The AI Pandemic

During the pandemic, the virus spread fast. So did expertise. Almost overnight, everyone had an opinion, a prediction, or a theory, and every day brought a new one. Some of it held up. Most of it did not. It got harder every week to tell what was real. Looking at AI today, I keep wondering whether expertise is once again spreading faster than understanding.

AI Expertise Is Growing Faster Than AI Understanding

AI has gone from a topic for researchers and engineers to the center of almost every business conversation. Conference, roundtable, vendor pitch, the thread always finds its way back to AI. That part is fine. AI will reshape how companies operate.

A quick look at LinkedIn tells its own story. Titles that barely existed three years ago are suddenly everywhere. AI Architects, AI Strategists, AI Coaches, AI Trainers. Some of these people have spent years in the field. Others seem to have arrived last month. Every technology wave creates new experts, but few have created them this quickly.

What bothers me is the gap between two speeds: how fast organizations are trying to adopt AI, and how slowly they are building the foundation to use it well. Most of the energy goes to what AI could do. Almost none goes to what AI actually is. Leaders still use "AI" as if it were one thing, when it covers decades of very different approaches: machine learning, predictive analytics, recommendation engines, computer vision, and now large language models, all packed under one word. When the word is that loose, expectations drift.

Why Enterprise AI Fails Without a Strong Foundation

Today's excitement is mostly about LLMs. And there is one property of these systems that rarely makes it into a business conversation: they are probabilistic by design. That is how they work, not a flaw to fix. It is also why they will sometimes be wrong with complete confidence, and why they get less reliable as the data, processes, and governance around them get weaker.

Here is where most companies get it backwards. They treat AI as something that will cover up problems they already have. Fragmented data, disconnected systems, duplicated records, processes that change from one team to the next. None of this is new. Generative AI did not create it, and in most companies it is still unsolved. The hope is that AI will sit on top of the mess and turn it into intelligence. In reality, it inherits the mess and often scales it faster than any human process ever could.

I see this most clearly in the distance between a demo and production. The demo is clean: good data, narrow scope, a controlled question. Production is the real company, with all of its inconsistency, and that is where the impressive prototype quietly falls apart.

AI Readiness Starts with Data, Processes and Governance

So here is the question I would put to any leader. Forget which model, forget which agent. Is the organization actually ready to benefit from either? A few honest checks:

• Do we trust our own data?
• Do we have one consistent view of our customers, our people, and our operations?
• Do we know where human judgment is still non-negotiable?
• Do we know which decisions should never be handed to a model?

These are duller than a keynote. They also matter more. In most cases, readiness has little to do with the model and far more to do with something basic: whether data, processes, and systems are connected well enough for the model to operate on something reliable.

Moving Beyond AI Hype to Business Reality

AI will keep transforming industries, I have no doubt about that. What I doubt is how many companies will get real results if they keep staring at the technology and ignoring the foundation under it. Without that foundation, AI becomes one more buzzword that produces more talk than value. With it, it becomes one of the most powerful tools a business has ever had.

Like every pandemic, the noise eventually fades. What is left is reality. The companies that build on reality will get something real out of AI. The ones that build on hype will move on to the next buzzword.