CPMAI™ Phase 4: Model Development

According to PMI, 80% of AI projects fail. Let’s not add yours to the list.

And not every business problem needs the fanciest AI to solve it.

The actual quote from pmi.org's CPMAI training is, "Research consistently shows that 80% or more of AI projects fail to deliver the promised impact or never move beyond prototypes. These failures are not usually caused by the underlying AI technology itself but rather by how AI projects are planned, managed, and aligned to real business needs."

Let's talk about CPMAI Phase 4: Model Development. When implementing AI, too many teams chase the newest, flashiest model — the one grabbing headlines — instead of selecting the right model for their specific business problem and constraints.

Here is a real-world example of an Epic AI Project Implementation Fail.

In 2018, Amazon tried to automate its hiring process with an AI model trained on ten years of resumes from successful employees. But the model learned to favor male candidates—downgrading resumes that included words like “women’s” or came from all-women colleges. Why? The training data reflected historical biases, and the model simply replicated them. Amazon scrapped the tool quietly after realizing it couldn’t be fixed without a complete overhaul. The model wasn’t inherently flawed—it just wasn’t the right fit for a fair and inclusive hiring process.

Your role as a project manager is to steer the team toward a fit-for-purpose solution, not a vanity project. That often means:

🛠️ Matching the model to data quality & quantity you actually have.

⏳ Considering the time and resources to deploy and maintain it.

📈 Ensuring the model supports the business outcome you’re solving for — not just showing off tech.

This is why you need an experienced project manager like me who can speak to the business, tech and AI needs.

Stay tuned for the remaining phases to get addressed and get you educated!