How private fund CFOs can put AI to work

1. Reviewing and validating waterfall models

Quarter-end close culminates with the waterfall calculation. Long formulas, version questions and eight- to 16-hour turnaround cycles can limit the process to one or two iterations when analysis matters most.

In a governed environment, AI can organize fund terms, source data and calculation logic; compare model provisions with governing documents; and surface assumptions or inconsistencies requiring review. The CFO can shift time from mechanical review toward scenario analysis, allocation implica­tions and judgmental review. Here is an example starter prompt to reduce waterfall review time:

2. Executing capital calls and distributions with greater control

Capital events are visible to LPs but can be fragmented internally. Even when an administrator performs key steps, the CFO remains responsible for oversight, timing, communications and exception escalation.

In an integrated, governed workflow, AI can assemble documents and data, identify inconsistencies, support allocation review, prepare draft notices and route defined approval steps. The accounting and investor relations teams still validate calculations, exceptions and messaging. The CFO no longer reconciles versions or waits for status updates; attention shifts to draw timing, liquidity implications, unresolved exceptions and communication quality. Here is an example starter prompt to strengthen capital-event control:

3. Turning DDQs and NDAs into an exception-based review

A 120-question due diligence questionnaire (DDQ) can send investor relations, finance, legal, compliance and IT searching through prior responses, policies and data rooms. Reusing old answers creates risks from outdated metrics, inconsistent disclosures or unsupported claims.

For DDQs, AI can classify ques­tions, retrieve approved language, map responses to sources and flag stale or unsupported content. For nondisclosure agreements (NDAs), AI can summarize deviations from approved positions and route issues to legal reviewers. Subject matter experts remain responsible for validation, legal reviewers for legal judgment, and the CFO for sensitive disclosures.

The difference is that the CFO reviews true exceptions instead of managing a document scavenger hunt. Here is an example starter prompt to turn diligence into an exception review:

4. Managing cash and expenses by exception

Daily cash and expense management is fragmented and error-prone, creat­ing risks around duplicate payments, coding errors and liquidity.

AI can extract invoice data, com­pare coding against policy and prior treatment, match bank movements to approved payments, and flag missing approvals or unusual activity. Prior treatment can inform review, but should not override current policy or judgment.

CFO’s time moves from validating routine transactions to resolving judg­mental allocations and testing liquidity choices. An example starter prompt to manage cash and expenses by exception:

Impact of AI-enabled execution

By building fluency with AI prompting and applying it to routine tasks, CFOs can reshape their calendars around exceptions, judgement and decisions that create value. They can standardize effective practices across the team and engage technology providers and part­ners from a stronger understanding of where deeper automation belongs.

The objective is not to automate judgment or remove CFOs from the process. It is to focus CFOs’ attention where it creates most value: interpret­ing exceptions, challenging assump­tions, validating governance, assessing risk and guiding consequential deci­sions that require human expertise.