If Deep learning or Machine learning is blackbox then why companies are still investing?
You make a huge assumption that because something is a black box, that it is not valid. Almost every decision made by a human is essentially a black box decision. Most could tell you the important factors in a decision, but they can rarely quantify accurately, how each component factored into the decision.

Another problem with your question is that you assume all Machine Learning techniques are black box.  For example, a Decision Tree is indisputably a Machine Learning technique, but it is definitely not a black box algorithm.

That said, in some applications, a black box technique is not desirable. For example, in the pharmaceutical field and credit approvals, you want to be able to explain the mechanics of the model.  But in other applications, black box algorithms trained on data generated by experts may perform nearly as well as experts, and probably better than the average human in a given task. For example, in the field of medical diagnosis from imaging, black box algorithms are enjoying success and they can be built right into the imaging software.  This means that the imaging machine can 'refer' the most challenging instances to a doctor for further diagnosis.  This means a doctor can spend more time with the most challenging patients and this is the real reason companies are investing in all manner of Machine Learning applications; they gain some economic benefit that outweigh the costs.

By all means, there are many failures of Machine Learning, but there are so many examples of Machine Learning that have been deployed and nothing is ever really mentioned about it.  For example, my iPhone employs facial recognition to help me search for people in my photos.  With minimal input from me, my phone has tagged, pretty accurately, all the people I typically take photographs of (mostly family).  I think the key is that we are seeing Machine Learning going mainstream to the point that it is not even really acknowledged anymore.