← Finance AI LabSample Proposal

Prepared by Brad Zapalac · BradCo. Software Group

30 / 60 / 90 Day Plan for Deploying Custom AI in a Commercial Finance Team

A boilerplate engagement plan for assessing, designing, building, validating, and deploying AI solutions inside a commercial finance organization. Real engagements are tailored to each company's systems, team, and value-creation thesis.

01 · Executive Summary

From diagnostic to deployment in a single quarter.

This plan compresses what most finance transformations stretch over a year into a focused 90-day arc. The objective is not to "do AI" — it is to remove the highest-cost manual work from your close, forecast, and reporting cycles while building the foundation for compounding gains.

Phase 1 is diagnostic. Phase 2 builds and validates the two or three highest-leverage solutions. Phase 3 deploys them into your live finance cadence and hands back a sustainable operating model with a forward roadmap.

Every engagement is tailored. Use this document as a reference for shape, scope, and expectations — the specific use cases, KPIs, and milestones are co-designed with your team during Phase 1.

02 · Phase 1

030

Assess & Diagnose

Establish a ground-truth view of the commercial finance operating model, data landscape, and highest-leverage AI opportunities.

Workstreams

Discovery & Stakeholder Alignment

  • Working sessions with CFO, VP Finance, FP&A, Accounting, RevOps, and IT leadership
  • Process mapping of close, forecast, reporting, billing, and commission cycles
  • Catalog of existing tech stack — ERP, CPM, BI, data warehouse, and point tools
  • Confidentiality, data handling, and security review with IT and compliance

Data & Systems Audit

  • Inventory of source systems, refresh cadence, and data ownership
  • Assessment of data quality, master data hygiene, and chart of accounts integrity
  • Identification of manual touchpoints, reconciliation pain, and report bottlenecks
  • Baseline metrics: hours per close, forecast variance, report turnaround time

Opportunity Sizing

  • Prioritized backlog of AI use cases scored on ROI, feasibility, and risk
  • Quick-win shortlist suitable for Phase 2 build
  • Strategic roadmap candidates for Phase 3 and beyond

Deliverables

  • Current-state assessment deck with findings and recommendations
  • Prioritized AI opportunity backlog with effort, impact, and dependency scoring
  • Target architecture sketch and data flow diagram
  • Governance, security, and change-management framework

Success Metrics

  • 100% coverage of in-scope finance workflows
  • Documented baseline for cycle time, accuracy, and effort across target processes
  • Executive sign-off on Phase 2 build scope

03 · Phase 2

3160

Design, Build & Validate

Stand up the foundational data and AI infrastructure, then build and validate two to three high-impact AI solutions in a controlled environment.

Workstreams

Foundation

  • Provision secure data layer with role-based access and audit logging
  • Establish connectors to ERP, CRM, billing, and HRIS systems
  • Define semantic model: entities, metrics, and finance-grade definitions
  • Stand up dev / staging / prod environments with version control

Solution Build

  • Forecasting copilot: variance commentary, driver-based scenarios, and rolling forecast support
  • Close accelerators: flux analysis, anomaly detection, and reconciliation assistants
  • Reporting automation: board pack drafting, KPI narration, and ad-hoc Q&A over financial data
  • Embedded controls: human-in-the-loop review, citations, and explainability

Validation

  • Side-by-side testing against analyst-prepared outputs
  • Accuracy, latency, and cost benchmarking
  • Security review, prompt-injection testing, and PII handling validation
  • User acceptance testing with finance power users

Deliverables

  • Working prototypes of two to three prioritized AI solutions
  • Validation report with accuracy, time-savings, and risk findings
  • Operating runbook and support model
  • Training materials and enablement plan for end users

Success Metrics

  • ≥ 95% factual accuracy on validation test suite
  • ≥ 50% reduction in cycle time on targeted workflows in pilot
  • Zero critical security or data-handling findings

04 · Phase 3

6190

Deploy, Adopt & Scale

Roll solutions into production, embed them into the monthly finance cadence, and hand off a sustainable operating model with a forward roadmap.

Workstreams

Production Rollout

  • Phased deployment by team and process with clear go/no-go gates
  • Cutover playbooks, rollback procedures, and on-call coverage
  • Integration into close calendar, forecast cycle, and board reporting cadence

Adoption & Enablement

  • Live training, office hours, and embedded support during first close
  • Internal champions program across FP&A, Accounting, and BU finance
  • Documentation, prompt libraries, and reusable templates

Measurement & Roadmap

  • Post-implementation review against Phase 1 baselines
  • Executive readout: realized ROI, adoption metrics, and risk posture
  • 12-month roadmap: next wave of use cases, platform investments, and org design
  • Transition to steady-state support or ongoing managed engagement

Deliverables

  • Production-grade AI solutions live across in-scope finance workflows
  • Adoption dashboard tracking usage, savings, and quality
  • Executive readout deck with realized value and forward roadmap
  • Operating model handoff: ownership, SLAs, and continuous improvement loop

Success Metrics

  • ≥ 80% weekly active usage among target finance users
  • Measurable improvement vs. baseline on cycle time, accuracy, and effort
  • Approved 12-month roadmap with funded next-wave initiatives

05 · Guardrails

Built for an audit-ready finance org.

  • Human-in-the-loop on every customer-facing or auditable output
  • Source citations and explainability built into every AI response
  • Role-based access, audit logging, and SOC 2-aligned data handling
  • No model training on confidential financial data without explicit approval
  • Clear ownership: finance owns the workflow, AI augments — never replaces — judgment

06 · Engagement Model

Lightweight team. Senior operator pace.

Sponsor
CFO or VP Finance with executive air cover
Core Team
FP&A lead, Accounting lead, RevOps / Data lead, IT partner
Cadence
Weekly working sessions + bi-weekly steering committee
Tooling
Existing ERP, CPM, and BI stack — augmented, not replaced
Investment
Scoped per engagement based on systems, headcount, and ambition

Take it with you

Download this plan as a Word document and customize it for your team.

Use it as a starting point for an internal proposal, a board pre-read, or a kickoff brief. Reach out when you're ready to tailor it into a real engagement.

Request tailored version

bradzapalac@gmail.com