The real power of finance data, and the AI built on top of it, starts from the bottom up. A strong data foundation begins with uniform naming, structured onboarding, and disciplined entry at the transactional level. Companies that build from clean, consistent inputs will unlock faster closes, better insights, and true AI leverage. Those that don’t will spend their time fixing what better design could have prevented.

AI cannot currently scale to meet the demands of high-volume, low-error-tolerance business processes. Despite the Agentic AI and automation, foundational limitations remain: AI’s probabilistic nature inherently produces variance, which compounds across complex workflows. From payroll to compliance, enterprise use cases demand precision, not educated guesses. Until models overcome these structural issues, AI will remain most valuable in low-volume use cases.