Challenges of Integrating LLMs Like ChatGPT with Enterprise Software and Solving it with Object Messaging and Intelligent Objects as a New Software Design Paradigm

The proliferation of AI tools, such as ChatGPT and other Large Language Models (LLMs), has raised expectations regarding their widespread adoption in the workplace. However, this paper delves into the limitations that hinder the deep integration of LLMs with existing software applications used in business environments. While LLMs excel in processing natural language, conventional software applications mostly communicate structured information in a rigid fashion. To bridge the gap between human usage of natural language and the structured data utilized by existing applications, communication tools such as email and Slack emerged. While these tools filled the void by accommodating the informality of chat-like interactions, they struggled to incorporate the applications' structured data. The prevalent form-based models employed by existing software applications present a fundamental obstacle for a meaningful AI integration. This paper examines the challenges of integrating LLMs with form-based software, shedding light on the associated complexities and introduces a new design paradigm, Object Messaging Model and Intelligent Objects (OMIO). By leveraging this model, natural language and structured data become logically combined while enabling seamless integration of LLM capabilities within the software application. This paper provides insights into the potential of the OMIO and paves the way for unlocking the transformative power of LLMs, resulting in highly enhanced productivity within the contemporary business landscape. The Object Messaging paradigm offers an elegant path for deep integration of LLMs and software applications with structured data, while optimizing communication among humans in the workplace producing humans and AI collective intelligence.