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Whitepaper
Small, medium, or large?
Why continuously right-sizing AI models is critical when change is constant.
If you’re like most organizations, you probably never go back to re-check if a choice you made yesterday still holds today. But in the dynamic world of AI, change is constant. Prices drop, better models ship, and rules get redefined seemingly by the hour. The gap between what model you approved and what should be running can easily be where budgets and audits go sideways. Right-sizing AI across models, tasks, and time requires continuously re-deciding a standing decision, instead of it becoming a quarterly fire drill.
In this paper, you’ll learn:
Why more than two-thirds of enterprises have AI budget overruns today, even as costs keep falling
How a few simple steps can help turn every new model release into an evidence-based decision
Where on the AI maturity model your organization sits, and what each stage actually looks like in practice
Why “the smallest model that works reliably” beats frontier-by-default model mandates every time
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[Whitepaper] Small Models
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