You can also listen to the episode with video on Spotify.
Enterprises around the world are struggling to predict and track their AI spending. What makes this a hard problem to solve, and what can CFOs do now to get a handle on token spending? This episode is ideal for anyone at an enterprise today who is trying to manage these costs.
Speaker: Ravi Kuppan
LinkedIn: https://www.linkedin.com/in/ravikuppan/
Yarken is a Betatron Venture Group portfolio company.
Episode learnings
AI spend has flipped from predictable per-seat licensing to variable, spiky consumption — which is why it's landed on the CFO's desk. Ravi's rough figure: about 75% of enterprises are over their AI budget, and he cites Uber burning a full-year token budget in three months and Salesforce spending ~$300M on one vendor.
Most enterprises are paying several times for overlapping capability: Copilot bundled into M365, GitHub via Microsoft, plus standalone Claude or ChatGPT seats. His analogy — buying a Ferrari when a Nissan does the job — unless you genuinely have power users.
The harder problem is invisible spend: AI features embedded inside SaaS products you already buy. Getting to true AI total cost of ownership means joining contracts, the GL, and actual usage data in one place. A Fortune 50 company he spoke to still can't state its AI cost.
Self-hosting isn't an escape. One university built on-prem AI infrastructure and found the energy cost of a single rack doubled its entire data centre bill.
Practical advice for 2027 planning: name an owner now; deploy an AI gateway (a proxy that reveals model, user, business unit, and query) so you can attribute and charge back; and block anything from going to pilot or production without a governance metric attached.
Tokens aren't comparable across providers — no like-for-like benchmark exists, which makes forecasting genuinely hard.
US enterprises remain wary of Chinese models; where they're used, it's self-hosted. Data sovereignty, MCP data flows, and security harnesses are becoming procurement questions.
His contrarian call on the data centre buildout: per-token prices fall, but total spend won't — consumption expands to fill it. The durable question becomes revenue generated or cost removed, not cost alone.
Hosted by Arshad Chowdhury, Managing Partner at Betatron: Betatron.co X (Previously Twitter): @arshadgc
LinkedIn: https://www.linkedin.com/in/arshadgc
