Financial teams operate with scattered information. An invoice in an email, a contract in SharePoint, vendor data in Salesforce, historical records in the ERP, policies on a drive. When a transaction needs to be verified, payment terms compared, or a process audited, the search is time-consuming.
One person consults a document and asks a colleague who might have it. Another waits for a response from accounting to locate an invoice. A third opens multiple folders to find the latest version of a contract. Someone rewrites information that already existed elsewhere.
According to data from Forrester and OpenText, this lost time in financial teams amounts to approximately 2.7 hours per person per day.
In a financial team of 5 people, this represents 67.5 hours weekly of lost productivity on tasks that do not generate direct value.
Examples of how AI is used in Document Management
AI in document management is more than an improved search system. It also leads to improvements in how information is accessed, organized, and analyzed.
Unified access
The system understands where information resides without requiring centralized migration. A query can search simultaneously in all these locations. The user accesses it as if it were a single repository.
Search by meaning, not just by keywords
Instead of searching for "invoice 2024 Acme," a manager can ask "What is our largest vendor by transaction volume?" The system understands the intent, locates relevant transactions, analyzes patterns, and delivers an answer in seconds.
Automatic Summarization and Synthesis
A 30-page document is summarized into key paragraphs. A set of invoices is analyzed to extract patterns. Monthly reports from multiple sources are automatically consolidated.
Intelligent Classification
Incoming documents are automatically classified. A vendor invoice is correctly tagged, assigned to the relevant accounting period, and linked to its purchase order. Without manual intervention.
Impact of intelligent document management on finance teams
The figures reported by companies that implemented these solutions are consistent:
2.7 hours per person per day of time recovered in information search and compilation tasks. For a team of 20 financial analysts, this amounts to nearly 270 hours per month.
23% reduction in operational costs of document management. Less time spent on manual searching and organization means specialized resources can be directed towards analysis and control.
30% improvement in productivity for advanced users who learn to work with AI. In financial analysis teams, those who use these tools report completing more complex analyses in less time.
28% increase in decision speed, according to research by Foundry Research from OpenText. When AI is integrated into content processes, not just search, the impact spreads across the entire operation.
Governance and Compliance
AI in document management also provides peace of mind regarding regulatory compliance:
Ø Automatic classification processes adhere to retention policies.
Ø Access is role-based when necessary.
Ø There is full traceability. A financial manager can demonstrate exactly what information was accessed, when, and by whom, right up to receiving personalized notifications.
At Brait, we support your digital transformation
Financial teams that have implemented AI in document management describe the change as both transformational and operational: less time searching and more time analyzing. This also leads to faster and more assertive decision-making.
For an organization considering this change, the approach is simple: start with an assessment of where current inefficiencies lie, measure their cost, and design a pilot to demonstrate impact in a real-world context.
Request an assessment for your finance department. We will analyze how information currently flows through your processes, identify bottlenecks, and determine the real impact of AI in your specific context.
