Manufacturing runs on capital. Finance protects the margin.
Manufacturing locks an estimated $1.7T in excess working capital across large US companies, trapped in inventory, receivables, and equipment; finance's job is freeing that cash, and AI agents are making that job both faster and more complex. The post argues an ontology is what makes a number trustworthy in business context, and shows how Genie acts as a data-smart finance coworker, surfacing where cash is trapped, where receivables are aging, and which assets underperform with governed, traceable answers.
* Finance protects the margin by keeping capital moving. Manufacturing ties up cash in inventory, receivables, and equipment, and an estimated $1.7T sits trapped in excess working capital across large US companies. As AI agents accelerate planning and finance decisions, finance's job of freeing that capital gets faster and more complex. * Accurate isn't the same as correct. A number is only trustworthy in the full context of the business, which plant, which SKU, which customer terms. That's what an ontology provides: it captures business meaning and keeps it current as demand, lead times, and payment behavior shift. * Genie is a data-smart AI coworker for finance. It answers the three core questions (where cash is trapped in inventory, where receivables are aging, which assets aren't earning their return), shows its work with governed, traceable answers, and readies actions while a person makes the call. The three outcomes compound into one reinforcing mechanism.