How semantic search works
Early search engines matched strings. If a page did not contain the words you typed, it struggled to appear at all. Semantic search matches meaning instead: the engine works out what the query is about, which real-world things it refers to, and what a satisfying answer would contain, then finds pages covering that — whether or not they use your exact wording.
Several layers do this together. Words are converted into numerical representations so that phrases with similar meaning sit close together, language models read the query as a sentence rather than a bag of words, and the things named in it are resolved to entities in a database of people, places and concepts. Someone searching cheap flights kathmandu to sydney and someone searching affordable airfare KTM to SYD describe one need, and the engine treats them that way.
Why semantic search matters
It changes what optimisation means. Repeating a phrase stopped working long ago. What works now is covering a topic properly, in the words your customers actually use, with the related questions answered on the same page or on pages clearly connected to it.
It also explains results that look wrong at first glance. A page can rank for a phrase it never contains, because it answers the underlying question. Another can miss a phrase it repeats constantly, because the engine has read the search intent differently — the people typing it want to buy, and the page explains.
Where semantic search goes wrong
The usual mistake is over-correcting. Because exact matching is gone, people conclude that keywords no longer matter and stop checking how customers phrase things. Meaning-based retrieval still needs your page to be about the thing; writing in your own internal jargon while customers use ordinary words leaves a gap that no amount of semantics closes.
The opposite error is padding a page with synonyms and related terms pulled from a tool, on the theory that mentioning more concepts makes the page more relevant. That produces something which reads like a word list and covers nothing in depth. Depth is what the mechanism rewards, not vocabulary coverage.
How to act on it
Plan pages around a question and everything a reader needs to settle it, rather than around a phrase. Read the results page for your target query before writing: it shows what the engine currently believes that query means, and if the pages ranking are guides while yours is a product page, you have a mismatch to resolve before any amount of writing helps.
Be explicit about what you are discussing — name the product, the place, the standard or the organisation in full at least once — so there is nothing to disambiguate. Keep one page per intent rather than several near-duplicates, and link related pages together with descriptive anchors so the relationship between them is legible. That is most of what modern content SEO actually consists of.