We discuss three emerging technologies for process enterprise optimization, using a different application domain as an example in each case. The first topic is cross-functional integration on a model predictive control (MPC) foundation, in which a coordination layer is added to dynamically integrate unit-level MPCs. Enterprise optimization for oil refining is used to illustrate the concept. We next discuss data-centric forecasting and optimization, providing some details for how high-dimensional problems can be addressed and outlining an application to a district heating network. The final topic is adaptive software agents and their use for developing bottom-up models of complex systems. With learning and adaptation algorithms, agents can generate optimized decision and control strategies. A tool for the deregulated electric power industry is described. We conclude by emphasizing the importance of seeking multiple approaches to complex problems, leveraging existing foundations and advances in information technology, and a multidisciplinary perspective.