Why The AI is failing in Electrical Utilities

AI in Electrical Utilities: Why Domain Expertise Still Rules the Game

Let’s get one thing straight — AI is like a child. It can learn incredibly fast, but only if you give it curated, meaningful data and the right guidance. Without that, it’s just guessing.

And who provides that guidance? Not just data scientists — but domain experts who actually understand what the data means.

Why Domain Knowledge Matters

Can you tell an IT person to write an algorithm to estimate the failure of electrical equipment? The answer is no. And honestly, it should be no.

No data scientist can accurately interpret transformer parameters without understanding the electrical behavior behind them. You need real engineering and field experience to make sense of that data. Otherwise, it’s like asking a chef to perform heart surgery because both use knives.

When AI Hallucinates

We’ve already seen cases where Generative AI produced fake reports for government institutions. There are also instances where AI systems accidentally wiped company databases, and when asked to plot a simple line chart, they gave different random answers every time.

So no, AI isn’t magical. It’s powerful — but only as reliable as the expertise and data behind it.

The Real Success Stories

Some companies have done it right. Palantir Technologies and Siemens have built robust AI/ML systems by deeply integrating domain experts into the process.

And while everyone is rushing to jump on the AI bandwagon, remember this: NVIDIA is selling the shovels during the gold rush. Hardware is the real hero of this story.

The AI Hype Machine

Today, every other piece of software claims to be “AI-powered.” Even a simple forecasting script is branded as AI to inflate its market value.

Let’s be honest — AI and ML aren’t new. The algorithms have existed for decades. What’s really changed is hardware — GPUs have supercharged computation, giving existing algorithms the boost they always needed.

Now every CEO who can’t even write a “Hello World” program wants AI “everywhere. ”Some companies managed it well. Most didn’t. Promises were made, deadlines were missed, and products were rushed out the door — all in the name of AI.

AI Terminology Overload

We used to call it extrapolation. Now it’s called prediction or forecasting. Same math, fancier name.

So, Should We Give Up on AI?

Absolutely not. But we need to get smarter about it.

If you’re an engineer, learn the basics of AI. If you’re a data scientist, learn the engineering principles of your domain. attaching a fancy library will not solve the problem .AI doesn’t replace expertise — it amplifies it.

Practical Advice for AI Engineers

• Build rugged, clean data pipelines. Garbage in = garbage out.

• Optimize your code for GPU execution. Understand what runs best on CPU vs GPU.

• Scale infrastructure with GPU compatibility in mind.

• Learn to choose the right GPU — not every NVIDIA card is made for training. (For instance, using an “L-series” GPU for heavy data training isn’t ideal.)

• And please — read the documentation. You’d be surprised how many “AI engineers” skip that part.

Behind the Curtain: The Unsung Heroes

While everyone talks about ChatGPT and neural networks, custom ASICs and FPGAs quietly power most AI inference and training at scale. These specialized chips are the hidden heroes making real-time AI possible.

The Final Word

AI implementation can break budgets, not just code. We often underestimate the computation cost and infrastructure demands until it’s too late. Marketing Team will sell goat and rename it as Unicorn. don't get fool ! do detailed analysis if not then do contact us for analysis. we will help you analyze the System.

So, before you jump into AI, ask yourself —Do I understand the data, the domain, and the hardware behind it? If not, maybe it’s time to learn.

Because AI may be powerful — but like a child — it still needs responsible parents to raise it right.

Interested in SAIEN, Request for a callback.

Tejeshw Vardhan Email: tejeshw@saien.in

Contact No: +91-9510917834