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Technology—the application of theoretical knowledge to practical problems—appears in two forms, tangible like electronic devices and intangible like software and processes. Digital technology converts analog information from physical signals into bits, enabling storage, computation, and transmission at scale.
The proliferation of technologies that rely on digital data representation gave rise to the contemporary Information Age, in which information is a commodified asset and knowledge is the principal driver of economic growth. In this knowledge economy, the production and consumption of goods and services depend on the effective application of the Data-Information-Knowledge-Wisdom (DIKW).
Unstructured data gains context to become information; information integrated with experience becomes knowledge; and applied judgment yields wisdom. This transformation constitutes knowledge work, and the professionals involved are knowledge workers (KWs).
Knowledge appears in two distinct forms, tacit (personal and hard to formalize) and explicit (codified and sharable through documents, databases, or manuals). It is the role of Knowledge management (KM) to convert individual know-how into organizational capability.
In knowledge-intensive firms, where primary assets are intangible and reside in employee expertise, KM is critical because it makes use of the organization’s collective intelligence (CI)—the shared capacity to learn, adapt, and solve complex problems across teams. Advances in artificial intelligence (AI) contribute by automating parts of the DIKW pipeline and augmenting knowledge work.
