The Fundamental Question   CFOs evaluating AI agents face the build versus buy decision. Understanding requirements, costs, risks, and timelines for each approach prevents misaligned investments and implementation failures.    The right choice depends on company size, technical capability, timeline needs, and operational requirements.      What Building Actually Means   Building AI solutions means assembling internal data science team, developing custom models and workflows,

The Mistake Question   Controllers worry AI agents will make mistakes damaging customer relationships or creating financial exposure. Understanding how AI makes mistakes, how often, and comparison to current manual handling risk provides realistic risk assessment.    AI mistakes differ fundamentally from human mistakes in pattern, frequency, documentation, and fixability.      How AI Agents Make Mistakes   Mistake Category 1: Misunderstanding Customer Statements   What happen

The Selection Decision   Mid-market companies evaluating AI agents face the custom versus generic solution choice. Understanding decision factors, cost implications, and risk trade-offs prevents both premature custom development and inappropriate generic implementation.    The right choice depends on exception volume, process complexity, competitive advantage requirements, budget constraints, and timeline needs.      The Decision Matrix   Four Solution Categories   Category 1

The Job Change Reality   AI agents don't eliminate AR/AP positions. They transform them. Understanding how roles evolve - from coordination-heavy to judgment-focused - helps staff and management prepare for beneficial change.    Reality: Jobs become more strategic, less administrative. Staff expertise becomes more valuable, not less.      Before AI: The Current Role   Typical AR Staff Day   Time allocation (8-hour day):   Exception identification: 45 minutes (reviewing aging

The Uniqueness Claim   "Our process is too unique for generic AI solutions" is the most common objection to standard AI agent implementations. Understanding when processes are genuinely unique versus standard with surface-level variation prevents both inappropriate generic solutions and unnecessary custom development.    Most processes claiming uniqueness have common underlying patterns. True uniqueness requires specific characteristics justifying custom development.      Wha

The Due Diligence Process   CFOs and controllers evaluating AI agents conduct thorough due diligence before committing budget. Understanding the questions finance leaders consistently ask helps frame evaluation and preparation.    These seven questions appear in virtually every finance leader discussion about AI agent implementation.      Question 1: What Is the Complete ROI Including Hidden Costs?   What Finance Leaders Want to Know   Surface question: "Will this pay for it