- Eric D. Brown, D.Sc.
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- AI Strategy or AI Graveyard?
AI Strategy or AI Graveyard?
Most companies are burning millions on AI projects that solve problems they don't have while ignoring the expensive problems hiding in plain sight. The difference between AI success and failure isn't sophistication...it's simply picking the right problem to solve first.
Eric Brown
May 13, 2025
In partnership with
Where failed AI projects rest: millions spent, zero problems solved. Don't let your AI initiatives become expensive monuments to good intentions.
These days, boardrooms are buzzing with AI energy. CEOs are green-lighting projects that promise to revolutionize everything. Data scientists are getting hired faster than toilet paper disappeared in 2020. Everyone has an AI initiative.
The results? If history repeats itself, the results will be expensive disappointments wrapped in technical jargon.
I've watched enough companies burn through AI budgets to spot the difference between strategy and spectacle. And it's not what you think.
The AI graveyard starts with grand announcements about "enterprise-wide AI transformation." PowerPoint slides filled with buzzwords like "machine learning," "neural networks," and "digital disruption." Six-figure consulting contracts with the Big Four. Teams of data scientists are hired before anyone asks what problems they should solve.
Sound familiar?
Most companies are solving the wrong problems with AI. They're automating processes that already work fine, predicting outcomes that humans already predict well enough, and building sophisticated hammers when what they needed was a simple screwdriver.
Real AI strategy starts unsexy and stays practical.
AI Strategy begins with looking at your P&L statement, not your technology roadmap. Where are you hemorrhaging money? Which processes eat up human hours without adding value? What keeps your operations managers awake at 3 AM?
One manufacturing CEO told me their biggest AI success came from analyzing maintenance schedules—not customer behavior, not market trends, but maintenance schedules.
The result? They cut unplanned downtime by 35%, saving millions annually.
The investment? Less than what they spent on consultants telling them they needed "comprehensive AI solutions."
The companies that win with AI think small, act smaller, and measure everything. They pick one problem, solve it completely, and then move to the next. They resist the urge to boil the ocean with data.
Meanwhile, the AI graveyards are filled with projects that touched every department, integrated with every system, and improved precisely nothing. These companies hired machine learning engineers before they fixed their data quality issues. They built predictive models for processes they didn't understand. They automated decisions that should have stayed human.
The difference between AI strategy and the AI graveyard isn't sophistication. It's focus.
Strategic AI implementation looks like this:
Finance notices that manual invoice processing takes 10 hours per week. They build a simple model to extract data from PDFs, saving 8 hours per week. They expand to accounts payable. Six months later, they've eliminated 30% of manual data entry.
Graveyard AI looks like this:
HR, Finance, Operations, and Marketing each get AI pilots. No one talks to each other. Each burns through the budget for 18 months. Leadership can't point to a single measurable improvement. The projects get quietly shelved during the next budget cycle.
This is the same outcome of ALL technology implementations for the past 30 years (and longer — but I’ve only seen the past 30 years worth). It’s the same game plan for success. If you can't explain your AI project's value to a 10-year-old, you probably don't have a strategy. You have an expensive experiment disguised as innovation.
The best AI strategies feel boring when you first hear them. They solve mundane problems that cost real money. They start small, prove value quickly, and expand methodically.
Everything else is just expensive theater in the AI graveyard.
If you found this post helpful, consider sharing it with another executive grappling with AI, technology, and data. If you want to explore AI and other Technology strategies, grab some time on my calendar, and let's chat.
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