What's the right first AI workflow for a Lincoln finance team?

Variance analysis narrative drafting. High-volume, repetitive in structure but not content, value shows up immediately.

Will AI calculate wrong and we won't catch it?

Less risk than most teams expect — the architecture is AI-drafts-prose-around-the-numbers, not AI-calculates. The numbers come from your ERP.

Should AI be near our actual GL?

Read access for retrieval, yes. Write access — no, except behind clear human approval.

What about the audit-prep workflow specifically?

AI drafts process narratives and control descriptions from prior-year documentation. Internal audit reviews.

How do we know if our finance team is at tool or architectural adoption?

Could you describe the rollout without naming a specific finance workflow that changed? Are metrics activity rather than outcome? Has any approval queue actually changed shape?

For Lincoln finance teams

AI for finance teams in Lincoln

Variance analysis, monthly close drafts, budget vs. actuals narratives, invoice processing, board-pack drafting. AI handles the typing so the team can spend time on the analysis that actually changes decisions.

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What this team is doing in Lincoln

Finance is one of the lower-adoption functions for advanced GenAI in 2026 — Deloitte's Q4 2024 survey found 4% of organizations' most-advanced GenAI initiatives are in finance, well below IT (28%). That's both a problem and an opportunity.

At a Lincoln mid-market finance team, the highest-payback AI workflows are the narrative-writing parts of the work, not the calculation parts. The numbers come from your ERP; the work AI changes is everything around them — variance commentary, board-pack narrative, budget-vs-actual write-up. The CFO or controller still owns the analysis.

Invoice processing is the other natural fit — AI extracts line items, matches POs, flags exceptions, drafts AP correspondence.

Workflows that fit this team

The AI-shaped workloads where this team gets the highest payback.

Variance analysis narrative drafting.
Monthly close prep — AI surfaces unusual transactions, drafts the close memo.
Board-pack and executive-summary drafting.
Invoice processing — extract line items, match POs, flag exceptions.
Forecast and scenario drafting.
Audit-prep documentation.

Why this matters in Lincoln

Finance is where the assistive-to-architectural distinction shows up most quietly. The risk isn't AI calculating wrong — it's finance staying in tool-adoption mode without ever moving to architectural adoption.

McKinsey 2025 found AI high performers are nearly 3x more likely to have fundamentally redesigned individual workflows. For finance specifically, EBIT-level impact almost always requires moving past tool adoption.

SHRM 2026 found 73% of directors and above report creativity improvements from AI vs. 65% of individual contributors — the finance team that closes that gap captures the most distributed value.

Common questions from this team in Lincoln

What's the right first AI workflow for a Lincoln finance team?: Variance analysis narrative drafting. High-volume, repetitive in structure but not content, value shows up immediately.
Will AI calculate wrong and we won't catch it?: Less risk than most teams expect — the architecture is AI-drafts-prose-around-the-numbers, not AI-calculates. The numbers come from your ERP.
Should AI be near our actual GL?: Read access for retrieval, yes. Write access — no, except behind clear human approval.
What about the audit-prep workflow specifically?: AI drafts process narratives and control descriptions from prior-year documentation. Internal audit reviews.
How do we know if our finance team is at tool or architectural adoption?: Could you describe the rollout without naming a specific finance workflow that changed? Are metrics activity rather than outcome? Has any approval queue actually changed shape?

Sources

39% of organizations report any EBIT impact at the enterprise level from AI — The state of AI in 2025: Agents, innovation, and transformation, McKinsey & Company (QuantumBlack, AI by McKinsey), 2025
About 6% of organizations qualify as 'AI high performers' — those attributing 5%+ EBIT impact to AI — The state of AI in 2025: Agents, innovation, and transformation, McKinsey & Company (QuantumBlack, AI by McKinsey), 2025
AI high performers are nearly 3x as likely as others to say their organizations have fundamentally redesigned individual workflows — The state of AI in 2025: Agents, innovation, and transformation, McKinsey & Company (QuantumBlack, AI by McKinsey), 2025
Most advanced GenAI initiatives by function: IT 28%, operations 11%, marketing 10%, customer service 8%, cybersecurity 8% — Now decides next: Generating a new future — State of Generative AI in the Enterprise Quarter four, Deloitte AI Institute, 2025
74% of respondents say their most advanced GenAI initiative is meeting or exceeding ROI expectations (43% meeting, 31% exceeding) — Now decides next: Generating a new future — State of Generative AI in the Enterprise Quarter four, Deloitte AI Institute, 2025
73% of directors and above report creativity improvements from AI vs. 65% of individual contributors — The State of AI in HR 2026, SHRM (Society for Human Resource Management), 2026

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