Xerox published a study that suggests that around 46% of the survey respondents stated to have wasted a significant amount of time because of excessive paperwork. About 50% of the firms have started using digital processing or are still planning to follow that path.
Indeed, digital files always have significant advantages over paper documents. Even though people are moving forward to a fully digital age, some areas, like public administration and justice, rely on paper because of outdated operational means.
These formal sectors can automate critical business processes thanks to AI and more such technologies. You can read more on How AI can change the future of the government sector.
There is a booming growth of the latest technology to optimize document digitization with the help of machine learning and artificial intelligence. You lag if your firm fails to take advantage of such modern technology.
Learning about AI and how it is used in digitization is essential. This article has compiled the top use cases of AI in content digitization. Let’s know about that in detail.
Content Recognition and Format Conversion
AI has now added multiple computational abilities to help recognize and analyze content in a textual or visual format.
Many organizations are now using machine learning and AI to help understand data patterns and metadata.
For that, some technologies are included in the list.
1. Speech Recognition
Audio and speech recognition algorithms are used these days. It helps in analyzing the wave patterns in the audio stream. These help determine the tone of voice, music, words, and other acoustic characteristics.
Natural language Processing (NLP) helps the system to make neural networks and understand the language, intent, tonality, etc. If the system is fed with appropriate data for learning, they can not only recognize mainstream language but can also differentiate vernaculars.
Natural language processing aims to combine not just computational linguistics but some other techniques, to help extract text meaning.
2. Image Recognition:
Image recognition analyzes patterns in videos or images to help distinguish objects. It helps in matching patterns against the chosen information. You can use image recognition to analyze Metadata for identifying the photo or video content.
Use Case: Using the CellStrat Hub’s image recognition AI module, an asset insurance company was able to save huge amount of money monthly. It helped recognize thousands of broken products sent by customers for the insurance claim and decided whether a claim could be processed or not.
Prescriptive and predictive ML algorithms will help to calculate the best actions to respond to activities, queries, and tasks.
3. Text to Speech and AI transcription:
AI can convert text Data into audio output and vice versa.
Speech Synthesis or Text to Speech (TTS) is an AI application that turns written text into audio. It is used not only to have machines to talk but also to make human-like natural voice of different ages and gender.
AI Speech transcription accurately converts audio into text with an API powered by AI technology. You are aware of Alexa, Google Assistant, and Siri; all these voice assistants are based on Speech AI.
4. Image to Text and Text to Image:
AI-based technology OCR stands for Optical Character Recognition. OCR is a prevalent technology to recognize text inside images, such as scanned documents and photos.
It can convert virtually any kind of Image containing written text (typed, handwritten, or printed) into machine-readable text data.
Similarly, AI tools can also convert Images into text descriptions. Automatic Metadata is one of the applications of text-to-image tools.
Generating Automated Content:
Creating new versions of the existing documents will ensure you waste a lot of time. Whenever new employees join a firm, they have to focus on company guidelines to regulate the internal working environment. Companies can speed up these procedures by automating documents through machine learning and AI.
Thanks to AI and its automated services, a new customer can easily register with an online system. The standard contract will be generated automatically! Furthermore, this process ensures that there isn’t any man-made error. Even the writing style remains consistent over here.
AI algorithms can learn past data and accurately predict future attributes. This can help in automatic generation of:
· Tax, invoices, and finance-related documents
· Human Resource files,
· Legal deeds, agreements, or contracts,
· Educational/ course materials etc.
Data analysis after extraction:
The current AI and ML ability to process a plethora of information automatically is helpful for many purposes. AI Algorithms can collect company, customer, and market data and necessary information from the live stream. After that, it can compare collected and sorted data with multiple document patterns. This step helps out companies to extract specified data from the said documents.
· One can procure information like the number of documents available in a domain.
For instance, entities that research and procure Intellectual Rights, trademarks, etc., have to peruse thousands of websites and documents on a large scale. Such analysis is possible through the inclusion of AI in search engines.
· You can further track down the current use of your document and significant figures to help identify changing trends and patterns.
Now employees can concentrate on their primary work and do not have to spend hours on routine tasks like document creation, invoice creation, and more!
Content Categorization and Processing:
Thanks to machine learning algorithms and AI, one can extract data to be used for other purposes. Machine learning tools capture and understand the content’s context automatically.
There are several AI APIs available that can easily be integrated with mobile and web applications. These APIs help in categorizing the content based on its context and intent.
· Documents can be divided into different groups or sorted by subject, date, area, and other classification data points.
· Major document management software already uses the power of optical character recognition (OCR) for reading out text content.
· It helps eliminate the time needed for manual processing and makes it easier to find documents once they got digitized. No longer need to invest any time or money handling physical document copies.
Content Management
AI is an effective way to administer documents and digital content. Previously, content management used to separate all the technical tasks like collections, sorting, analyzing, distribution, editorial assignments, information updates, and more.
The technical and non-technical support staff can now hand off some of the routine chores like content maintenance. AI-based tools make content management a lot easier.
AI tools also eliminate the need to edit documents and files individually, as AI makes neural maps of the content and updates it with a single command. It is a helpful factor for legal firms these days.
Now, legal firms can manage multiple document types of clients with the same course of legal proceedings.
For instance, a legal firm may handle several cases of land accusations. A new amendment in law needs to be reflected in every case’s documents. With the help of AI-powered document management software, legal firms can update all docs in the same category.
These tools also help in updating graphics with personalization and in bulk.
CellStrat Hub plays a pivotal role in developing such Ai tools to embark on AI disruption.
CellStrat Hub has helped many business entities, from start-ups to industry stalwarts, embed AI within their tools for quick and effective digitization.
Conclusion
Like content is evolving so are skills and tools to manage it. In future, AI and ML will help develop micro-experience enriched content. It enables intelligent processing and create new roles for the employees to work with. But such changes won’t happen overnight and will take some time!
AI algorithm needs employees with good experience and skills to implement and maintain the norms. However, this technology won’t exist in a vacuum. In its place, firms will tie AI to some predefined tasks to save the time and effort of human resources.
Artificial Intelligence indeed supplements human intelligence.
