Evaluating Software Performance in the Age of AI

A practical guide for established software companies transitioning to AI.

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How should software leaders evaluate ARR when revenue fluctuates with consumption?

What happens to profitability as AI infrastructure costs scale with usage?

How can companies translate AI productivity gains into measurable business outcomes?

Drawing on OPEXEngine's proprietary benchmark data and findings from a joint AI survey with Bain & Company, the guide examines four interconnected layers of software performance and how AI is changing their underlying drivers.

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Inside the report, we explore:

Overall performance: How the balance between growth and profitability is evolving, and what it means for evaluating the Rule of 40.
Growth drivers: Why consumption-based pricing is making ARR and retention metrics more complex to interpret.
Profitability drivers: How AI infrastructure costs are putting pressure on gross margins and creating new considerations for cost allocation.
Efficiency drivers: Why productivity improvements across GTM and R&D aren't automatically translating into better business outcomes.

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