Financially quantifying AI risk is neither easy nor simple. Why else would big insurance be abandoning AI coverage? 

Set the investment language: Finance (not Tech) 

CIOs, CTOs, and AI Executives (who are IT/tech people) love to talk about AI development options in technical terms. Even the concept of risk is shrouded in security techno acronyms. If they want their projects funded, requests must be in financial terms. That includes a price on the AI risk. 

Financial attestation can’t have blind spots 

When signing financial statements, CEOs and CFOs are attesting to their completeness, accuracy, and making a legal obligation in support. The only way a CEO and CFO can reasonably take this position is to understand the financial risks. That means financially quantifying AI risk or, in other words, pricing AI risk. 

A LOT of AI failure is happening. What’s the plan to deal with it? 

Useful industry data showing just how wide and deep the financial risks may be: 

• 95% of all AI projects fail (MIT) 

• 30% of AI projects abandoned post-PoC (Gartner) 

• $1Trillion+ in AI failures quantified (Bleederboard.AI) 

Clearly defined seat at the AI table 

AI cross-departmental work groups, pods, teams, et.al. have thus far excluded representatives from the Finance org. Why? AI has been conflated with tech-term heavy cyber framing and layered under broader initiatives (e.g. Digital Transformation). Financial AI Risk Managers need to be added to the table, and their role is pricing AI risk.