Industries with lower tech budgets, like retail, must balance limited resources with growing demands for AI innovation.
Search Results: risk (1484)
Rapid adoption of AI-driven coding tools could lead to a significant rise in software vulnerabilities, challenging current security practices.
NIST’s newly released AI Risk Management Framework and GenAI Profile offer organizations vendor-neutral guidance to securely integrate AI technologies, aligning with the White House’s executive order for trustworthy AI development.
Veriato leverages GenAI and predictive security tools to enhance insider threat detection, productivity monitoring, and compliance, dynamically updating risk profiles to proactively safeguard organizations.
Despite its market leadership, Microsoft faces scrutiny over security lapses and the vulnerability exposed by software monoculture and the recent Crowdstrike incident.
Investigations that find AI firms bypassing a protocol that disallows certain content to be crawled highlight the need for, and current lack of, strong AI governance.
Databricks’ AI Security Framework illuminates the path to secure and compliant AI adoption, addressing critical security risks across various stages of AI systems.
Analyzing the role of AI in manufacturing, this CIO guide explores efficiency gains, quality control improvements, and predictive maintenance benefits, while addressing cybersecurity, data privacy, and technology dependency risks.
Supply chains have benefited from AI for years, but GenAI is introducing new capabilities including what-if scenarios, risk mitigation, and finding new opportunities.
Discover the hidden risks embedded in AI code, including false security assumptions and a pattern of bypassing policies.
NetRise’s AI-driven Trace feature transforms supply chain security, using semantic search and natural language processing to identify risks, offer context-rich insights, and create comprehensive asset graphs.
Episode 10: PayPal and VISA use AI to reduce payments errors; ConverSight raises funding to build generative AI for enterprises; and Hugging Face launches secure coding assistant.
Copilots bring AI functionality to everyday enterprise applications. Discover three use cases where they’re poised to make a difference, and risks to keep in mind.
Discover the top 10 Low-Code/No-Code vulnerabilities and how to secure rapid development environments.
There are several security risks associated with generative AI, including AI-powered social engineering attacks and evasion of traditional security defenses.
Discover why closing the loop by fixing code is essential to effectively combat the security risk of hard-coded secrets.
With its EU Sovereign Cloud, Oracle aims to address common risks associated with data residency, privacy, and management.
Manual code reviews have limitations in addressing the risks of hard-coded secrets, leading to a critical need for automated analysis in securing the software development process.
The speed of AI innovation is outpacing companies’ ability to understand, let alone manage, the risk. This is where leaders can take control.
Snyk provides developer-focused security for companies across every sector, enabling ongoing security improvements including reduced risk exposure.