The rise of machine learning can give some businesses advantages over others. The favour leans towards the big guys.
When training machine learning, it is crucial to find suitable data and a huge quantity of it. The fact that large organisations are more likely to have large databases of training data from years of operation makes them the primary beneficiaries of the AI wave. When needed, they can reach out to existing networks and utilise the relationships they have with other big organisations. It's simpler.
On the other hand, small companies can move fast, they are more innovative, and flexible but lack the large samples of training data. Startups that want to develop a machine-learning based product need to think hard about where they would get data from. Without required data, it's an uphill battle.
Despite this, open data sets such as Machine Learning Library and Stanford’s Deep Dive are starting to emerge. This is a big opportunity for startups because they can acquire data for a very cheap price or at no costs. Those that can leverage these opportunities are the ones that will thrive.
Data, after all, is necessary to train the machines. A small company could have big plans but without big data to feed those plans, it's a losing battle. As such, large enterprises are in a prime position to use big data to enrich themselves and effectively hold off would-be, smaller competitors.