Some of the tasks that ML can help companies deal with is the manipulation and classification of large quantities of vectors in high-dimensional spaces. Current algorithms take a large chunk of time to solve these problems, costing companies more to complete their business processes. Quantum computers are slated to become all the rage soon as they can manipulate high-dimensional vectors at a fraction of the time. These will be able to increase the number of vectors and dimensions that are processed when compared to traditional algorithms in a quicker period of time.
We are still far from applying quantum computing in those types complex problems
It's true we're still not ready for practical applications of QC to ML, but for the time being a wide number of researches have been done and are still on going on the subject, with a lot of interesting and promising results (provided we'll have a working HW soon to run them!).
You could have a look at those (just some examples - many others are available googling a bit):
- Quantum Machine Learning (Seth Lloyd is an authority on the subject...)
- Quantum Nearest-Neighbor Algorithms for Machine Learning
- Quantum computing for pattern classification
- ...
You might find this paper interesting: Preprint An Artificial Neuron Implemented on an Actual Quantum Processor
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