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Document management is a vital process within most midsize-enterprise businesses, with almost every sale, delivery, or contract being tracked through a series of documents like invoices, purchase/sales orders, written agreements, and more. AI has rapidly improved in its ability to automate the digitization and organization of data tracked by these documents, as well as customizing the workflows of employees who rely on them.
As a result, businesses are rapidly increasing their implementation of AI into core business processes, increasing operational efficiency and giving their staff more flexibility to focus on tasks that require more of a human touch. This puts these companies at a strategic advantage against others in their industry, so it is vital to understand exactly why and how they are doing so.
We’ll discuss the following to provide some clarity to business leaders:
- What AI in Document Management Looks Like
- AI Document Management Use Cases
- Benefits of AI Implementation
Let’s explore each and get a better understanding of why AI in document management has seen so much growth in the past few years.
What AI in Document Management Looks Like
For those new to AI implementation, it is important to understand what we mean when we discuss “AI implementation.” Generally, there are a few different ways that companies choose to implement AI into their document management processes.
AI Implementation Strategies
| Purchasing Third-Party Software | Purchasing third-party software tools is one of the cheapest and most common ways to implement AI into business processes, but also the least complete since individual tools usually only automate one or two specific functions. |
| Developing Custom Software | The most expensive option is developing custom software, or having it developed by a third-party developer. This provides comprehensive AI automation but at the highest up-front cost and longest onboarding time. |
| Full-Service Outsourcing | Another common option is outsourcing to a company that utilizes its own mix of AI automation and expert staff. This provides a middle ground in terms of cost and the fastest possible onboarding process since staff don’t need to be trained on a new software tool. |
These are the most common manifestations of AI implementation in document management, and the correct choice for your company depends on your goals, budget, and tolerance for onboarding time. Full-service outsourcing provides the most versatile all-around value by offering comprehensive automation without long onboarding time, all at a cost that lies somewhere between out-of-the-box software tools and custom development.
AI Document Management Use Cases
The clearest way to illustrate the value of AI in Document Management is to explain the most common use cases we see from our clients across several industries. The following are some of the highest-value use cases we’ve identified in our time implementing the tech for our clients:
| Automated Document Indexing | Using machine learning-powered tools like optical character recognition (OCR), AI software can automatically index documents, making their text searchable by other programs. |
| Fully Searchable Databases | Document indexing means that databases are fully searchable, allowing staff to search not just by title and date but by any field included in the document since the database can read every character. |
| Automated Data Capture | For many businesses, scanned documents have their data entered manually into Excel sheets or other software by data entry clerks. AI implementation automates this process, with full outsourcing taking over every step so firms can simply send in scanned docs and get back their fully organized data. |
| Building a Neural Network | A “neural network” refers to a machine learning process of connecting different data points that all contribute to a larger knowledge base. By using unified AI platforms with fully digitized documents, these neural networks allow all information in those documents to be accessed and utilized by any number of connected apps or business process automations. |
These use cases provide exceptional value for companies that rely on a high volume of documents by replacing countless labor hours that their staff spend on mundane data ingestion workloads. This is one of the most important things to note about AI document management: While it’s profoundly effective on its own, it is also a force multiplier for more complex business processes for which staff can use the labor hours they’ve saved on these mundane tasks.
Benefits of AI Implementation
To provide even further clarity regarding the transformative capabilities of AI for your business, let’s go over the tangible benefits resulting from the above-mentioned use cases. All of the following are common value-adds that all three implementation strategies can offer to varying extents:
| Increased Data Capture Speed | AI automation makes data capture infinitely faster than manual entry, wit comprehensive custom solutions and/or outsourcing being capable of handing massive volumes of documents in mere days, allowing more time for auditing. |
| Improved Data Accuracy | ML-paired OCR is extremely accurate, with fewer misinputs, automated alerts when certain fields fall outside of normal parameters, and far more time left to audit all data for accuracy. |
| Heightened Data Security | AI-powered data security keeps staff more accountable regarding data protection best practices and provides real-time warnings about potential breaches. It can also scan digitized docs to determine what type of document they are, and how they need to be handled, without the need for manual document labeling. |
| Easier Access to Data | Cloud-based storage and document indexing make data far more accessible and decrease the time needed to find highly specific information and generate reports on data en masse. |
| Digitization of Handwritten/Older Documents | One of the more unique uses of cutting-edge ML OCR technology is its ability to extract data from handwritten documents and older documents with less in-tact text. While these docs will require a bit more auditing, modern ML-paired OCR does a far better job parsing through harder-to-read documents than any technology before it, allowing it to automate processes in ways that simply weren’t possible a decade ago. |
All-in-all, these benefits are the reason why so many businesses are implementing AI into their document management processes. It is arguably the single most effective use of AI, as its ability to handle ingestion workloads is where it excels most, and with the lowest risk of costly mistakes.
To maximize this value, and minimize any risk, consider a comprehensive data outsourcing service from a company like iTech.
Implement AI in Document Management with iTech
We at iTech pride ourselves on our cutting-edge machine learning OCR software, top-of-the-line onboarding experience, and ongoing support. We also offer 24/7 access to support personnel and senior account managers to maximize visibility and peace of mind, eliminating the “black box” approach to outsourcing.
To learn more about AI in document management, fill out the contact form below.
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IDS Commander iTech2021
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