Artificial intelligence (AI) can enhance several business processes through automation—one of which is document management. With AI-embedded models, organizations can improve their operations, especially those dealing with large volumes of data.   

Automated document processing involves main functions such as scanning the document, labeling it, and separating it based on customized datasets. These classifications are dictated by an organization’s data management guidelines and procedures and executed by an efficient and reliable document annotation tool. Having this essential tool by your side ensures easy, fast, and intelligent processing without compromising the outcomes.   

Automation is a necessity in today’s highly competitive world. Organizations must access and invest in valuable tools to increase efficiency, reduce repetitive workflows, and access critical business information. By integrating AI into document processing procedures, companies can experience the following advantages. 

1. AI-driven data classification ensures fast and error-free processing

Businesses that deal with large amounts of data, such as banks and other financial institutions, healthcare, and book publishing industries, need a reliable data management system and have to spend money on it. For instance, they have to pay someone to perform manual data entries, which takes time, is laborious, and is also vulnerable to human errors. 

With automated document processing, any AI or machine-learning-enabled device can run through each document, understand what it says, and extract pertinent information. In doing so, it makes the document easier to sort and manage. More organized data processing makes it effortless for businesses to convert unstructured to structured data. It can also remove double or invalid entries while keeping only pertinent data.

2. Increases work productivity

As mentioned, manual data classification is labor-intensive and vulnerable to human errors, but it’s essential in maintaining company and third-party data, mainly clients. Refusing to automate document processing can lead companies to several work hour losses just by reading, analyzing, storing, and sorting each document. Retrieving data can also be a nightmare without access to structured information.  

 As data is generated daily, it can be challenging for data managers to keep up with the demand when sticking with manual processing. In addition, a company must hire the correct number of people to perform this task. 

 Because intelligent data processing doesn’t require manual intervention once it’s up and running, fewer people are needed for data classification, allowing your staff to work on core business activities.  

3. Ensures regulatory compliance and data security

Besides the hefty cost businesses have to pay for adequately categorizing documents, traditional document classification practices may expose companies to inappropriate tagging of personally identifiable information—making it insecure.

Based on an IBM report, security breaches can cost a business an average of USD$4.24 million per incident as of 2021. The figure represents a 10% increase compared to 2020, the highest in 17 years. In addition, about 44% of security issues involved hacking of an individual’s name, password, email address, and healthcare information. Further, 20% of the victims had their credentials stolen, leading to the breach. Unfortunately, this most common entry point for security issues often took 250 days to detect and mitigate, reflecting the longest time to address, among other data leakages.      

Most industries that gather personal data must uphold the data privacy law and other related security regulations. AI-enabled data classification enables proper identification and handling of sensitive data, reducing the risks of a data breach and penalty fees. For instance, organizations can protect data with passwords or other authentication processes. Automated data classification also detects and denies unauthorized access to private and secure data.     

4. Enables scalability

The good thing about artificial intelligence platforms, most notably machine learning (ML) and natural language processing (NLP) models, is that they improve over time. That said, the more you use them for document classification, the better results they provide. It’s similar to how AI makes search engines deliver the most relevant results. 

By understanding more about the organizational rules on how documents are classified and managed, intelligent document classification assures better outcomes. As a result, companies can operate more efficiently, make data-driven business decisions, and provide better services to their customers, allowing them to scale.  

5. Improves overall business efficiency

An AI-enabled data classification method doesn’t only make identifying, sorting, and storing data fast and secure. It can improve the overall data management system, which helps easy access to data that encourages executives to develop business intelligence. For instance, if financial managers want to find the best supplier for a specific raw material, they can enter the keywords based on their priorities and get the results they want in no time. 

Moreover, it can flag problematic entries or move forward with the following steps, such as forwarding the text to other departments without human intervention. Additionally, automated data classification allows organizations to study past performances, identify weaknesses, correct them, and make more realistic projections. 

The bottom line

Businesses must have quick and efficient access to valuable business data to get relevant insights for business improvement and growth—which can be challenging with manual processes.

By automating business document processing, organizations can ensure that their clients’ and clients’ data remain relevant, valuable, and secure. Investing in this model helps businesses improve their internal operations and external relations.   

References 

  1. SAP. Undated. What is document classification?. https://help.sap.com/. https://help.sap.com/docs/DOCUMENT_CLASSIFICATION/ca60cd2ed44f4261a3ae500234c46f37/d35119b10c1e4c8dbcbaec853a78fc5b.html. Accessed 11 July 2022
  2. PR newswire. 28 July 2021. IBM Report: Cost of a Data Breach Hits Record High During Pandemic. www.prnewswire.com. https://www.prnewswire.com/news-releases/ibm-report-cost-of-a-data-breach-hits-record-high-during-pandemic-301342720.html. Accessed 11 July 2022.  
  3. Kochhar, H. 14 August 2020. 7 Benefits of AI-Enabled Document Management Systems. www.hackernoon.com. https://hackernoon.com/7-benefits-of-ai-enabled-document-management-systems-6wb63udx. Accessed 11 July 2022