Beyond Intelligent Document Processing: The Rise of Advanced Document Understanding
Artificial Intelligence (AI), encompassing intelligent document processing (IDP), has experienced a surge in adoption across various sectors. As organizations embrace digitization, IDP, an AI class, automates the processing of vast unstructured data volumes. Technologies such as machine learning, deep learning, and expert systems drive IDP, analyzing, categorizing, and retrieving pertinent data from unstructured records, including invoices and contracts.
AI, in its essence, is a machine or computer’s ability to learn from past experiences. It responds to various inputs, such as written prompts, images, and even mathematical problems. There are a myriad of artificial intelligence models today. For instance, dynamic content suggestions are available on social media platforms, and self-driving cars, such as Autox and Motional, use AI. Additionally, generative AI, like ChatGPT, can detect security vulnerabilities and write code.
Artificial intelligence can be categorized into machine learning, deep learning, and expert systems. Machine learning allows machines to learn from data and experience without explicit programming. This is evident in apps like Snapchat and TikTok, which apply interactive filters through machine learning.
On the other hand, deep learning deals with more complex patterns and datasets. It consists of neural networks that recognize patterns in input data. Google’s MetNet-2 neural network, which predicts weather twelve hours ahead, is a notable example of deep learning.
Expert systems mimic human decision-making. These are not self-aware but can scale up to human-level decision-making. For instance, AI of chest X-rays can identify the kind and stage of lung cancer by analyzing the image of the upper body.
To illustrate the fusion of these artificial intelligence types, let us consider Zillow Zestimate. The expert system notes that the smallest house on a block usually sells higher than another house of the same size elsewhere. Machine learning captures trends in home sales in specific zip codes, and deep learning analyzes thousands of listed homes’ images to derive insights.
In 2023, global artificial intelligence technology spending by businesses and governments will exceed $500 billion, revealing the scale of AI adoption. Artificial intelligence capabilities used by businesses have also grown from an average of 1.9 in 2018 to an estimated 3.8 in 2022.
Finally, businesses and governments must find the AI solutions best suited to their specific needs. While artificial intelligence enhances productivity, speed, and accuracy, it is not a one-size-fits-all solution. Therefore, careful evaluation and integration of artificial intelligence into business operations is crucial for the realization of its countless benefits.