New Use Cases of ChatGPT and IDP in Automation Processes
Updated: Apr 20
This year, significant hype has surrounded artificial intelligence (AI) development, which is expected of any new emerging technology in the market. According to Gartner’s hype cycle report, product innovations, such as biochips, self-driving cars, and personal assistants, have followed ‘a typical progression of innovation, from overenthusiasm through a period of disillusionment to an eventual understanding of the innovation’s relevance and role in a market or domain’.
Today, the most iconic and prospective artificial intelligence developments are generative pre-trained transformer (ChatGPT) and intelligent document processing (IDP). According to the Markets and Markets report, the chatbot market size is estimated to increase from €2.6 billion in 2021 to €9.6 billion in 2026. Meanwhile, per the Market Research Future report the IDP market is projected to grow from € 1.35 million in 2022 to € 13.58 million by 2030.
In this publication, we will study the definitions and features of ChatGPT and IDP and the new use cases of these two technologies.
Definition and features of ChatGPT
Different opinions about ChatGPT have flooded the internet. While some people have invested in this technology and claim it is the best development ever, others have criticised AI technology for taking jobs and destroying creative fields. ChatGPT is a new chatbot based on a large language model (LLM) that understands the prompts left by users and creates answers to their requests. To do so, it has been pre-trained with a wide range of vocabulary and extensive general knowledge. ChatGPT can make predictions, such as AI solutions, by using prompts to predict what information users are seeking. It can provide encyclopaedia-level information with listed data, such as telephone numbers and addresses. Moreover, it creates original sentences with words that mimic how humans write. For example, between March and April 2023, the Italian newspaper Il Foglio published one ChatGPT-generated article per day on its official website.
However, the accuracy of the information provided by ChatGPT varies. While you can use this instrument to generate ideas in creative fields, you probably do not want to ask for legal advice. We believe that the real skill in using this development is the quality of the prompt. The more accurately you use words in this chatbot, the more relevant replies you receive.
The impact of ChatGPT on the market
LLM can be applied in different business industries. The greatest impact these models have shown is in the areas of marketing and journalism, which are both supporters and detractors of ChatGPT. People who suppose that ChatGPT will destroy the need for human writing are incorrect. Fact-checking, editing, and confirming that the tone of voice fits a brand strategy are weaknesses of this new technology.
AI generates texts that may seem credible. However, in industries where accuracy is critical, receiving inaccurate output that sounds like what someone said, rather than precise quotes, may cause problems.
Definition and features of IDP
IDP with the convolutional neural network (CNN) — one of the first deep learning models — was developed in the 1990s. This technology was used by banks to automatically process checks and by post offices to automate the input of handwritten mailing addresses. The discipline has since developed into optical character recognition (OCR)-based approaches.
Today, IDP applies various synergetic technological instruments. Modern IDP systems are based on computer vision, natural language processing (NLP), deep learning, and machine learning (ML) techniques. They are used to gather information from a document, check that it has been analysed correctly, extract relevant data and perform intelligent processing. While OCR perfectly transcribes errors, document processing instruments, which are AI driven, are responsible for higher accuracy and permanent improvements.
As mentioned, the core goal of IDP is to transform unstructured, semi-structured, and structured documents into usable digital data. Due to statistics, 80% of business data is presented in unstructured formats, such as emails, paper documents, images and PDF files. Business data requires the integration of different technologies to transform it into machine-readable files. There are also many industries in which this technology can be applied, such as banking, logistics, manufacturing, government, retail, etc. According to the McKinsey Global Executives Survey, 70% of respondents said that their organisations are at least piloting the automation of business processes in one or more business units or functions.
The impact of IDP on the market
IDP technology has had the greatest impact on the banking sector. Depending on key clients, a typical banking company may have several departments, such as insurance, debt collection and separate corporate and private client branches.
In the past, internal manual processes related to documents prevented cost reduction and the acquisition of new clients. Banking management indicated that they had concerns over time and that resources were wasted on manual consumer data processing. Some banks saw their market share reduced, losing to modern alternatives that captured the attention of younger clients.
Today, more banks apply modern IDP systems to effectively manage document workflows. Clerks working in branches no longer spend hours on manual data input. Most paperwork is digitised immediately, without the need to collect papers and only then to digitise paper. Automated document processing has helped the banking industry reduce the risks associated with sunk costs and outdated processes.
Use cases of IDP and ChatGPT
For this publication, we researched how ChatGPT, the next-generation LLM, could be applied to IDP and unstructured data processing (UDP) markets.
We believe that LLM can enhance IDP and UDP in the following ways:
1. Document classification
ChatGPT can be used to classify documents based on their structure or content. For instance, it can be trained to distinguish between different types of invoices. It can also recognise whether a file is a contract or an email.
2. Named Entity Recognition (NER) ChatGPT can identify and extract named entities, such as people, organisations, and addresses from documents. This feature can be used when you need to identify key stakeholders in a contract or extract contact information from business cards. 3. Text extraction ChatGPT can be used to extract information from images or scanned documents by using OCR technology. This feature can help extract information from forms and digitise paper documents. 4. Text summarisation ChatGPT can be used to create summaries of long documents or emails. For example, to provide a high-level overview of a contract or to summarise a news article. This could be valuable for people who need to quickly understand what a document is about without having to read the whole thing. 5. Sentiment analysis ChatGPT can be used to analyse text data for insights. For instance, to understand customer sentiment in reviews or to identify topics that are being discussed on social media. This technology could provide businesses with valuable insights to help them make better decisions.
ChatGPT and IDP have had a major impact on various business sectors in recent years, particularly affecting marketing, journalism, finance, and logistics. The use of ChatGPT and IDP makes time-consuming, monotonous, and tedious document processing easier and less prone to manual errors. In this way, data in a variety of formats becomes more effective, supporting increased productivity and operational efficiency.
IDP technology addresses the market need to process large volumes of semi-structured and unstructured documents with greater accuracy and speed. Meanwhile, the development of chatbots aims to provide 24/7 customer support at a lower operational cost, self-service operations, and customer engagement across multiple channels.
Together, ChatGPT and IDP can deliver great results — improving the accuracy of data extraction, responding to natural language commands about critical business information, and easily creating new UPD and AI applications. In addition, IDP platforms using ChatGPT functionality can also improve customer intent identification, summarise conversations, answer customer questions, and direct customers to resources.