Artificial Intelligence (AI) is a dynamic and fast-growing field that many businesses are beginning to adopt into their models to streamline processes and increase efficiency. It is such a fast-growing field that Ark Invests predicts that by 2023, AI will add $200 trillion to global economic output. Some examples of AI models that are well-known include content removal on social media (Twitter, Facebook, Instagram), self-driving cars, and generative AI (like ChatGPT). Let’s explore more about advanced document understanding below.
There are some key terms to be familiar with when understanding what AI is. First is machine learning which is the ability of a computer to learn, identify patterns, and make predictions without being programmed. Next, is the application programming interface. These are the rules that process data transfers between systems. Another key term is data extraction which is the ability to pull and identify information from large sources. JavaScript Object Notation is the format used for storing and transporting data. Finally, optical character recognition is the ability to recognize or extract text from images or documents.
How exactly do these AI models work? Artificial Intelligence works by having a computer or machine learn from previous experiences. More so, through AI, machines can understand as well as respond to written prompts, math problems, and even images.
There are different types of AI, each with its functions. First is machine learning which is used by companies like TikTok and Snapchat to allow users to apply interactive filters. Machine learning is not manually programmed and is able to learn from data or experiences. The next type of AI is deep learning which is used by Google’s MetNet-2 neural network to predict the weather as much as twelve hours ahead. Deep learning differs from machine learning because it can deal with more complex data and patterns. Finally, expert systems mimic human decision-making.
Four Categories of AI Applications
To further understand AI, one should note the four categories of AI applications. First is generative AI which works by having algorithms use old data to create new content. Next is predictive analytics, which engages in data mining and statistical analysis to predict future events. Natural language processing is the next category of AI application. It works by enabling computers to understand and respond to human language. Finally, computer vision is a category of AI that interprets and understands digital images.
Because of the numerous categories and types of AI, businesses are quickly beginning to adopt some of its capabilities. For example, businesses are using AI capabilities like automatic processes, deriving information from media (computer vision), and talking to date Natural language text understanding). AI capabilities used by businesses today have nearly doubled since 2018.
Additionally, businesses are using AI because of its numerous functions. Some of the most popular functions of AI include service operations optimization (24%), the creation of new AI-based products (20%), and customer service analytics (19%). Other popular functions of AI include customer segmentation, new AI-based enhancements of products, customer acquisition, and lead generation. Some of the less popular, but still unique functions of AI, include call center automation, product feature optimization, risk modeling & analytics, as well as predictive service & interpretation.
What are some of the benefits of AI for businesses? First off, AI can increase businesses efficiency and productivity, it can also result in greater speed. AI can also improve monitoring for businesses and result in higher quality and increased accuracy. Finally, AI results in enhanced talent management, therefore can streamline the hiring process.
There are five steps to successfully incorporate AI into business operations. The first is to define business needs, like defining what problems need to be solved. Next is to set near-term goals, about the financial benefits of AI and the use of AI in daily operations. The Next step would be to evaluate business capabilities and determine which approach will work best. Step four would be to prepare the data. Finally, to successfully incorporate AI into business, start small, like using small sample data sets.
Advanced Document Understanding and Conclusion
To better understand AI and how it can be used, two examples of it are described below. Lazarus AI is a type of advanced document understanding that extracts data from any document of any format, language, or type. Furthermore, it requires no training. RikAI does not need to gather or label training data. Both RikAI and Lazarus AI contextualize information to analyze it and find answers to questions.
