Is data enough to win in AI?

The common narrative in the tech industry is that those companies with access to the most data are best positioned to win with machine learning. The apparent logic of this positive feedback loop is simple: more/better data better models more accurate predictions better product or service more customers more data, etc. In his December 2018 blog post, Benedict Evans argues that this is too simplistic. It is critical to consider what data, for what problems, for which use cases? Google, Facebook, or China will not "just win" because of some combination of existing data assets, scale, and permissiveness around user data.