The clamour of anticipation around new applications for artificial intelligence is as fevered as ever. The problem for me is that expectations are not informed by a robust appreciation of the practical requirements for innovating with AI. As an adviser to businesses on bringing such innovation to market, my advice is simple: to scale rapidly, large-scale AI-enabled projects must be built on firm foundations to allow multidisciplinary development teams to thrive. Chief among the reasons is that, in engineering terms, developing AI is a complex, non-linear process. Frankly, you can expend a great deal of time and effort with very little progress to show for it.