What Should Private Markets Teams Measure When They Deploy AI

A capital call notice arrives on Monday morning. AI extracts the amount and due date in seconds. By Tuesday afternoon, the investment operations team is still reconciling the notice to the right fund and checking whether an amended version supersedes it. Accounting is waiting to post the obligation.

The extraction was fast. The question for the COO is whether the workflow got faster.

Private markets teams should measure AI from the moment a document arrives to the moment someone can use the data. For a capital call, that means a validated record in the accounting system. For private credit, it might mean an updated borrower record that the portfolio monitoring team can act on. Once the team defines that endpoint, four measures can show where AI is making a difference.

Establish the baseline before the pilot

Choose one workflow and agree on where it starts and ends. Include routine documents and the cases that consume disproportionate time. For capital calls, that could mean revised notices, unfamiliar manager formats and investments with similar fund names.

Use the same definitions before and after deployment, and compare batches with a similar mix of documents. A pilot made up of familiar notices can show what AI does on a good day. Including month-end volume and amended notices shows how the workflow handles the work that usually slows the team down.

Measure where judgment adds value

A reviewer who confirms that an amended notice supersedes the original is doing valuable work. A reviewer who rekeys a validated amount because the accounting system cannot accept it is addressing an integration gap. Counting both actions makes the work visible. Recording why each action was needed helps teams decide what to automate next.

The same principle applies when an AI agent can write to another system. A routine record that clears agreed checks may be eligible for automated posting. An amendment that changes a payment amount or due date may warrant review. Measure both paths so the team can see how much moves automatically, where human judgment is needed and how often either path leads to a correction.

At the end of a pilot, investment operations leaders should be able to say how much sooner they received usable records, how much work the team saved and what happened to data quality after posting. 

See how much faster your team can turn private markets documents into validated data with Alkymi. Measure how much sooner usable data reaches your systems and how much manual work your team saves, giving them more time to investigate exceptions, analyze portfolio changes and support investment decisions.

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