companies specifically, understating the real activity and significance happening across a much broader and more varied set of organizations.
What we changed as a result
We started deliberately tracking the company-size and prominence distribution across our commentary output on a periodic basis, and adjusted assignment and pitch selection specifically to correct the imbalance once we could see it clearly, rather than relying on our own unexamined sense of whether coverage felt reasonably balanced.
Why we're sharing this rather than just quietly fixing it
We think this kind of unintentional skew is common across AI commentary generally, and making our own audit and correction process visible is more useful to readers evaluating any publication's coverage than simply presenting the corrected version without acknowledging the pattern it was correcting.