What "value" is AI delivering and how to prove it.

**What **“Value” is AI delivering and how to prove it? In my last post I promised to unpack my AI Adoption framework. Let's start with the hardest one: VALUE.

Not "productivity" or "efficiency." Actual, measurable business value.

This summarizes the steps I took at ALM, the result proved that it works: taking the company through a successful PE exit, **increasing **revenue significantly,**reducing **cost meaningfully, and scaling the user base. Here's what I learned about categorizing and capturing AI value.

• **Employee Value **made our teams faster, more efficient. We saw wins here, automated workflows, smarter tools. But here's the reality:Time Saved is NOT Money Earned. At best, you're optimizing expenses, not creating new revenue.

• Clear ROI embedded intelligence into our core products and processes. This is where we saw measurable returns. Real dollars we could track from investment to outcome.

• Strategic Value created new products and business models. Highest risk, highest reward. For us, this meant AI-driven intelligence products that became new revenue streams, not just incremental improvements.

The turning point came when I stopped reporting "30% faster ticket resolution" and started showing "$20M added through AI-driven products." Same technology. But one gets you a pat on the back. The other gets you a seat at the strategy table.

Move the needle: Focus 80% of your AI investment on ROI and Strategic Value. That's where AI connects directly to revenue, product differentiation, and financial outcomes that boards actually care about.

Employee value is extremely important, but a singular focus on it can be a long, winding road to proving overall business impact. In fact, focusing on ROI and strategic value creates quick wins and measurable success that speed up employee adoption significantly.

In my next post, I'll share some practical templates/tools we used, from board-level visuals to prioritization framework. Follow me and stay tuned.