The benefits of parallelization are highly depended on the task, but there are quite a lot of tasks that are very amenable to it. It's difficult to rewrite a system from the ground up to take advantage of parallelization, but systems are designed with it in mind from the beginning, they can simply be scaled up as a larger number of processors becomes economically feasible. For quite a few algorithms, setting up parallelization is quite easy. Creating a new bitcoin block, for instance, is already a highly parallel task. As far as society-changing applications, there's a wide variety of tasks that are very susceptible to parallelization. Certainly, human-level intelligence does not appear to require huge serial power; human neurons have a firing rate in at most a few hundred hertz. Self-driving cars, wearable computers, drones, database integration ... I don't see a need for super-fast processors for any of these.
There's a long article in this week's The Economist:
The onrushing wave
discussing the effect of changing technology upon the amount of employment available in different sectors of the economy.
Sample paragraph from it:
(There's a summary online of their previous book: Race Against The Machine: How the Digital Revolution is Accelerating Innovation, Driving Productivity, and Irreversibly Transforming Employment and the Economy)
What do people think are society's practical options for coping with this change?