Did AI Deliver Value in 2025? Here’s How to Tell.

Author

Charlene Li
January 06, 2026

As we wrap up 2025, I'm willing to bet your inbox is flooded with year-end recaps, performance reviews, and demands for ROI calculations on every initiative your team launched this year.

And if you're leading AI transformation, you're probably staring at spreadsheets wondering if you're even tracking the right numbers.

Leaders get so caught up in calculating traditional ROI that they miss the signals that actually predict long-term AI success. They're looking at the wrong dashboard entirely.

The ROI Trap

Don't get me wrong, return on investment matters. If you can't show value creation, you shouldn't be investing resources. But here's the thing about AI: it's fundamentally different from traditional technology investments.

When you installed that new CRM system five years ago, you could draw a straight line from cost to benefit. With AI, the value compounds in ways that don't fit neatly into existing measurement frameworks. AI disrupts how work gets done, which means it disrupts how we should measure success.

Think about it; if someone had asked you to calculate the ROI of email adoption in 1995, you might have focused on reducing postal costs. But the real value of email came from fundamentally transforming how business communication happens. It’s not always easy to know which metrics to track when the level of transformation is so massive.

What You Should Actually Be Tracking

Based on what my “Winning with AI” coauthor Katia Walsh and I are seeing work across organizations driving real AI transformation, here are the metrics that actually tell you if you're winning:

💫 AI projects launched.
How many of your AI experiments are actual production with the intention of creating value? If you're stuck in perpetual pilot mode, your problem isn't the technology … it's your lack of commitment. Track not just how many projects are in play, but which ones your organization actually creating value. 

🏎️ Adoption velocity. 
Are people choosing to use your AI tools, or do you have to mandate compliance? I'm talking about organic spread, when someone in marketing tries a tool and tells three colleagues in sales who start using it without HR sending a single training email. 

🛠️ Workflow transformation depth. 
Are you using AI to speed up existing processes, or are you fundamentally reimagining how work gets done? There's a massive difference between "our reports generate 40% faster" and "we've eliminated three entire process steps because AI changed what's possible." 

🚀 Learning velocity. 
How fast are your teams discovering new applications and iterating toward value? Organizations that compress experimentation cycles from months to weeks create compounding advantages.

🏗️ Building block progress. 
Where are you in developing the foundational capabilities—mindset, skillset, toolset, and decision-set? These aren't nice-to-haves. They're the infrastructure that determines whether AI delivers sustained value or becomes yet another abandoned initiative.

Why This Matters Now

To be extremely transparent, traditional metrics make AI transformation look expensive and risky. They're designed for a world where technology augmented existing processes. AI does more than just augment: it fundamentally transforms how value gets created.

If you only measure ROI, you'll underinvest in the very capabilities that create sustainable competitive advantage. You'll optimize for short-term wins and miss the strategic opportunities that define market leadership.

Your Reflection Moment

As you close out the year, don't just ask "Did we get positive ROI on our AI investments?" Ask these questions instead:

  • Are more teams adopting AI and becoming AI fluent without being told to?

  • Have we fundamentally changed how work gets done in any area?

  • Are we learning and iterating faster than we were six months ago?

  • Have we built capabilities that will compound over time?

These are the signals that predict whether your AI transformation will accelerate in 2026 or stall out.

The organizations winning with AI are the ones measuring what actually matters, and building the capabilities that turn AI investment into sustained competitive advantage.

So before you rush into 2026 planning, take time to reflect on what you've actually accomplished this year. Not just the ROI numbers, but the real progress on transformation.

Because here's what Katia and I know: AI is an industry disruptor. So naturally, the ways we measure it should be different too.

💭 Your Turn

What metrics are you tracking that tell the real story of your AI progress? I'd love to hear what's working for you.

What I Can't Stop Talking About

  • Leaders need to get uncomfortable in 2026. If you’re not uncomfortable, you’re not leading. Here’s how to stretch outside of your comfort zone. 

  • I’m taking time to pause and reflect as we head into the new year. It’s been a big year, and before I hit the ground running, it’s important to take a moment to acknowledge what’s come before. Let me know what you’re reflecting on this week, too!

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