Automated Document Management: automation and artificial intelligence serving businesses

Introduction

Document management often proves to be a critical node for businesses, but with the strategic adoption of automation and artificial intelligence, this challenge can turn into a decisive competitive advantage. Traditionally, business documents have come from different channels such as email, PEC, fax or physical counters and require a manual and often repetitive approach to their processing.

Definition of automated document management

Until recently, Robotic Process Automation (RPA) has been used to automate mainly repetitive tasks, revolutionizing process management but limited to less complex scenarios. Today, technological evolution has pushed automation toward integration with Artificial Intelligence, giving rise to Intelligent Process Automation (IPA). This new frontier allows robot-software to learn from the context in which they operate and to transform from simple performers to true assistants capable of managing complex business processes. In particular, when we talk about advanced automation in the context of document management, we are referring to Intelligent Document Automation systems. These systems not only simplify document processing but also elevate the entire process to an unprecedented level of efficiency and accuracy, opening the door to document management that is not only automated, but also intelligent and strategically integrated within business operations.

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Cos’è l'Intelligenza Artificiale e perché è utile alle aziende

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Benefits of Automated Document Management

Adopting automated document management systems can bring a number of significant benefits for companies of all sizes and industries. Below, we will explore the main benefits these systems can offer:

Improved operational efficiency: Automated document management dramatically reduces the time required to store, search and retrieve documents. With automation, processes that traditionally took hours can be completed in minutes, freeing up human resources to devote to more value-added tasks.

Cost reduction: automating document management helps eliminate costs associated with paper handling, including printing, mailing and physical storage. It also reduces the need for manual intervention, minimizing human error and subsequent correction costs.

Security and compliance improved: Automated document management systems provide better security controls and facilitate compliance with applicable regulations. Sensitive documentation is protected from unauthorized access and document tracking is ensured, which is essential for audits and reviews.

Accessibility and collaboration: With digitally managed documentation, files can be accessed in real time from anywhere, facilitating collaboration among even geographically distant teams. This is especially valuable in an era when remote and flexible working is becoming the norm.

Scalability: automated systems enable companies to manage volumes of documents that increase with business growth, without the need to invest proportionately in human resources or physical storage space.

Improved customer experience: the ability to quickly retrieve documents and information significantly improves customer response time, leading to increased customer satisfaction and loyalty.

Analysis and Insight: advanced document management systems can offer detailed analysis of document usage and management, providing valuable insights for strategic decision-making and process optimization.

The Automated Document Management Process.

Effective, state-of-the-art document management is not limited to the simple archiving or retrieval of documents, but embraces a comprehensive and integrated process that runs through four key phases. Each phase is designed to optimize different aspects of document management, from receiving documents to monitoring the entire system. These phases are essential to ensure that each document is managed intelligently, efficiently, and in compliance with current regulations. Below, we will explore each of these steps in detail, which include: classification, generation, sorting, and tracking.

The Automation of Document Classification.

The document classification process represents one of the first and most critical steps in automated document management. This step is essential because it allows the "class" of each document to be determined, a categorization that will influence all subsequent operations, from management to preservation of the document itself.

In a business environment, documents are varied and numerous, often requiring different treatments depending on their specific characteristics:

Processing: each class of document may require a different processing.

Legal fulfillments: some documents may require specific legal fulfillments, such as storage for a specific period of time.

Deadlines: different documents may have different deadlines, which are important for meeting legal or contractual deadlines.

Skills required: some documents require specific skills or clearance levels to manage them.

The use of Machine Learning models in the classifier is crucial to deal with the large volume of documents and their variety. Through the use of pre-trained algorithms, the classifier is able to:

Automatically identify document class: the ML model analyzes incoming documents and automatically assigns a class based on pre-defined features learned during the training phase.

Improve classification accuracy and speed: over time, the system becomes more and more efficient at recognizing document classes, even the less frequent ones, reducing errors and waiting times.

Automating this process through the classifier not only frees human resources from repetitive and error-prone tasks, but also ensures greater compliance and accuracy in document processing. With accurate and timely classification, the company can significantly improve its operational efficiency and reduce document management risks.

 

An Example of Classification: back office of an electric supply company

The back office manager of an electric supply company, is faced with a variety of communications from users on a daily basis. Here is a list of classes typical document classes:

Supply contracts: documents defining the terms of electricity supply service, including tariffs, duration, and conditions for renewal.

Bills and bills: details of periodic energy consumption and rates charged, along with other fees and charges, sent to users.

Notifications of outages or service interruptions: reports sent by users reporting malfunctions or temporary suspensions of electric service.

Requests for contractual changes or updates: solicitations from users to make changes to existing contracts, such as updating contractual power, change of domicile, or biographical updates.

Disputes and complaints: communications concerning disputes over bills, quality of service received, or other contractual disputes.

Service terminations and cancellations: requests from users to terminate electricity service, generally associated with moves or change of supplier.

Marketing & Communication: information on new offers and additional services, energy efficiency initiatives, and other promotional campaigns.

Energy consumption readings: details on procedures for measuring energy consumption, either by self-reading by users or by technical audits.

Technical information and safety regulations: essential data on electrical installation safety and industry regulations, crucial for new agreements and keeping users up-to-date on safety regulations.

Once the "Document Class" is established through Machine Learning, paperwork is forwarded to the appropriate departments or individuals responsible. For example, shipping requests go to the shipping department, invoices to the accounting department, and so on. Departments or individual employees receive the paperwork and can handle it according to company procedures.

Document production using artificial intelligence

The Generator is a key component in automated document management: using a generative artificial intelligence (LLM) language model, it allows document content to be created automatically. These models are optimized and pre-trained to produce text based on specific document classes and data from previous processing. This allows for:

Generate responses and documents: the model can automatically compile and customize documents such as contracts, responses to customer inquiries, and internal reports, saving time and reducing human error.

Adapt to changing contexts: with the ability to learn from historical data, the model adapts to improve the accuracy and relevance of documents generated over time.

Consistency and Tone of Voice: all documents produced will be consistent in tone and format, ensuring uniform professional communication.

Practice sorting automation

The Sorter represents the automation step of routing documents and files to the appropriate departments or managers within the organization. This automation platform:

Assigns practices intelligently: based on predefined rules and learning from past actions, the system can automatically distribute practices to the right people, optimizing workflows.

Reduces waiting time: by minimizing delays in distributing files, the system ensures faster response to internal and external requests.

Facilitates traceability: every file is tracked by the system, providing complete visibility into where each document is and what its status is.

Real-time monitoring of document flow

The Monitor Cockpit is the dashboard from which administrators and management teams can view and control document workflow in real time. This tool offers:

Customizable dashboards: users can configure dashboards to display metrics most relevant to their specific role or needs.

Alerts and notifications: the system can send notifications if there are anomalies or delays in document processes, enabling timely action.

Detailed Analysis: provides access to in-depth analysis of document flow, identifying strengths and areas for improvement, offering the ability to constantly optimize and redefine business processes.

Conclusion

Automated document management proves to be not only a strategic solution, but a compelling necessity for companies that aspire to remain competitive. Through the adoption of intelligent and interconnected systems, ranging from Classifier to Generator, Sorter to Monitor Cockpit, organizations can transform a traditionally onerous task into a dynamic competitive advantage.

Integrating advanced technologies such as artificial intelligence and machine learning into document management processes not only accelerates day-to-day operations, but also improves accuracy, security, and regulatory compliance. This innovative approach ensures a more agile response to market demands and customer expectations, while simultaneously improving internal collaboration and optimizing resources.

Ultimately, automated document management is essential for any company that aims to optimize its processes, reduce operating costs and continuously improve the services it offers to its customers. With a well-implemented document strategy, companies not only keep up with the pace of technological evolution, but also place themselves at the forefront of operational and strategic innovation.

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