Why Your AI Maturity Model is Outdated (And What to Do Instead)

For the past decade, business leaders have been obsessed with measuring AI maturity through traditional corporate lenses: governance, strategy, and IT readiness. But here’s the inconvenient truth: AI adoption isn’t happening in boardrooms—it’s happening on employees’ laptops, phones, and even their personal ChatGPT accounts. And most of it? It’s happening outside IT’s control.

Welcome to the age of Shadow AI.

AI Adoption is Happening From the Bottom Up

Think about how technology adoption has played out over the last decade. In most cases, consumers embraced new tech way before corporations did.

• Employees started using Dropbox and Google Drive before IT rolled out “official” cloud storage.
• They adopted Slack and WhatsApp groups before enterprise messaging tools were even considered.
• And now? They’re using ChatGPT, MidJourney, Notion AI, and AutoGPT to enhance their productivity—whether their company allows it or not.

This isn’t a fringe phenomenon. A 2024 Gartner study found that 57% of employees regularly use AI tools at work, even if their employer has no AI strategy.

So why are most AI maturity models still measuring AI adoption from the top down?

The Problem With Traditional AI Maturity Models

Most corporate AI assessments follow the same playbook:

• Do we have a corporate AI strategy?
• Are our data governance policies in place?
• Have we invested in AI-ready infrastructure?

And while these questions are valid, they completely miss the reality on the ground. In many cases, companies scoring "low" on AI maturity are actually full of employees already using AI to automate tasks, summarize reports, draft emails, and even analyze data.

Yet, since these tools aren’t officially sanctioned, they remain invisible in most AI assessments.

So what if we flipped the script? What if, instead of measuring AI maturity from the boardroom, we started measuring it from the cubicles, Slack channels, and Zoom meetings where AI is actually being used?

A New AI Maturity Model: "Organic AI Maturity"

Instead of focusing on top-down AI governance, an Organic AI Maturity model measures real-world AI adoption from the workforce up. Here’s what it looks like:

1. AI Penetration in Workforce Productivity

How many employees are already using AI tools in their daily work, whether officially approved or not?

• What types of AI tools are they using? (ChatGPT? Grammarly AI? AI-powered Excel macros?)
• Are AI-driven automations reducing workload?
• Is AI usage widespread or concentrated in a few power users?

2. AI’s Influence on Decision-Making & Workflows

Are employees trusting AI recommendations when making decisions?

• Is AI being used to prioritize tasks or analyze data?
• Are team workflows being restructured to take advantage of AI’s capabilities?
• Are AI-driven insights shaping strategic choices?

3. Organizational Attitude Toward Shadow AI

Is the company embracing AI-powered productivity, or is it blocking AI tools out of fear?

• Are employees rewarded or penalized for using AI tools?
• Does leadership recognize that AI is already in use, even if unofficially?
• Is there an effort to bring AI tools into the company securely and responsibly?

4. IT & Security Integration of AI Tools

Instead of banning AI tools, is IT working to integrate them safely?

• Are companies formalizing Shadow AI tools into official workflows?
• Is there a balance between security and innovation?
• Are IT teams collaborating with employees to understand their AI needs?

5. AI Learning & Upskilling at the Workforce Level

Are employees actively learning how to use AI?

• Are they self-learning, or is training provided?
• How much AI knowledge is spread across the company?
• Are employees experimenting with AI beyond their immediate tasks?

Why This Matters More Than Ever

Companies that embrace Organic AI Maturity will have a competitive edge over those that stick to outdated top-down AI strategies. Why?

1. Employees are already ahead of corporate policies—ignoring this reality leads to inefficiencies and missed opportunities.
2. AI adoption is happening whether you measure it or not—so you might as well measure it properly.
3. Organizations that resist AI adoption will fall behind—if employees aren’t empowered with AI tools, they’ll either leave or work less efficiently.

The Future of AI Maturity is Bottom-Up

Instead of asking, "How mature is our AI strategy?" companies should be asking:

• How much AI adoption is already happening, and how can we support it?
• What AI tools do employees actually use, and how can we integrate them safely?
• How do we build an AI culture that empowers employees instead of restricting them?

The future of AI maturity isn’t about corporate strategy decks or five-year AI roadmaps—it’s about recognizing the AI revolution that’s already happening on the ground.

Companies that understand this will move faster, innovate better, and empower their employees in ways their competitors won’t.

And that’s real AI maturity.

What’s your take? Are you seeing employees adopt AI tools before your company has a formal AI strategy? Drop a comment and let’s discuss!