This paper develops an economic perspective on dynamic capabilities by conceptualizing them as investments in intelligent knowledge under uncertainty. The dynamic capabilities literature has made substantial progress in explaining how firms sense opportunities, seize them, and reconfigure resources, yet it has paid less systematic attention to the cost structure of capability development and to the possibility that organizations may invest either too little or too much in dynamic capabilities. Building on a formal transaction cost optimization model previously developed by the author, the paper argues that dynamic capability investment follows an analogous optimization logic: organizations incur direct and quasi-fixed costs in building sensing, seizing, and reconfiguring mechanisms, while these investments reduce the expected losses associated with misadaptation, missed opportunities, strategic errors, or delayed transformation. The central claim is that there is a scale-dependent optimum of dynamic capability investment. As organizational exposure increases – through size, volume, scope, technological interdependence, or ecosystem involvement – the potential losses from weak adaptation increase, making higher capability investment economically justified. However, the optimum remains bounded because excessive investment may generate coordination burdens, cognitive overload, bureaucratic routines, and declining flexibility. The paper contributes to dynamic capability theory by integrating economies and diseconomies of scale into the analysis of intelligent knowledge investments and by deriving propositions for SMEs, large firms, and sustainability-oriented innovation ecosystems.