AI-Ready Finance Starts with the CFO: Clean Migrations, Continuous Monitoring, Trusted Data
AI is transforming the finance function. Forecasting and anomaly detection are now table stakes. The next wave—agentic workflows powered by large language models (LLMs)—is here. These agents don’t just analyze; they act: drafting entries, syncing systems, preparing close packages.
But all of this depends on one fragile foundation: your data. CFOs must lead the readiness effort, starting with how financial systems are migrated and how data is continuously monitored.
The reality: most financial data is messy
At Doyen AI, we’ve seen finance data from dozens of companies. We consistently see data that is incomplete, inconsistently structured, and difficult to trace. ARR is calculated differently across teams. Contract dates don’t align. Custom fields and manual overrides break logic downstream.
Migration is the first moment that matters
Migrations are more than technical projects. They are the opportunity to fix structural problems at the source and often coincide with adopting or upgrading a system of record. Establishing a modern system of record helps ensure data is structured, governed, and aligned to platform best practices. Done well, they introduce:
- Clean, normalized data
- Clear, explicit mappings
- Alignment with best practices of the destination system
Doyen helps teams use this moment to set a foundation both finance teams and AI agents can build on with confidence.
Clean data doesn't stay clean
Even after a strong migration, trust decays. Systems drift due to manual edits, broken syncs, or inconsistent logic. Most teams only catch problems when reporting breaks or close timelines slip.
What needs to be monitored:
- Contract → invoice → GL consistency
- ARR and revenue recognition alignment
- System-to-system agreement on key financial metrics
Spreadsheets and dashboards are not enough. You need structured, automated checks to maintain confidence as data flows.
A high-leverage example: cross-system revenue validation
Revenue data flows across CRM, billing, and ERP systems. If those numbers don’t match, forecasting, reporting, and audit-readiness all suffer. We’ve seen mismatches delay closes, erode trust, and require days of manual reconciliation.
Doyen’s migrations are built to support this validation. We make the mappings explicit and clean, so downstream monitoring can be automated, not improvised.
Why this matters more in the age of agents
LLM-powered agents are now acting within financial systems and increasingly across broader organizational workflows, from procurement to approvals to compliance. Many finance leaders and CIOs are planning to expand their use of these agents in the coming quarters, aiming to accelerate routine processes and reduce manual intervention. These agents don’t just consume data, they generate it. If the underlying data is flawed, agents won’t work properly. Worse, they may introduce additional inconsistencies and errors. To confidently scale agentic workflows, CFOs must first ensure the data is clean, aligned, and continuously validated.
That’s why migration and monitoring are both critical. One sets the structure. The other protects it.
Final thought: this starts with the CFO
AI-readiness isn’t about tools. It’s about trust. Clean migrations. Continuous monitoring. Trusted data.
These are the levers CFOs can pull today to build a finance function that moves faster, automates more, and stays accurate.