Hey friend,
You saw a demo. You got excited. You bought the tool. And now six months later you are paying for software your team barely uses.
That is the pattern. It is playing out across companies right now, and it is costing people real money.
Here is how it happens. Someone hears about AI and goes looking for what to apply it to. Suddenly every problem in the business looks like it could be solved by an AI tool. The hiring process. The customer support backlog. The reporting. The onboarding. Pick your pain point and there is a vendor ready to sell you the AI solution for it.
The problem is not the excitement. The problem is starting with the tool and working backwards to the problem. When you do that, you skip the one step that actually matters: figuring out what is broken and why.
Let's Also Name What AI Actually Is
A lot of what gets sold as AI right now is not AI. It is automation. Rule-based logic. If-this-then-that workflows with a language model bolted on for the pitch deck.
That is not a criticism of automation. Automation is genuinely useful. But if you are paying AI prices for automation value, and skipping the root cause work that would tell you which one you actually need, you are getting hit twice.
What the Numbers Actually Tell You
More than 80% of AI projects fail. That is twice the failure rate of regular IT projects. And 48% of C-suite executives now call AI adoption a "massive disappointment" on ROI, up from 34% just last year.
But here is what those numbers do not say: most of those projects were not killed by bad AI. They were killed by processes that were already broken before the AI showed up. The AI just made the failure more expensive and more visible.
If your customer support team is overwhelmed because your product has a confusing onboarding flow, an AI chatbot does not fix that. It automates the confusion. If your sales reporting is a mess because nobody agreed on definitions three years ago, an AI analytics layer does not fix that.
It just produces faster wrong answers.
One Thing to Do This Week
Before you greenlight any new AI purchase, answer this question without mentioning technology: what exact problem am I solving, and why does it exist?
If you cannot answer that clearly, you are not ready to buy. You are ready to diagnose.
That is where the real work starts. Reply to this email and tell me what you are trying to solve. I read every reply.
Until next week,
Boubacar
Sources:
[1] RAND Corporation, "The Root Causes of Failure for Artificial Intelligence Projects," 2024. rand.org/pubs/research_reports/RRA2680-1.html
[2] WRITER, AI Adoption in the Enterprise 2026 Survey, April 2026. writer.com/blog/enterprise-ai-adoption-2026/