The evolving dynamics of innovation in digital, bioeconomy, and clean energy are discussed, focusing on the systemic dimension of change. Systems-based policy approaches that could help policymakers influence these dynamics to achieve societal and environmental goals are presented. Conceptual models of innovation systems have been developed that describe the positive outcome of innovation efforts within a multidimensional, interacting space involving knowledge, actors and institutions, and resource mobilisation, as well as innovation outcomes. These interacting dimensions are complementary and need to be addressed simultaneously by policy. Formal systems modelling can also assist innovation policies to tackle deep innovation uncertainty. Models drawing on portfolio theory provide a quantitative framework of the economic value of risk diversification. In these models, different degrees of risk aversion (to innovation failure) become an input variable specified by policymakers. “Optimal” diversification portfolios given pre-specified innovation uncertainties and policy-specified risk aversion can be determined mathematically.