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Artificial Intelligence (AI) has rapidly increased in its capabilities over the past decade. We have seen AI being used for facial recognition, natural language processing, and document processing. AI-based document processing will become the norm for many business operations and processes as technology evolves.
The first few months of 2023 have passed, and the world is still obsessed with ChatGPT and the endless opportunities the application brings with it. ChatGPT is part of a bigger story spread over the decades and still unfolding. Artificial Intelligence is too real now, changing how we look at the world and work.
One such story is document digitization in different businesses. Lending, Insurance, Law, Healthcare, Supply-chain management, Hospitality - no industry is untouched by the powerful effects of automated document data extraction. The automated document capture market currently stands at 8.7 billion, growing at a CAGR of 29.7%. Intelligent document processing(IDP) takes a chunk of it, making 63.6% of the overall market, which is only expected to grow with time.
The reason is simple - Artificial intelligence and machine learning make it possible to capture contextual information from documents and make sense of it just like a human. On the contrary, the template-based and rule-based data capture solutions can recognize the characters in a document; with little training, they can identify key-value pairs and line items and differentiate one from the other; but because these solutions are not capable of capturing contextual information that comes with characters identified, they can’t make sense of it.
If I dare make an analogy - a template-based OCR solution can read a document but can’t understand it.
It means you need humans to review the captured data to ensure its accuracy. In contrast, IDP solutions need you to review exceptions. Less human intervention frees up essential human resources for businesses that can be utilized for much important and humane tasks. That’s why the share of IDP will only grow from here because businesses need accurate, timely, and actionable information.
How AI-based document processing works
AI-based document processing technology uses artificial intelligence to automate manual data entry processes related to documents such as contracts, invoices, forms, etc. The process works by converting paper or digital documents into structured digital data that can be easily analyzed and stored later. AI systems can read and understand the text from these documents to extract relevant information quickly and accurately. This eliminates tedious manual data entry processes while still ensuring accuracy.
In addition to helping streamline internal processes, AI-based document processing has the potential to help organizations stay compliant with industry regulations. Through automated review and analysis of documents, organizations can quickly identify any areas of non-compliance or risk that need to be addressed before they become serious problems. This could include anything from identifying outdated contracts that need to be updated for compliance reasons to detecting errors in financial statements that could cost an organization millions in fines if left unchecked.
Benefits of AI-based document processing
There are numerous advantages associated with using AI-based document processing over traditional methods. For starters, it saves time because there is no need for manual data entry processes, which can be incredibly time-consuming. Additionally, this technology is incredibly accurate; whereas human errors can happen when manually entering data from documents, an AI system will always get it right without fail. Finally, this technology reduces costs since it eliminates the need for people to manually enter data from documents, which means fewer resources will be needed for those tasks:-
AI-based document categorization
One benefit of AI-based document processing is the ability to categorize documents into different categories based on their content quickly. For example, an AI system can be trained to identify legal documents such as contracts or invoices and automatically route them to the appropriate department within an organization. This capability helps streamline workflows and reduce human errors associated with manual document categorization tasks.
AI-based document automation
AI-based document automation uses natural language processing (NLP) to generate custom responses based on existing documents or templates automatically. This means that organizations no longer need to manually respond to customer inquiries or create new contracts from scratch—a task that could take hours or days when done manually—but can instead rely on automated systems powered by AI technology to generate responses in minutes or seconds. Additionally, this technology has potential applications in other fields, such as healthcare, where automated systems could be used to review patient records for the accuracy or generate medical reports based on existing templates.
What is the future of AI-based document processing?
AI-based document processing has already made a significant impact on businesses around the world. Still, it is poised to become even more important as more companies embrace this technology. As businesses continue to rely on digital solutions for their operations, they will need efficient ways of managing their paperwork and other documents, which makes AI-based document processing an ideal solution. In addition, advances in machine learning technology have enabled these systems to become even more accurate over time, so they will only become more reliable as time passes.
As CTOs look ahead at what lies ahead for their organizations, they must consider incorporating AI-based document processing into their business strategy if they want to stay competitive in today’s digital world. This technology offers numerous advantages, such as faster turnaround times and improved accuracy compared to traditional methods, while also reducing costs associated with manual labor involved with manual data entry processes related to paperwork and other documents. With advances in machine learning technologies continuing at a rapid pace, it’s clear that incorporating this type of solution into your business strategy now will pay off greatly down the line as you reap all the benefits it has to offer.
Here are some trends to look forward to in 2023:-
1. Increased use of Natural Language Processing (NLP) technology
NLP technology allows machines to understand and interpret human language. In the future, we can expect more advanced NLP techniques to enable machines to understand and process complex language more accurately.
2. Greater automation
AI-based document processing will continue to automate repetitive tasks such as data entry, document classification, and routing. This will help organizations to save time and resources, reduce errors and improve accuracy.
3. Integration with other technologies
AI-based document processing will be integrated with other technologies such as optical character recognition (OCR), machine learning, and robotics. This integration will enable faster and more accurate document processing.
4. Enhanced security
As AI-based document processing increases, security measures will be needed to protect sensitive data. AI-based security measures such as anomaly detection and user behavior analytics will be implemented to prevent unauthorized document access.
5. Improved user experience
AI-based document processing will improve the user experience by making it easier for users to find, retrieve and process documents. The technology will also make it possible to personalize the document processing experience to meet the specific needs of each user.
The future of automated data capture technology will likely involve continued improvements in the accuracy and speed of data extraction and increased integration with other technologies, such as machine learning and artificial intelligence. Additionally, there will be a greater emphasis on data security and privacy as more sensitive information is collected and stored electronically. The technology will also be able to handle more and more diverse types of data, such as image and voice, and will be able to extract data from pdf, scanned/non-scanned images, webpages, & social media platforms. Overall, automated data capture technology is on its way to becoming more sophisticated and widely adopted in various industries.
Cloud based IDP software vs On-premise solutions
Cloud-based solutions take the chunk amongst all document digitization solutions, making 57.6% of the overall market. Cloud-based solutions cost less and are more accessible, making businesses opt for these against in-premise solutions. Some companies still prefer in-premise document capture solutions because they can’t trust their confidential information on clouds susceptible to data breaches. However, this ‘trust gap’ is bridging fast, as cloud-based solutions are going for strict security measures.
Criteria
Cloud-based IDP software
On-premise IDP solution
Deployment
Hosted on cloud servers
Installed on local servers
Accessibility
Accessible from anywhere with an internet connection
Accessible only within the local network
Scalability
Scalable to handle large volumes of data
Limited scalability based on hardware capacity
Maintenance
Minimal maintenance required
Requires dedicated IT staff to maintain
Customization
Customizable according to specific business needs
Customization limited by available hardware resources
Integration
Easily integrates with other cloud-based services
Integration may require additional hardware
Security
High level of security provided by solution providers
Security is the responsibility of the organization
Cost
Charged on a subscription basis
Upfront costs for hardware and software licenses
Unlike IDP vs. template-based solutions, there’s no clear winner here. Both on-premise and cloud-based solutions will continue to be relevant; however, more and more companies will continue to go for cloud-based solutions.
Finally, by using AI-based document processing systems, companies can create much more efficient searchable records across multiple platforms, including email servers and databases. This makes it easier for employees to find relevant documents when needed. It also helps ensure that all documents are regularly updated, so they remain accurate and up-to-date at all times, which is critical for any organization looking to remain competitive in today’s marketplace.
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