How AI Is Transforming The Traditional Power Balance In Enterprises

Vitaliy Goncharuk, founder and CEO at 12New.AI–a developer of AI solutions for enterprises. Worked in AI since 2012, has one exit.

Since 2012, I've been involved in integrating various AI solutions into corporations. Before the generative AI (GenAI) boom in 2022, computer vision, machine learning and big data solutions were mainly implemented in low-level technical processes—for example, recognizing license plates on vehicles or facial recognition at turnstiles—that primarily impacted the efficiency of technical operations.

Most managers who made decisions might not have even heard of AI or its subdomains. For them, it was just "another IT solution." But since the onset of GenAI, AI solutions have begun to be actively used at much higher levels, integrating into the "holy of holies": the processes of decision-making at middle and executive levels, from marketing and sales to procurement and in-house legal departments.

These solutions are being used to actively evaluate employee performance, identify unfinished tasks, prepare executive reports and propose management decisions as a "second independent opinion."

All of this has raised hopes for increasing corporations' overall efficiency. AI has emerged as a technology whose effective integration into key business processes has become a long-term competitive advantage for most businesses—and, for many, a matter of survival.

However, in my experience, AI is also causing turbulence in any corporation that begins integrating GenAI, altering the established and traditional balances of power distribution within organizations. In this article, I'll share key observations at the executive level and discuss fundamental changes in the distribution of power within corporations.

Classical information gatekeepers are losing power.

Before GenAI, most users of big data couldn't consume it directly due to its vastness, necessitating entire departments dedicated solely to structuring data and creating various reports. The role of those departments was highly valuable to other stakeholders.

With GenAI, access to big data has been simplified and democratized. Even top managers can now generate various reports and conduct analyses through prompts, iteratively refining them to get better results.

In many cases, this process is faster and simpler than explaining to "information gatekeepers" what is actually needed.

Consequently, traditional information gatekeepers will soon lose power in corporations, especially as more managers enhance their skills in prompt engineering.

Experts are losing exclusivity.

Many corporate executives and professionals have historically gained power through their expert knowledge. However, with the advent of corporate systems that store all company data accessible to GenAI and allow it to be synthesized with global knowledge, the power of experts within corporations is diminishing.

Currently, many employees cross-verify the answers they receive from experts with responses from LLM systems as a "second opinion." I've noticed that some are beginning to consult corporate LLM knowledge systems without contacting internal experts at all.

As a result, expertise is becoming significantly devalued as a tool for gaining traditional power within corporations.

The dynamics of decision-making are changing.

In one corporation, we conducted an experiment: We took the meeting minutes, posed the discussed questions to a well-known LLM and compared the responses with those of the meeting participants.

Approximately 65% of the LLM's answers were similar to the participants' responses, and some were even better.

While this invites certain speculative organizational conclusions, LLMs will increasingly participate in such meetings in the long term—complementing and sometimes replacing human input—which will significantly reduce classical bureaucratic maneuvering.

For instance, integrating LLM transcription of meetings with the automatic generation of action points has eliminated the role of meeting secretaries, making meetings more dynamic and agile.

Operational management has less influence over executives.

Historically, the influence of operational management was based on their proximity to "primary information" and their ability to process it for easier comprehension at the executive level. With the development of various agents—from marketing to project management—the influence of operational management is narrowing.

While it may still be challenging to collect primary information without operational managers in the short term, this is changing, especially in areas where independent sensors (like surveillance cameras) can be deployed or data can be collected directly from front-line employees.

I predict that operational managers will restrict their focus to operational efficiency metrics. They will have diminishing power to influence data assessment, collection and interpretation, all of which will be handled by GenAI solutions reporting directly to middle and executive levels.

Companies are restructuring to fit AI, not vice versa.

In old-school companies, AI solutions could typically be customized during integration to fit managerial and organizational specifics.

The situation has changed significantly over the past five to 10 years. Popular IT and AI solutions have become so expensive to customize and have started to embody the most modern and effective organizational approaches in their "standard packages" that corporations are now adapting themselves to these solutions.

Essentially, best practices in management and organizational structures are spreading not through training, books or education but through software and AI—under which, it's cheaper to adapt than to customize.

Where is all this heading?

IT solutions powered by AI and automation at various levels are significantly increasing their influence and decisiveness. From current projects that I've observed, I predict the power determining the qualitative development of corporations is shifting from the operational level to executives and, unexpectedly, to IT departments recently considered service units responsible for infrastructure.

Most of these departments are not prepared for such a role. Only those who understand the business not just at the technological level but also at the level of business processes (i.e., business architecture) are managing effectively.

This is why many corporations have started introducing positions like chief AI officer instead of elevating the formal role of IT departments. Individuals in such positions can have substantial influence. In the long term, the proliferation and integration of AI will "program" the efficiency and quality of many business processes and, overall, the competitiveness of corporations.

As LLMs from companies such as OpenAI and Anthropic become increasingly sophisticated—which I am confident they will—the power shift toward executives and AI departments will accelerate. Other departments will become more operational and less strategic.

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