The estimates issued by Gartner indicated that by 2026, 20% of the artificial intelligence institutions will use their organizational structures, which may lead to the abolition of more than half of the functions of the middle administration; It is also a trend documented by Harvard Business Review and Shrm. The question that initiates in my mind: Does this mean the end of the role of these jobs or the beginning of a smarter formulation? As we analyze business, I remember myself and the honorable readers that future expectations illuminate the way, but they do not lead us to proven facts; And that technology speeds up the movement, but it does not give us the direction or meaning; Because they are basically a human industry.
The truth is that artificial intelligence does not erase the functions of middle management in institutions and companies as much as it transmits the center of its weight and is reshaped. The tasks that consumed the occupants of these jobs, such as managers and executives, for example, for years – schedule, follow up on developments, routine approvals, initial analysis, and scrutiny – are exactly what the algorithms are mastering today, and what smart models will master tomorrow faster and more accurate. As this burden is transferred to the machine, the supervisory role of these functions is transformed from “procedures” to “systems engineers” to decide what is being trusted, what is supported, and what should remain human because it is conditional on the context, values and creativity. With this logic, the question is not: How much is a manager we dispense with? Rather: What components do we transfer to the machine without dispeling our cognitive capital and professional development paths?
From the corner closest to what I came out after reading the article of Faisal Hook, published in Fast Company, last week, I see that the practical summary is not in emptying the functions of middle management; Rather, in redefining it about three highly attributed jobs: the first of which is a “coordinated” that controls the rhythm between man and the machine, and determines when we trust the outputs of the forms and when we go beyond them; The second is a “change agent” that reports and designing operations, and deals with ambiguity as an opportunity; The third is a “trainer” that builds digital culture, the skills of critical thinking, moral verification and communication, so that human learning curve remains faster than the tool development curve. At this intersection, the middle administration becomes a lever, not just a censorship of the effort.
According to these data; We must come out from theoretical to more practical procedures by re -describing the functions of middle management and re -directing them, as traditional indicators and roles are no longer predicted by impact. The most important criterion is the ability to adapt, fluency in artificial intelligence tools, discipline in verification and treatment of any failures that may occur; Therefore, we need new paths and roles that translate the philosophy of the work of these jobs into the leadership of smart integration between man and the machine, such as dismantling of flows and classifying their steps into “automatic/backed/human,” purely human “, and the adoption of a matrix of distribution of responsibilities (Raci) that determines” whoever accomplishes, who adopts, who is consulted, who is informed “, with the determination Human risk and context. In addition to the creation of a use record of artificial intelligence at the level of the team (task/tool, guidance/result or risk) to build a cumulative learning cumulative knowledge, continuous training in verifying outputs and risk management, data governance that guarantees privacy, quality and scrutiny. These are not only operating details; It is the new language that the new roles should speak of the functions of the middle administration in order to be able to control the rhythm between the efficiency of automation and the wisdom of man.
Finally; Governance remains a safety network that gives speed its meaning: professional performance indicators (KPIS) for each role, information maps known, specific Hitl points, and a clear decision on what is taken and what remains always human, with a comprehensive documentation that guarantees the ability to scrutinize and trust. Through this we measure two goals together: efficiency is seen in the time of decision and completion courses, integrity and development seen in the participation of employees, while monitoring the early signals of job combustion so that the automation sparkle is not hidden, so that the speed of the machines goes and the decision remains for humans.
