Beyond the Buzz: How to Actually Measure AI ROI in Your Organisation

Let’s be honest – we’re all a bit tired of the AI hype train, aren’t we?

Every conference, every LinkedIn post, every vendor pitch seems to promise “exponential productivity gains” and “revolutionary transformation.” But here’s the thing : most companies still can’t prove their AI investments are actually working.

The Reality Check We All Need

I recently came across some eye-opening research that made me pause. While 58% of data and AI leaders claim they’re seeing exponential productivity gains from AI, very few are actually measuring these improvements properly. It’s like saying you’re getting fitter without ever stepping on a scale or timing your runs.

Think about it – when was the last time your organisation ran a controlled experiment to test AI productivity? If you’re like most companies, the answer is probably “never.”

The Goldman Sachs Reality Check

Here’s what real measurement looks like: Goldman Sachs actually studied their developers using AI coding tools. The result? A solid 20% productivity increase. Not exponential, not revolutionary – just a meaningful, measurable improvement.

That’s the kind of honest assessment we need more of. Because here’s the uncomfortable truth: if AI were really delivering exponential gains, we’d be seeing massive layoffs across industries. The employment statistics tell a different story.

How to Actually Measure AI Impact

Start with controlled experiments. Here’s a simple framework I recommend:

• Group A: Uses AI tools without human review
• Group B: Uses AI tools with human review
• Control Group: Works without AI

Run this for 30-60 days and measure actual output quality and speed. Yes, it’s more work upfront, but it’s the only way to get real data.

Don’t just measure speed – measure quality too. If your AI helps write blog posts 10x faster but they’re boring and inaccurate, that’s not a win. It’s actually worse than doing nothing.

The Questions You Should Be Asking

Before your next AI budget meeting, ask yourself:

• What specific tasks are we using AI for?
• How are we measuring the before and after?
• What are our “liberated” employees actually doing with their freed-up time?
• Are we tracking both quantity AND quality of output?

The Bottom Line

I’m pro-smart AI investment. And smart investment means knowing what you’re getting for your money.

The companies that will win in the AI race aren’t the ones with the biggest AI budgets – they’re the ones who can prove their AI actually works. Start measuring today, because the honeymoon period of “trust us, it’s working” is officially over.

What’s your experience been with measuring AI ROI? I’d love to hear your stories in the comments.