How to Introduce AI Into Your Close Process
The most effective implementations for AI in accounting and finance begin with precision—identifying a few high-impact areas, proving the value quickly, and building on those wins. Finance transformation is sustainable when it’s grounded in clear priorities, solid data, and shared ownership across the business.
Here’s a framework for introducing AI to your close process in a way that drives results and builds momentum.
1. Find Your Bottlenecks
Review your last few closes and pinpoint where time is lost or errors recur. Common culprits include time-consuming reconciliations, last-minute manual journal entries, and intercompany mismatches. These pain points are often ideal entry points for AI because they are repetitive, rules-based, and rich in historical data.
2. Start Small, Prove Value, Then Expand
Choose one use case—such as anomaly detection or transaction matching—and implement it within a specific business unit or legal entity. Capture measurable outcomes like time saved, error reduction, or audit improvements. Use these wins to build buy-in and expand adoption across additional teams or processes.
3. Build on a Unified Data Foundation
Disconnected systems create friction. AI requires access to reliable, connected data to generate meaningful insights. Ensure your financial, operational, and people data are part of the same system or easily integrated. Clean data is the fuel for accurate automation.
4. Partner Early With IT
Bring IT in from the start. Their involvement is critical to ensure systems are secure, scalable, and properly governed. Finance and IT alignment also helps avoid rework and accelerates time to value. Workday research on the CFO-CIO partnership uncovered that organizations with high alignment are significantly further ahead on finance transformation initiatives like AI adoption.
5. Prioritize Transparency and Trust
AI only works when finance professionals trust the outputs. Select AI-powered tools that clearly explain the logic behind recommendations. Transparent AI builds confidence, supports accountability, and encourages adoption across teams.