After the machines have analyzed users' behaviors, system performance or images, they can be asked to act: the owner's smartphone has just left his workplace and is on his way home? Enhances heating.
The face of the owner of the house appeared before the camera of the entrance? Open the garage. His smartphone just crossed the front door ? Starts playing the last song of his favorite band. His bank account is too inflated? Automatically launch a transfer to a savings account that will generate interest. The last tax provision is approaching and the balance of the bank account does not cover what he paid last year in taxes ? Send him an SMS alert. The conversion rate of a merchant on product X on the Amazon marketplace, dropped by 20% compared to last month? Automatically lower the price by 5%. If the conversion rate does not go up, send an email to the acquisition manager and propose to him to launch a netlinking operation or to add two hundred words to improve trafic so as to compensate conversation rate drop.
As of today, many companies that do not employ the battalions of deep learning experts that Google does, can still develop such applications inspired by artificial intelligence, enabling them to increase the value of their service or optimize processes, development actions or management variables. Most companies can therefore begin to mutate. But the majority do not because the "shovel sellers" of artificial intelligence may be looking more, for the moment, to sell machine learning or deep learning services, but also because professionals who controle digital activities, in companies do not yet have the reflexes related to the implementation of this type of artificial intelligence which presupposes a minimum understanding of programming and algorithmics and that they already have a lot to do to understand the responsive design , load management issues, conversion rate optimization techniques, tag management, or DMP, RTB or Cloud platforms, to name but a few.
If we take a step back from the emergence of these different forms of artificial intelligence, we can see that between today and the uncertain future where machines will surpass man, there is a horizon of two or three years when some professionals will turn into professionals augmented by artificial intelligence and where some companies will become "AI augmented companies". What might these mutant companies look like? Let's take the example of a bank where it sometimes takes years to train customer managers to know their 127 clients and to be able to provide investment or financing advice to them, better than "buy stocks, because stocks are up" or "sell, because a crack just happened". In addition to lack of knowledge of financial products and strategies, customer managers who seldomly stay for more than 3 years in place, do not have time to take an interest in each of their clients. Artificial intelligence by analyzing the profile of customers and detecting suitable products can suggest to the customer manager freshly recruited in his agency by giving him every morning a list of customer actions to be carried out during the day which can range from a simple: "Hello, Mr. Martin, I am presenting myself" to a "Here, dear David, a placement at 7%, a fairly high risk corresponding to your investor profile ", or a "Do you know, dear Anaïs, that we offer a car loan that would allow you to buy a minivan "(I do not tell you, but my intelligent assistant told me based on the analysis of your purchases of the past 6 months that, according to all truth, you were going to have your 3rd child).
In this perspective, artificial intelligence can be an answer to a problem of human resources management: people in their forties who do not know how to manage the generation of millenials that they sometimes perceive as impatient, not involved enough, not sufficiently trained and who, having just arrived on a job, are already thinking about the next one and do not remain long enough to become sufficiently efficient. Intelligent assistants who would immediately render more effective these impatients millenials, could inadvertently solve a generation gap.