Executive Comp & Equity Administration
Illustrative scenario

Compress Comp Committee Prep Cycles With an AI Agent — Not More Analyst Hours

For CPOs and CFOs at public mid-cap SaaS companies, Compensation Committee season is a recurring crunch: three to four weeks of manual data wrangling between Workday, Compensia, and Diligent board book templates, with the real risk that the meeting cycle slips. The work is high-stakes and deeply templated — exactly where an AI agent can take most of the burden off your team.

Up and running in ~12 wkFor: Chief People Officer or CFO
Estimate your payback
~5 mo
Payback period
$330K
Est. savings / year
+$198K
Year-1 net

Rough estimate — change the numbers to match your business. We scope the real figures with you on a call.

The Problem: Your Most Important Board Materials Are Built on Manual Labor

Assembling a Comp Committee package for a NYSE- or NASDAQ-listed company means pulling executive compensation records from Workday, reconciling them against Compensia peer group benchmarks, computing CEO pay ratios, and then manually formatting everything into Diligent board book templates — all before routing for CPO and CFO review. That process reliably takes three to four weeks. At a company with 800 to 4,000 employees, that timeline isn't an abstract inconvenience; it dictates when your Comp Committee can actually meet and deliberate. Late materials compress board deliberation time on decisions — equity refresh ranges, executive pay positioning, peer group composition — that deserve full attention.

How an AI Agent Handles the Assembly Work

An AI Labor Company agent connects to Workday to pull current executive compensation records, ingests Compensia peer group benchmark data, and executes the structured calculations — tally sheets, peer percentile positioning, CEO pay ratio — that your team currently does by hand. It then formats the output into the Comp Committee package sections your Diligent templates require, routes the draft to the CPO and CFO for review, and handles the upload. The agent doesn't replace judgment on pay philosophy or peer group selection — those decisions stay with your team. What it replaces is the four weeks of mechanical assembly that precedes those decisions.

The Business Case: Time the Board Gets Back

This is fundamentally a quality and governance win, with meaningful efficiency gains on top. Compressing materials prep from three to four weeks to seven to ten days — a 40–60% reduction in cycle time — gives the Compensation Committee more lead time before its meeting. That means more time to review complex decisions, request follow-up analysis, or schedule supplemental calls if needed. It also frees the HR and finance analysts who currently spend weeks in spreadsheets to work on the underlying pay strategy rather than its documentation. Teams operating at this scale typically go live and start producing results in about 12 weeks. The cost of the agent is a fraction of the senior analyst time currently consumed by each cycle.

Works with
WorkdayCompensiaRadfordDiligentSlackMicrosoft SharePoint
Questions

Does the agent handle the judgment calls on peer group composition or pay positioning?

No — the agent handles assembly and formatting. Peer group selection, positioning philosophy, and final pay decisions remain with the CPO, CFO, and their advisors. The agent's job is to make the package structurally complete and current before those conversations happen.

How does the agent connect to Workday and Compensia?

The agent uses Workday's API and structured exports from Compensia to pull source data. During the 12-week onboarding, AI Labor Company works with your team to configure the data connections and validate that the outputs match your existing templates before the agent runs live.

What happens to the materials once the agent assembles them?

The draft routes to the CPO and CFO for review before anything goes to the board. Once approved, the agent uploads the finalized package to Diligent. No materials reach the board book without human sign-off.

Related use cases

Illustrative scenario for people ops, hr & customer support. Figures are example ranges, not guarantees — we scope real numbers with you on a call.

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