This survey reveals both excitement and trepidation around enterprise AI adoption for knowledge management. Long-standing problems around information access, data quality, and speedy acquisition of needed information are the puzzle pieces that AI has the potential to solve.
The options are many and varied when it comes to taming silos. The specific approach should depend on the use case, the organization's existing knowledge assets, and the strategic goals.
Modern collaboration means and mechanisms ultimately make it easier, less risky, and more productive for organizations to work together within business units, between them, and between organizations. Constructs such as data mesh architecture, data fabric architecture, data access governance platforms, data catalogs, and process automation solutions are based on sharing information between parties—and make doing so tenable.
Until KM systems can achieve trust in AI, a totally AI-centric workplace will be a fantasy. The future of KM will be based on collaborative work habits, fueled by technology that encourages knowledge sharing, enhances productivity, supports employees to have a healthy work life, and accepts that not every aspect of knowledge management is technology-reliant.