Why Executive AI Experience Is the Best Predictor of Project Success
8 min read
·
Jul 30, 2025
Budgets and vendors matter in AI projects. But the best predictor of success is simpler.
Does the person writing the check use AI every day?
The Difference Leaders Make
One client told us, “I stayed up two nights straight building automations.”
This was not a junior engineer. It was an executive. They had experimented with prompts, tested workflows, and built automations themselves. They knew what worked. They knew where “good enough” landed.
These leaders are grounded in reality. They understand AI is powerful but imperfect. They expect iteration, not magic.
Contrast this with executives who have never touched ChatGPT but want to deploy AI across the organization. They expect flawless results. They get frustrated when adoption requires structure and guardrails.
AI Adoption Starts at the Top
Executives who experiment with AI:
Set realistic expectations for their teams
Model curiosity and learning
Invest where AI can add real value
Their hands-on experience turns AI adoption into strategy, not theater.
The Quiet AI Power Users
Inside most organizations are hidden champions. They are not executives. They are employees experimenting on their own.
A marketer using AI to draft campaigns
A salesperson automating lead scoring
A finance analyst enhancing spreadsheets
These power users often create more value than a vendor demo. A teammate saving two hours per day has real impact.
How to Harness This
Find employees already using AI.
Share their wins across the company.
Connect them with executives who understand AI. Together they create roadmaps grounded in practice.
The Best Clients Say
The strongest conversations start with, “We’ve been experimenting, but now we need help scaling.”
That is the signal of a client ready to succeed.
Closing Thought
AI adoption is not about hype or large budgets. It is about leadership grounded in experience and teams already proving value.
The best predictor of success is simple. Do the decision makers use AI themselves?
If the answer is yes, the path is clear.
