Agentic AI represents a significant advancement in artificial intelligence,enabling proactive agents that can set goals,make decisions,and adapt to changing situations.However,the performance of these systems is heavi...Agentic AI represents a significant advancement in artificial intelligence,enabling proactive agents that can set goals,make decisions,and adapt to changing situations.However,the performance of these systems is heavily dependent on the quality and relevance of the data they process.This research highlights the critical risk posed by faulty,insecure,or contextually inappropriate input data in modern Agentic AI systems.To address this challenge,this study proposes the Autonomous Data Integrity Layer(ADIL).This flexible architecture integrates best practices from security engineering and data science to ensure that Agentic AI systems operate with clean,validated,and contextually relevant data.By focusing on data integrity,ADIL enhances the reliability,accountability,and effectiveness of Agentic AI systems,leading to more trustworthy and robust intelligent agents.展开更多
文摘Agentic AI represents a significant advancement in artificial intelligence,enabling proactive agents that can set goals,make decisions,and adapt to changing situations.However,the performance of these systems is heavily dependent on the quality and relevance of the data they process.This research highlights the critical risk posed by faulty,insecure,or contextually inappropriate input data in modern Agentic AI systems.To address this challenge,this study proposes the Autonomous Data Integrity Layer(ADIL).This flexible architecture integrates best practices from security engineering and data science to ensure that Agentic AI systems operate with clean,validated,and contextually relevant data.By focusing on data integrity,ADIL enhances the reliability,accountability,and effectiveness of Agentic AI systems,leading to more trustworthy and robust intelligent agents.
