This is interesting because I believe the two major supermarkets in Australia can create a duopoly in anti-competitive pricing by just employing price analysis AI algorithms on each side and the algorithms will likely end up cooperating to maximise profit. This can probably be done legally through publicly obtained prices and illegally by sharing supply cost or profit per product data. The result is likely to be similar. Two trained AIs will maximise profit in weird ways using (super)multidimensional regression analysis (which is all AI is), and the consumer will pay for maximised profits to ostensible competitors. If the pricing data can be obtained like this, not much more is needed to implement a duopoly-focused pair of machine learning implementations.
The rationale is that if all prices are out there in the open, consumers will end up paying a higher price, as the actors (supermarkets) will end up pricing their stuff equally, at a point where everyone makes a maximum profit.
For years said supermarkets have employed "price hunters", which are just people that go to competitor stores and register the prices of everything.
Here in Norway you will oftentimes notice that supermarket A will have sale/rebates on certain items one week, then the next week or after supermarket B will have something similar, to attract customers.
