In the future, search engine Google will look like a combination of Google and Wikipedia. When you search for something on Google, you will get a wikipedia-like explanation of the term you are looking up and a list of categories to further refine your search, rather than a list of most relevant links, as you get now.
The links won't disappear completely, you will still be able to visit relevant web pages, but the links to these sites are highlighted words in the explaining text or in the biography, or 'See also' section, at the end of the small article.
The content for the small article and the categories isn't provided and edited by a community of people sharing knowledge, but is derived from all information that is accessible, like webpages and digital libraries. For this to work, an algorithm (computer program) is needed that can scan documents, articles, blogposts and webpages and understand what it is about. Some people call this AI, or Artificial Intelligence, others would define this to be base of the semantic web.
Rather than looking for the occurance of search terms in the indexes of all webpages, the search sites of the future would understand what the search is about and answer what it 'remembers' about it, after 'reading' and 'understanding' all available sources on the internet.
I'm not affiliated with Google or any other company offering internet search services. What I described is my vision on the future of websearching and looking for information. My vision is much like, and is probably influenced by, the view of Tim Berners-Lee, one of the founders of the internet, on web 3.0 and the semantic web :
I have a dream for the Web [in which computers] become capable of analyzing all the data on the Web – the content, links, and transactions between people and computers. A ‘Semantic Web’, which should make this possible, has yet to emerge, but when it does, the day-to-day mechanisms of trade, bureaucracy and our daily lives will be handled by machines talking to machines. The ‘intelligent agents’ people have touted for ages will finally materialize.
(Berners-Lee, Tim; Fischetti, Mark (1999). Weaving the Web. HarperSanFrancisco, chapter 12. ISBN 9780062515872)
The ability of computers to understand texts, rather than searching for occurances of words, is until now not possible. A big goal in computing was set out by Alan Turing, famous mathematician and the person who cracked the Enigma-code of the German army during the second World War.
The Turing Test defines that a computer must be able to have a conversation with a human, where the human is unable to tell wether he or she is talking to a computer or another person. A computer that passes the Turing Test is considered to be thinking, interpreting and understanding on its own.
When computers (or algorithms) could pass the Turing Test, they would be able to understand and interpret every available text and information and connecting it to other texts or concepts, just like humans would do, thus making the semantic web possible.
Until now, computers haven't passed the Turing Test, so we have to do with the current search technologies aided by human understanding, like I mentioned in Computers need help or projects like ChaCha.