The Association of Intelligent Information Management (AIIM) published survey results from 100 Leaders in Document Automation, focusing on how the digital workforce takes advantage of Document Automation Solutions.
1. Document Processing Automation
Major trends are expanding advanced capture, replacing paper forms with e-forms, processing more born-digital documents and expansion to the cloud.
What do you see as the direction of document processing automation over the next three years at your organization?
- 70% of respondents plan to expand document processing to more born-digital documents, compared to only 39% in 2018;
- 41% of respondents plan to focus more on the replacement of paper forms with e-Forms;
- 32% of respondents plan to focus more on expansions to other scanned document types;
- 30% of respondents plan to migrate to Cloud/Hosted Offering;
- 4% of respondents plan to outsource the document processing to service providers that use full automation.
2. Robotic Process Automation
Robotic process automation (or RPA) is an emerging form of business process automation technology based on the notion of metaphorical software robots or artificial intelligence (AI) workers.
Do you have plans for RPA that include processes that are document intensive?
Only 18% of respondents currently use RPA and 12% don't even know what is it.
As you can see from the infographic, records management (40%) and accounts payable/receivable (35%) top the list of business processes making use of RPA technology, with HR (24%) and customer on-boarding (23%) close behind.
3. Greatest Weakness of Advanced Capture
According to the survey, the inability to extract handwriting on documents was cited as the top weakness (28%) of advanced capture technology, followed by the complexity of the configuration/learning curve to get proficient (25%) and inability to handle unstructured data (23%).
Paper is still prevalent when it comes to data capture. All respondents say that they manage multiple document types, and 65% say they have more than ten document types and variations within these types.
4. AUTOMATION WITH MACHINE LEARNING
Artificial intelligence (AI) and Machine Learning (ML) can radically improve the way businesses process the massive volume of documents in their organizations.
Last April, Alfresco unveils new AI and ML-based Intelligence Services, that seamlessly leverages Amazon Web Service uses AI and ML to provide enterprises with a highly-scalable method for intelligently extracting important content often locked away in multiple documents, scanned images, videos, and photographs. Alfresco Intelligence Services captures and preserves all AI data, which means users can reuse the data at any time when needed. It also extracts relevant intelligence in a way that provides granular control and enables users to use complex metadata structures, as well as build more effective user interfaces.
In the survey, AIIM asked how satisfied are leaders with the machine learning capability.
At Xenit, we are developing AI/ML capabilities for data classification and entity extraction, together with the University College Leuven Limburg (UCLL). Our mission is to help customers automate the extraction of entities and apply relevant metadata without disturbing information workers.
Talk to us if you want to know more.