United StatesManufacturing2024 – ongoingCummins
Machine learning for records classification and retention
Cummins automated 10% to 15% of its global record schedule with machine learning
Problem
Cummins needed to classify unstructured records and meet retention requirements across jurisdictions. Employees manually labeled important files and moved them into a repository that restricted collaboration.
Approach
With support from Infotechtion, Cummins adopted Microsoft Purview for information governance. It used machine learning to automate part of its records schedule and applied persistent sensitivity labels so employees could continue editing protected documents.
Results
Takeaway
Cummins reported the share of its records schedule automated with machine learning. It did not quantify labor savings from that automation.
Categories
- Size
- Large enterprise
- Industry
- Manufacturing
- Business function
- Finance, risk and legal
- Innovation type
- Process innovation
- AI technology
- Predictive analytics and ML
- Adoption
- Off-the-shelf tool or platform
- Evidence
- Vendor case study
Sources
Source summaries
Microsoft described Cummins' adoption of Purview for records governance. Its enterprise content management director said machine learning had automated 10% to 15% of the global record schedule.
Full details are in the original sources.
