The industry is currently obsessed with AI ROI, but we're measuring it through the wrong lens. Most leaders are still trying to justify AI spend by looking for immediate headcount reductions, 🤦🏻♂️ a "subtraction" mindset that fails to capture the "multiplication" happening beneath the surface. True AI value isn't just about doing the same things with fewer people; it’s about doing things that were previously impossible due to scale, speed, or complexity.
To find the real ROI, we have to look at "unlocked capacity." Look at your existing backlog! When an engineer uses AI to handle boilerplate code, the value isn't the hour saved; it’s the breakthrough feature they finally had time to design. When a marketer automates personalization, the value is the revenue from a segment that was previously too expensive to target. If your metrics can't account for improved decision quality or accelerated time-to-market, you aren't measuring ROI; you're just being penny-wise and pound-foolish.
🧠 The Value Trap: Focusing solely on labor cost savings ignores the broader strategic impact of AI on business growth.
⚡ Qualitative Metrics: ROI must include "soft" gains like employee satisfaction, customer experience, and risk mitigation.
🎓 Speed as Currency: Measure the reduction in "time-to-insight" and how that accelerates your competitive response.
🔍 Hybrid Frameworks: Successful CIOs are combining traditional financial KPIs with new "innovation velocity" metrics.
https://www.cio.com/article/4106788/ai-roi-how-to-measure-the-true-value-of-ai-2.html
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