Update first the pages with the most to gain or lose: high-traffic pages that are decaying, page-two rankers sitting just below the first page, and high-intent commercial pages that convert. Sort the queue by traffic-at-stake multiplied by how much you can realistically improve the page, and work top to bottom. Age is not the criterion.
The instinct to “update the oldest first” feels orderly but optimizes for the wrong thing. An old page that is stable, accurate, and quietly serving its audience has little to gain from a refresh, while a one-year-old page that has lost half its traffic to fresher competitors is bleeding right now. Updating everything is not an option when you cannot do all, which is the premise, so the work has to be triaged by impact.
Three groups rise to the top. Decaying high-traffic pages come first because they have the most absolute traffic to recover, and decay usually has a fixable cause: stale information, an answer the results have outgrown, or a competitor who simply did the job better. Page-two near-misses come next because they are close to the threshold where traffic jumps, so a modest improvement can move them from page two to page one and unlock a disproportionate gain. High-intent commercial pages earn priority even at lower traffic, because each visit is worth more, so a small lift there can outweigh a larger lift on an informational page.
Below those sit the low-traffic, stable pages. They are not worthless, but they have little at stake and little headroom, so they wait. The point is not to ignore them forever, it is to refuse to spend your first hours on pages that can barely move while the recoverable losses go untouched.
Build the queue by scoring each page on two axes: how much traffic or revenue is at stake, and how much you can realistically improve it. Update in descending order of the product of the two, and you will spend your limited time where it returns the most rather than where the file is oldest.