Hi {{first name | reader}}!
Here's something we see all the time: Someone decides they need AI. They pick a tool. They build something. And then... it doesn’t quite live up to the hype. 💀
Why? Because they skipped the most important question.
Why are you doing this?
Not (yet) "why AI?" but:
Why this project?
What specific problem are you solving?
What does success look like?
Most people can't answer these questions clearly, and that's why their AI projects fail.
Because not all problems are best solved with AI.
What Makes a Good WHY?
A good WHY has three parts:
Specific problem + Measurable impact + Clear who it affects
Here's what that looks like in practice:
❌ A Bad WHY:
"We need AI" (too vague)
"Everyone else is using ChatGPT" (not a problem)
✅ A Good WHY:
"Our team spends 5 hours/week searching for documents during client calls"
"If key employees leave, operations crash because critical knowledge lives in their heads"
See the difference?
A Real Example 👇
When Morgan Stanley introduced AI tools for financial advisers, they didn't start with the technology.
They started with people.
The head of AI spent countless hours with advisers to understand their pain points and how AI could actually help. The tool wasn't mandatory. Each adviser could decide whether and how to use it.
The result? Strong buy-in and engagement throughout the organization.
The lesson: Employee-centric organizations that prioritize enhancing the employee experience are more advanced in employee motivation, retention, and build better AI solutions.
Try This: Your Pain Point Scan 🔎
Take 5 minutes right now to answer these three questions:
What do you keep postponing?
What can you NOT stop doing?
What do people ask your help with?
These are three potential touchpoints for implementing AI. By tackling each one you could…
Reduce the pain caused by #1
Supercharge your abilities in #2
Share your wisdom and knowhow with #3 (for free or for a fee)
Now imagine: How would your work look in a year if you had created solutions for each!
Want to Go Deeper?
We covered this topic in depth during our last workshop. You can access the full session here: workshop.purposedriven.ai
It includes 👇
Step-by-step mapping exercises
Real examples of good vs. bad WHYs
How to identify where AI actually fits in your workflow
Next time, we'll talk about the WHAT & HOW. Once you know your WHY, it’s time to look at what you need to focus on for an optimal AI build. 💪
Until then,
Maaria & Josué
P.S. Just because everyone's doing something doesn't mean you should. And it definitely doesn't mean they're doing it well. Start with WHY, not with trends.