AI Cost Governance to AI Cost Optimization with Sundeep Goel, CEO, Mavvrik

Ray Rike sits down with Sundeep Goel, co-founder and CEO of Mavvrik, for a deep dive into the second annual AI cost governance research report from Maverick and Benchmarkit. With 30+ years in enterprise software, Sundeep brings a practitioner's view of why AI spend is proving far harder to forecast and govern than cloud spend ever was, and what finance and technology leaders need to do about it.

• Forecast accuracy is getting worse, not better. Only 11% of companies can forecast AI spend within plus or minus 10% in 2026, down from 15% the prior year, even as aggregate AI spend has climbed sharply.

• Unexpected AI costs are already changing business decisions. 49% of companies with AI-powered digital products have had to modify pricing, and 25% have stalled or shelved an AI project due to cost overruns.

• Traditional per-seat and percentage-of-spend pricing models are breaking down. Variable, high AI cost of goods sold is pushing companies toward consumption-based and outcome-based pricing.

• Cost tracking and cost allocation are two different problems. 98% of companies say they track AI costs at an aggregate level, but only about 5% can allocate that spend down to the customer, application, or agent level where it actually drives decisions.

• Cost governance is the precursor, cost optimization is the destination. Drawing a parallel to the 30%+ waste long documented in cloud spend, Sundeep argues a similar magnitude of waste exists in AI spend today, and that dynamic model selection, prompt caching, and rate optimization are the next frontier.

• ROI has a solvable half and a harder half. Cost is measurable today; value remains subjective and requires a company-specific framework to quantify.

Ray and Sundeep close with three rapid-fire questions on who should own AI ROI measurement, the key variables for driving it, and advice for early-career professionals navigating an AI-disrupted job market.

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