AI seems to be on the hype cycle in 2017 and companies offering unrealistic solutions is no surprise to many of us. The reality is that many companies are too green in the BI to Big Data process, and many in fact have faltered on the Big Data front, trying to boil the ocean. If ML and AI are to be successful, data needs to be better managed and regulations like GDPR should be focusing companies to be data centred in their strategies. This would tend to align them on their data journey towards GDPR compliance and the benefits many companies state where companies successfully using AI / ML strategies often expect to be around 15% more profitable than companies that don't.
The attached article by Fabio Ciucci on Deep Learning is well written and worth the read.
AI is not easy or fast to apply. The most exciting AI examples come from universities or the tech giants. Self-appointed AI experts who promise to revolutionize any company with the latest AI in short time are doing AI misinformation, some just rebranding old tech as AI. Everyone is already using the latest AI through Google, Microsoft, Amazon etc. services. But "deep learning" will not soon be mastered by the majority of businesses for custom in-house projects. Most have insufficient relevant digital data, not enough to train an AI reliably. As a result, AI will not kill all jobs, especially because it will require humans to train and test each AI.