Artificial intelligence is being actively integrated into business processes, but not all pilot projects yield a financial return. To achieve a tangible impact, it is crucial to select the right processes for automation.
Key use cases for AI in document management
- Intelligent Document Processing (IDP): automatic data extraction from invoices, acts, and contracts to minimize manual entry.
- Smart search: semantic search in document management systems (DMS) based on meaning rather than just keywords.
- Classification and routing: automatic categorization of incoming documents and routing them to the responsible personnel.
- Summarization: generating concise summaries of lengthy contracts or regulations.
How this affects the sector
For the business and software industry, the low financial return on ad-hoc AI pilots means companies must shift from hype-driven adoption to a structured, value-driven approach. Businesses that fail to select the right processes risk wasting investments and slowing down their digital transformation, while successful integration allows companies to optimize investments and mitigate risks associated with automation errors.
A practical checklist
To ensure a successful AI integration in document management, experts at Scriptum advise taking the following practical steps:
- Avoid the automation of rare or legally sensitive tasks in the initial stages of the project.
- Focus on repetitive processes that rely on high-quality digital data.
- Prioritize high-impact use cases such as Intelligent Document Processing (IDP), smart search, automatic routing, and document summarization.
Prepared by a Software Ukraine member. Original publication.