Lisp WAS used in AI until the end of the 1980s. In the 80s, though, Common Lisp was oversold to the business world as the "AI language"; the backlash forced most AI programmers to C++ for a few years. These days, prototypes usually are written in a younger dynamic language (Perl, Python, Ruby, etc) and implementations of successful research is usually in C or C++ (sometimes Java).
If you're curious about the 70's...well, I wasn't there. But I think Lisp was successful in AI research for three reasons (in order of importance):
- Lisp is an excellent prototyping tool. It was the best for a very long time. Lisp is still great at tackling a problem you don't know how to solve yet. That description characterises AI perfectly.
- Lisp supports symbolic programming well. Old AI was also symbolic. It was also unique in this regard for a long time.
- Lisp is very powerful. The code/data distinction is weaker so it feels more extensible than other languages because your functions and macros look like the built-in stuff.
I do not have Peter Norvig's old AI book, but it is supposed to be a good way to learn to program AI algorithms in Lisp.
Disclaimer: I am a grad student in computational linguistics. I know the subfield of natural language processing a lot better than the other fields. Maybe Lisp is used more in other subfields.