When the first GeoComputaion (GC) conference took place in 1996, the computational environment was much more limited. With increased computational power and data storage, we can now model millions of agents and begin to tackle the challenges associated with big spatial data streams. In light of the many changes that have taken place since the 'GeoComputation' book first appeared (Openshaw and Abrahart 2000), this chapter considers what the current limitations to GC are right now. In the first edition, Kirby (2000) identified a series of limitations that included inherent predictability and the need to use additional  computing power to build more complex models, estimate uncertainty and improve the process of model calibration and validation, framed within the context of the earth and environmental sciences. This chapter takes a broader view that encompasses both physical and human geographical domains. Five main limitations are discussed: computational power, data-led limitations, limitations in predictability and understanding, computation or artificial intelligence (AI)-led limits and limitations as a result of uncertainty. Although some of these limitations reprsent real barriers, others can simply be viewed as exciting challenges that require further research within and beyond the field of GC.