The Great Knowledge Gap: Are We Swapping Expertise for "Received Wisdom"?

I’ve been thinking a bit lately about how Artificial Intelligence is reshaping the landscape of professional knowledge, particularly in the IT consulting sector—the environment I know best.

While AI is undeniably a powerful tool, I believe it is creating a widening Knowledge Gap. To explain this, I distinguish between two types of knowledge: "Researched Information" and "Received Information."

Here is why this distinction matters, and why we need to talk about it.

The Era of "Researched Information"

Not long ago, if a consultant or IT professional needed to solve a complex problem or map out a project, the process was manual and rigorous. We had to dig through documentation, scour forums, and read technical blogs to find a scenario that mirrored our own.

This required effort. Crucially, it forced us to understand the context. To find the answer, you had to understand the question, the variables, and the potential consequences of every configuration. This friction resulted in growth. The professional acquired knowledge because the information was actively researched, digested, and understood.

The Shift to "Received Information"

With the advent of GenAI, the consulting process has changed drastically in terms of both quantity and quality.

1. The Quantity: The Illusion of Competence Today, the perceived limits of an IT worker’s knowledge are exponentially amplified by their "friend," the Generator. Internal teams and managers, armed with GenAI, now feel empowered to tackle tasks they previously would have outsourced to specialists.

When a team encounters a small, unknown operation, they no longer spend nights studying it from scratch. They ask the AI. Empowered by this (sometimes superficial) knowledge, they attempt procedures internally that used to be the domain of external consultants.

Looking ahead 5 to 10 years, as these tools become vastly superior, I suspect this will significantly reduce the volume of requests for external consulting. Why hire an expert when you feel like one yourself?

2. The Quality: The Rise of the "No-Content Consultant" However, the impact on the consultants themselves is even more concerning. I am witnessing the rise of the "No-Content Consultant."

We are at risk of losing the concept of true Expertise. I see professionals executing tasks based solely on a list of steps received from an AI assistant.

• The problem: Because the consultant didn't research the solution, they skipped the "comprehension" phase.

• The result: There is no effort to understand if the solution actually fits the specific nuance of the scenario.

We passively receive steps and apply them without verifying sources—often because if you ask an AI for sources, you get "broken links."

Let’s be honest with each other: How many of you have pasted a command into a terminal without first verifying what every single flag and option actually does?

I have done it. But that is dangerous ground.

The Echo Chamber in the Meeting Room

This phenomenon is most visible in meetings. When a topic comes up that is off-agenda or slightly outside the core expertise of the room, I notice a pattern. Participants—consultants and clients alike—start responding with phrases clearly freshly baked by Gemini, GPT, or Claude.

It creates a strange loop. I have found myself saying something suggested by AI, only to hear someone else repeat the exact same concept moments later, convinced they are adding something new. They didn't realize they were repeating me, because they didn't understand the concept I explained—they only recognized the "generated" keywords they just read on their own screen.

A Call for Balance

I am not anti-AI. In fact, I use it to refine my thoughts and polish my writing (like this very post). But I try to use it to enhance my skills, not replace the background work required to form an opinion.

We need to ensure we are still building Researched Information foundations, or we risk becoming a workforce that knows how to ask for answers, but doesn't understand the solutions.

What do you think? Are you seeing this "hollow expertise" in your field, or do you think the efficiency gains outweigh the loss of deep understanding? Let’s discuss in the comments.

 

Disclaimer: The critical thoughts, opinion, and human reflection in this post are 100% mine. The grammar, however, has been prettified by GenAI because, let's face it, it writes better than I do. ;)