Third-party cyber evaluations involving OpenAI models
openai.com·14h ago
Cloud & Infrastructure
Google Cloud Blog·20d ago·5 min read
IDC: Why the right networking approach is foundational to agentic AI
TL;DR
Enterprises face significant challenges in transitioning AI projects from pilot to production, primarily due to infrastructure issues. Key concerns include security, automation difficulties, and talent shortages.
✦ Why It Matters
Focus on enhancing your organization's networking infrastructure to better support AI project scalability and security.
Key Takeaways
- Assess your current networking infrastructure for AI readiness.
- Implement consistent security policies across distributed AI systems.
- Consider a balanced approach between platforms and best-of-breed tools.
- Invest in staff training to enhance AI operational capabilities.
Full Summary
A recent IDC survey highlights that 32.6% of enterprises struggle with security issues as AI workflows become more distributed, while 26.8% face automation challenges due to manual operations. Additionally, 24.7% cite limited staff skills as a barrier to moving AI initiatives into production.
Agentic AI, which involves dynamic interactions across various applications and services, exacerbates these issues by increasing the complexity of networking requirements. Effective networking is crucial for ensuring operational control, security, and governance across these distributed systems.
The survey indicates a divide between preferences for platform-based solutions versus best-of-breed tools, with organizations favoring platforms for their stronger security and reduced complexity. Ultimately, a balanced approach that combines the strengths of both strategies is necessary for successful AI deployment.