How do you measure the ROI of AI investments?
Short Answer
AI ROI is measured by comparing the total cost of AI development and deployment against quantifiable benefits including revenue uplift, cost reduction, productivity gains, and the fair value of intangible assets created.
Full Explanation
Measuring AI ROI requires a multi-layered approach because AI investments create both direct financial returns and indirect intangible value. Direct ROI is relatively straightforward: compare development costs (talent, compute, data acquisition) against measurable outcomes like revenue increase, cost savings from automation, or reduced error rates. However, the full picture requires valuing the intangible assets AI creates. A proprietary recommendation engine, for example, may increase customer lifetime value by 30% — that uplift in customer relationship value is an intangible asset gain. Similarly, AI-driven process improvements create organisational capital that compounds over time. Best practice is to track AI ROI across three horizons: immediate efficiency gains (months 1-6), revenue and margin impact (months 6-18), and strategic intangible asset accumulation (18+ months). Many companies focus only on the first horizon and undervalue their AI investments. The Opagio platform's questionnaire scoring captures AI's contribution to each intangible asset category, enabling a more complete ROI picture than traditional financial metrics alone.
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