AI challenges Mnemonic

10/6/2025

MBABusiness AIMnemonic

How to Use This Method

The Memory Palace: The “AI Innovator’s House”

Your memory palace is a sleek, modern, but slightly chaotic house. It’s the headquarters of a startup that went a little too wild with its own AI. You’re going to walk through five rooms, each corresponding to a letter in our SHADE mnemonic.

S - The Study: Where Strategy & Vision are born.
H - The Hallway: Filled with people representing Human Factors.
A - The Kitchen: Where Analytics & Data are cooked up.
D - The Garage: Where projects are Deployed into Reality.
E - The Attic: Where you reflect on Expectations & Ethics.

Now, let’s walk through the house with a story.

The Story: A Tour of the AI House of Errors

Imagine you’re pushing open the front door. This is the story of what went wrong here.

1. The Study (S - Strategy & Vision)

You step into the study, and it’s a mess.

In the center of the room, a CEO is wildly chasing a glowing, buzzing drone labeled “AI Hype” with a butterfly net. He’s completely ignoring the solid gold blueprint on his desk. This is AI hype chasing.
The blueprint itself is blank except for a sticky note that says, “Figure it out later.” This is a lack of AI strategy.
On the wall, there’s a ridiculously complex machine that dispenses a single, useless plastic widget. It’s labeled “Project Chimera,” representing chasing novelty over product-market fit.
The CEO keeps getting distracted, looking out the window at a parade of shiny, marching robots called the “AI Trends,” forgetting his own company’s goals. This is distraction by AI trends.
Finally, you see the company’s stock ticker on a screen, but it’s being fed by a machine that just prints out pictures of cats. The outputs have nothing to do with the business goals. This is the misalignment between AI outputs and business goals.

2. The Hallway (H - Human Factors)

You leave the study and enter a long, crowded hallway.

The walls are covered in complex equations, and the team members are all wearing dunce caps, looking confused. They have underdeveloped AI literacy.
In one corner, a group of employees is nervously building a barricade of office chairs, terrified of a small, friendly-looking Roomba. This is their fear of being replaced by AI.
A programmer is sitting at a desk, sweating, while a robot flawlessly writes code next to him. The programmer looks like he’s about to be found out. This is AI-driven imposter syndrome.
A doctor is looking at an X-ray. A giant red arrow from an AI points to a spot labeled “99.9% PROBABLE FRACTURE,” but the doctor can clearly see it’s just a smudge. He ignores his own eyes and puts a cast on the X-ray itself, neglecting human judgment.
Another employee is sitting in a chair with his feet up, letting an AI write all his emails. One of the emails it just sent reads, “Yes, let’s approve the billion-dollar purchase of rubber chickens.” This is overreliance on AI tools.
At the end of the hall, a manager is frozen in place, surrounded by hundreds of flashing charts and graphs from an AI. He can’t make a decision. He’s suffering from paralysis by algorithmic analysis.

3. The Kitchen (A - Analytics & Data)

You push into the kitchen, and the smell is awful.

The chef is trying to make a gourmet meal, but he’s scooping rusty nails and mud into a pot. This is poor data quality management.
He thinks the oven will cook the meal in 5 minutes, but the recipe book is a thousand pages long and written in ancient Greek. He’s underestimating training complexity.
The chef tastes the foul stew and declares, “Amazing!” A biased feedback loop is making the bad food seem good, amplifying the bias.
The oven itself is a smooth, black cube with no buttons or windows. Food goes in, something comes out, but nobody knows how it works. It’s a dependency on black-box models.
When you ask the chef why the stew is good, he just shrugs and points at the black box. He’s ignoring interpretability.

4. The Garage (D - Deployment & Reality)

You escape the kitchen and enter the garage.

A team of mechanics is trying to attach a massive, shiny jet engine (the new AI) onto a rusty old bicycle (the existing system). Sparks are flying, and it just won’t fit. This is the failure to integrate AI with existing systems.
The company owner is happily paying a bill for the jet engine, not noticing the fine print which includes costs for a runway, jet fuel, and a pilot. He’s misjudging AI adoption costs.
In the corner, a huge, powerful robotic arm is being used for one task: buttering a single piece of toast. It’s a classic case of overautomation.

5. The Attic (E - Expectations & Ethics)

Finally, you climb a dusty ladder into the attic. It’s quiet and spooky.

A salesman is standing in the middle of the room, promising a dusty old crystal ball that it can predict the future with 100% accuracy. He’s overpromising AI capabilities.
He then tries to use the crystal ball as a hammer, confused when it doesn’t work. He’s misunderstanding AI limitations.
All around him are stacks of dusty books, with titles like “Laws of Robotics,” “Regulations,” and “Moral Philosophy.” The salesman is sweating, too scared to open any of them. This is ethical and regulatory anxiety.

As you close the attic door, you have a complete picture of the “AI House of Errors.” To remember the list, just take a walk through the house, room by room, recalling the chaotic scenes you witnessed.