Must a CEO stay fluent on each & every #AI component? Know the ins & outs of #LLMs like ChatGPT, Claude AI, #Grok, #Gemini, … ? Or even know what #RAG or #MCP means? No, no and… wait for it… NO.

Perhaps there’s sufficient AI knowledge depth to make efficient investment decisions. Ones relying on data and supported with quantified reasoning. To get there, we need to bridge the Finance – Technology language gap. Presently, many deployment rejections lack supporting financial data and thereby frustrate those most valuable and sought after technical human resources. Moreover, deployment thresholds become misaligned by the rapidly changing technology & terminology.

What if you could Indemnify AI your developments into policies to support efficient production roll-out decisions. On a recent SAP webcast, Mickey N., IDC GVP Enterprise Software, shared 65% of organizations will leverage AI to bring immediate value to employees and the business by late 2026. This will drive 45% improvements in overall operational efficiency and employee productivity₁. Meaning, if you aren’t actively unifying your teams on a common language and methodology for your AI investment decisions, you’re behind.

To evade an FY27 Balance Sheet leg sweep, a top-down (dashboard-based) perspective is required to know which projects carry the most financial #risk (“quantifying”) and how they compare (“benchmarking”). Have your CFO connect here for a 15min AI Risk Discovery Session.

₁https://lnkd.in/d_ZMtNTi