Three years ago, ChatGPT introduced generative AI to the public. Today, as more businesses begin to report measurable efficiencies and ROI from AI initiatives, we’re no longer in the experimentation phase. We’re in the execution phase.

I recently shared some reflections on this shift in a new piece for Forbes Tech Council:

📖ChatGPT Turns Three: Five Lessons from the Frontlines of AI Adoption

In the article, I outline five core lessons that have emerged from working with companies as they move from early pilots to integrated, scalable AI capabilities:

1. You can’t scale what you haven’t structured. Pilots are easy, sustained results require ownership, governance, and alignment with busines outcomes.
2. Data is your multiplier, or your bottleneck. Without strong data foundations, even the best tools underperform.
3. Frontline adoption matters just as much as executive vision. Real impact comes from enabling the people closest to the work.
4. Culture and capability are everything. Upskilling, trust-building, and change management are often the difference between value and frustration.
5. Measure what matters. Don’t stop at prompt counts. Track real business impact: cycle time, cost reduction, revenue lift, employee engagement.

These aren’t just theories; they’re patterns we see every day at Evaila. As more organizations get serious about using AI at scale, the ones that will win will treat AI as a long-term capability, not just a tool.

If you're ready to move from experimenting to executing, we'd love to help.

Demystifying AI. Delivering Results.

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