Today I want to reflect on the current debate: are machines able to replace managers? It is known that billions of dollars are invested worldwide in machine learning technologies, and according to PwC, the introduction of artificial intelligence by 2030 will increase global GDP by more than 15%.
Take, for example, Russian banks, which are already actively testing voice identification, minimizing possible risks, as well as demonstrating outstanding results of forecasting and assessing the solvency of customers. Personalized service offerings, according to experts, have increased revenue from retail banking products by 7% year-on-year, and marketing is becoming a completely different field for analytical "creativity".
In a retail close to me, the introduction of machine learning has already reduced the cost of millions of dollars only in one of the largest Russian networks (optimization of logistics, change of store locations, real-time inventory, demand forecasting and assortment planning).
However, despite the high potential, we all see that practical implementation often hinders managers ' doubts about the return on such investments. A rare Manager thinks in the long term, knowing who is the first to optimize business processes, he will not only reduce costs, but will be able to create the best offer for the client. The expression "time is money" is appropriate in this situation.
About a year ago, I myself initiated the implementation of a business process management system, which freed time not only to solve their own problems, but also allowed to move to a remote format. The workload of employees has been reduced, which has become more efficient and focused on the main functions, which the algorithm is still difficult to cope with. Now I don't need to tightly control the processes, the tasks "monitor" smoooches system, alerting both an employee and I about the risks and "floating" time.
But, as it is not sad to say, in such almost perfectly debugged processes the system itself has revealed "links" from which it is necessary to refuse (in the race for efficiency, people suffer). While it is employees performing routine operations, which writing several scripts-deprived of many years of work (such is it, the new reality). Of course, managed to find another use, however, we all understand that this is temporary.
Perennial managerial dilemma: good performance allows companies to better treat employees, or the right attitude to the team leads to high performance?! And remains more than relevant.
Psychologists have found confirmation in practice, staff in some degree even easier when tasks are using "bot": nobody pulls nothing, a measurable and clear result is fixed without excessive reporting. Such peculiar rest from need of constant maintenance of social contacts, satisfaction with work of colleagues, desire to be pleasant to the chief and many other things.
I don't know about you but I am perspective and intriguing and intimidating. After all, fundamental changes in one or another work, with the increasing strengthening of the role of artificial intelligence, will lead to a productivity in which few will be able to compete. Human intervention will be necessary only in an emergency, and the higher his qualification, the greater the probability of preserving the workplace.
If last year, to summarize the work of my Department had to spend weeks on calculations (and we were the best), now, uploading the results with all metrics, trends, in General, relevant Analytics — takes a couple of hours. At this rate, not many are able to work with AI, there is a "evolutionary replacement" of managers-managers, operators control "flight control" :) Most of the data processing and options for further action performs AI, and for the final decision is enough one line Manager.
No wonder the founder of Alibaba said that AI is a more objective and certainly less sensitive compared with men. If earlier the assessment of employees of large corporations was actually exposed in manual mode, now, the maximum of what I can do is to add a comment to the "verdict" pieces of iron. And that if teach" machine " ethics, scientists believe, that this perhaps, here is only as track, in what direction evolves system and what she learns.
Of course, the use of machine learning and neural interfaces is still being implemented only in a small part of the business with maximum digitalization (Telecom, banks, retail), but even at the current level of automation, "conservative" industries will have to adapt to new conditions, which means that the prospect of the next few years is clear. Bots will be able to help a person not only in monotonous and routine operations, but most importantly, in the rapid adoption of complex informed decisions.