Agentic AI in Business Processes

open_access
Open Access
Author:
Modi, Dhruv
Area of Honors:
Information Sciences and Technology
Degree:
Bachelor of Science
Document Type:
Thesis
Thesis Supervisors:
David Joseph Fusco, Thesis Supervisor
Carleen Maitland, Thesis Honors Advisor
Keywords:
AI
Artificial Intelligence
GenAI
Generative AI
Agentic
Agentic AI
BPA
Business Process Automation
Automation
Abstract:
The rapid growth of Artificial Intelligence (AI) has led to the act of many people, groups, and organizations taking advantage of the unforeseen capabilities that this growing technology brings. More specifically, organizations and businesses have used AI to transition into a new form of business automation, which is led by the rise of automated systems that are capable of processing and perceiving data in order to make practical business decisions. This technology is called agentic AI, and it is one of the newest technologies that massive companies and organizations are looking to implement in order to make business processes more efficient. Unlike traditional machine-learning applications, agentic AI uses analytical decision-making paired with available data to curate decisions for different areas of operations within a business for both short-term and long-term decisions. This study investigates how secure and achievable the integration of agentic AI is for businesses in various areas of responsibility. It explores how agentic AI can prove to be useful when automating different processes and identifying various risks, while also showcasing how the risks of integrating agentic AI can be mitigated through following structured frameworks. This research will also cover how compliance, ethical, and technical issues can be major drawbacks for organizations looking to implement agentic AI into their processes, along with heavy cost considerations and abundant amounts of processed data that is required to be available. Ultimately, this study will contribute to the ongoing noise that artificial intelligence has brought to our daily lives, and will provide more information on how businesses can implement agentic AI in their systems in the most efficient way.