The commentary discusses the tension between regulating AI for safety and promoting innovation, emphasizing that investments in AI safety and security can foster sustainable development in Global Majority countries. It highlights the upcoming AI Impact Summit in India as a pivotal opportunity to align innovation priorities with safety-first approaches in international AI cooperation.
As artificial intelligence (AI) tools rapidly spread across industries, they present new cyber risks alongside their benefits. Brokers are advised to help clients navigate these risks by understanding AI use cases, establishing governance, and reviewing cyber policy language to ensure comprehensive coverage against emerging threats.
Pillar Security has developed an AI security framework called the Secure AI Lifecycle Framework (SAIL), aimed at enhancing the industry’s approach to AI security through strategy and governance. The framework outlines over 70 risks and provides mitigations to support secure AI adoption across various sectors.
IBM has introduced tools to help organizations manage AI systems they may be unaware of, addressing the growing challenge of shadow AI. With a significant number of employees using unapproved AI tools, the company aims to unify governance and security to mitigate associated risks.
The rise of AI agents in enterprise applications is creating new security challenges due to the autonomous nature of their outbound API calls. This “agentic traffic” can lead to unpredictable costs, security vulnerabilities, and a lack of control, highlighting the urgent need for a dedicated infrastructure layer to manage these interactions.
Pillar Security has developed an AI security framework called the Secure AI Lifecycle Framework (SAIL), aimed at enhancing the industry’s approach to AI security through strategy and governance. The framework outlines over 70 risks and provides mitigations to support secure AI adoption across various sectors.
IBM has introduced a unified AI security and governance software that integrates watsonx.governance with Guardium AI Security, claiming to be the industry’s first solution for managing risks associated with AI applications. This integrated approach enables enterprises to effectively manage security and governance risks across various AI use cases, ensuring compliance with multiple frameworks.
IBM has introduced the industry’s first software to unify AI security and governance for AI agents, enhancing its watsonx.governance and Guardium AI Security tools. These capabilities aim to help enterprises manage risks associated with AI use cases while ensuring compliance with various regulatory frameworks.
AI Copilots, such as Microsoft’s, present significant security, privacy, and compliance risks if not properly secured, potentially leading to data breaches and regulatory violations. Real-world incidents have already highlighted these dangers, indicating the urgent need for organizations to adopt a multi-layered approach to AI security and governance.
The emergence of artificial intelligence (AI) has fundamentally reshaped the cybersecurity landscape, acting both as a solution and a threat. As AI becomes increasingly embedded in cybersecurity practices, professionals must evolve their skill sets to include AI-driven governance, risk visibility, and compliance oversight.