The last decade, civil engineering has exercised a rapidly growing interest in the application of neurally inspired computing techniques. The motive for this interest was the promises of certain information processing characteristics, which are similar to some extend, to those of human brain. The immediate examples of these include an ability to learn and generalize. In parallel to this and further developments in the information systems technology, established the essential motivation that the construction industry should benefit from these developments for enhanced and effective executions. Today such information processing methods are collectively referred to as soft computing (SC). Explicitly, soft computing is an emerging approach to computing which parallels the remarkable ability of the human mind to reason and learn in an environment of certainty and imprecision. SC consists of several computing paradigms, including neural networks, fuzzy set theory, approximate reasoning and combinatorial optimization methods such as genetic algorithms. SC finds important applications in diverse disciplines. As a branch of artificial intelligence, soft computing is closely related to computational intelligence where in essence SC methods are implemented by machine learning techniques. Paper deals with SC in the context of construction information technology (CIT) pointing out the important role it can play. It exemplifies the SC applications in CIT supported by pilot implementations, which are carried out as a part of ongoing departmental research program.