Do you remember Clippy?

If you’ve been behind a computer a long time ago, you are likely to remember “Clippy”, a friendly assistant bundled with Microsoft Office’s versions 97 to 2003. It was supposed to help you get things done better and quicker by predicting what you’re trying to do and understanding your queries. This was at a time when artificial intelligence was advanced enough to defeat a world chess champion (IBM’s Deep Blue defeated Garry Kasparov in 1997), but the technology behind it was not yet commercialized and made available for end users. So Clippy had to rely on more rudimental methods like Bayesian algorithms to offer advice to users. The result was a disaster. The intelligent paperclip was declared a total failure and caused more hate than love. But Clippy’s creators at Microsoft had a logical vision. Working with documents is an excellent use case for automation and artificial intelligence. How far have we come since then?

History of AI Use in Document Management

The need for AI in document management can be traced back to the early days of document scanners and the digitization of paper documents. Users needed an easy way to index and classify large numbers of scanned documents. And so, one of the earliest forms of AI in document management was the use of optical character recognition (OCR) to read the content of documents. OCR used multilayer perception (MLP) neural network classifiers to identify letters by shape and the models were easily trainable to work with different alphabets and fonts. The models were even capable of understanding handwriting, albeit with less accuracy.

Since then, document management systems have progressively used AI to automate and enhance a number of functions. They became capable of identifying structured documents and extracting their metadata. They were also able to enhance the accuracy and relevance of search results. And more recently, the use of AI in document management has expanded to include advanced capabilities such as generating useful insights and predictions based on data and content analysis.

Common Use Cases of AI in Document Management

Among the most significant and very effective applications of AI in document management are:

  • Automated data extraction: Using AI to extract metadata and content from documents. This includes OCR, intelligent form recognition for structured documents (e.g., invoices, forms) and intelligent processing of unstructured documents (e.g., contracts, transcripts).
  • Automated document classification: Using AI to classify documents based on their type or content, allowing for more efficient organization and retrieval.
  • Intelligent search: Using AI to improve search functionality within a document management system, allowing users to find relevant documents more quickly and accurately.
  • Predictive analytics: Using AI to analyze historical data and make predictions about future trends, helping organizations make informed decisions.
  • Natural language processing: Using AI to understand and interpret the human language found in the content of documents in order to provide valuable insights and suggestions that can be leveraged to improve business outcomes.

Benefits of AI Use in Document Management

We’re barely scratching the surface in our use of AI in document management, and yet the economic benefits are invaluable. There are many industries and businesses that are taking advantage of it. Some examples include:

  • Legal firms: Many legal firms are using AI to automate the process of reviewing and analyzing legal documents, freeing up time for lawyers to focus on higher value tasks.
  • Healthcare organizations: AI and big data models can be used to extract data from medical records and other documents, allowing healthcare organizations to more easily track and analyze patient data, and providing valuable insights that can be leveraged to improve patient treatments and outcomes.
  • Financial institutions: Financial institutions are using AI to automate tasks such as data entry and document classification, improving the efficiency of their processes and reducing the risk of errors.
  • Government agencies: Government agencies are using AI to automate the processing of documents such as tax returns, social cases, and benefit applications, improving the speed and accuracy of their services.

The Future Ahead

Back to Clippy and why we think the intelligent assistant model will make a strong comeback in the world of digital workplace solutions including document management and collaboration systems. The recent developments in AI and language models such as GPT-3 have made significant strides in the field of NLP and the computer’s ability to understand human language and respond with useful inputs in a natural and intuitive way. We believe document management, authoring and collaboration systems will start employing a layer of intelligent assistance that will help users make the best use of their existing documents and the knowledge contained within, helping organizations establish a collective brain that is capable of improving outcomes and propelling growth.