What if I told you the most technically flawless AI system I ever built…completely failed?

After deploying over 200 AI POCs across a variety of industries, I learned that the hard way:

The biggest threat to AI success has nothing to do with technology — and everything to do with the people.

Years ago, we built the perfect AI system.

Cutting-edge models. Impeccable accuracy. Seamless deployment.

And then… only 7% of the anticipated user base used it. 

It sat there — untouched — while the business teams quietly returned to their old, familiar Excel & processes.

The system worked. But the people didn’t trust it, didn’t understand it, and didn’t see how it fit into their day-to-day reality.

This is how so many organizations get stuck in Perpetual POC Purgatory — where brilliant proofs of concept never make it into real, scalable use.

The Real Lesson: Scale Comes from Adoption, Not Algorithms

Every Friday morning, I deliver 1 actionable insight to help you navigate the post-AI landscape, simplifying complex transitions into a clear path for business impact. You can click here to subscribe.

After overseeing hundreds of AI initiatives, I developed the 3E Framework — a practical approach to break out of POC purgatory and build AI solutions that people actually use.

This framework is copyrighted: © 2025 Sol Rashidi. All rights reserved.

1. Engage

Don't just announce the AI project. Bring users into the process before deployment. Their early buy-in creates champions who will drive adoption when challenges inevitably arise.

When marketing, operations, and finance teams help select use cases and success metrics, they become invested gardeners rather than skeptical observers.

But whatever you do, don’t let them off the hook. This is more than just having alignment and requirement meetings, this is about making them a part of the project team, making them accountable as a “success criteria” and having names on decks for accountability. 

2. Educate

Theory creates anxiety; hands-on experience builds confidence. This isn't about extensive technical training—it's about demystifying AI and its functioning through guided exposure. They have to be using the POC at least a few months.

The result?

When deployment comes, you observe curiosity instead of resistance among your employees.

3. Embed

Think "AI-enhanced workflows" rather than "AI replacements." The most successful AI implementations feel like natural extensions of how people already work. 

For example, while introducing an AI customer segmentation tool, design it to integrate directly into the exact dashboards and reporting tools that are already used daily. The technology can be more complex, but the adoption becomes seamless because the experience feels familiar.

To conclude, think about AI adoption this way:

Scaling isn't about more sophisticated algorithms—it's about human adoption at every level.

Building AI systems is like planting exotic trees in your garden—you can select the perfect species and use cutting-edge cultivation techniques but if the local gardeners don't understand how to nurture them, those trees will never flourish.

Next time you're facing resistance to AI scaling, remember: technical hurdles are often the easiest to overcome.

The real transformation happens when you nurture the human ecosystem around your AI.

That is how you scale AI across the workforce. 

What's your experience with scaling AI? I'd love to hear your thoughts.

Every Friday morning, I deliver 1 actionable insight to help you navigate the post-AI landscape, simplifying complex transitions into a clear path for business impact. You can click here to subscribe.