Agentic AI represents a significant advancement, marking a shift from traditional AI tools to autonomous systems capable of decision-making and action in dynamic environments. Its adoption is seen in various sectors, highlighting its role in improving operational efficiency and ROI for organizations. However, as businesses integrate agentic AI, they face challenges regarding security vulnerabilities due to the technology’s interoperability across platforms.
Key security risks include data poisoning, which compromises system integrity and performance, and prompt injection threats that manipulate AI outputs through malicious instructions. To mitigate these issues, organizations are advised to map vulnerabilities within their tech ecosystems, conduct real-world attack simulations, and embed safeguards for real-time data protection. As agentic AI continues to evolve, the need for accountability structures becomes paramount, emphasizing human oversight and governance to ensure responsible usage within corporate frameworks.
👉 Pročitaj original: MIT Sloan Management Review
