Even if you've banned AI, your employees are 100% using it. 🥵
To make matters worse?
Even if you've approved a certain AI system, your teams are probably using whatever they want.
And those choices are likely putting your enterprise data at risk.
So, how do you reel in manage the AI sprawl?
Kevin Kiley, the CEO of Airia, is laying out the playbook.
Out of the Shadows: How to Manage AI Sprawl -- An Everyday AI Chat with Jordan Wilson and Kevin Kiley
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Topics Covered in This Episode:
- AI Sprawl Challenges for Enterprises
- Shadow AI and Security Risks
- Centralized AI Management Platforms
- Model Agility and Vendor Lock-In Solutions
- Secure Sandbox for Model Testing
- Financial Impact of AI Sprawl
- Agentic AI Security Concerns
- Steps to Discover and Control Shadow AI
Timestamps:
00:00 Navigating AI Chaos & ROI
04:30 AI Tool Chaos and Security Risks
09:45 Employee Decisions Risk Data Security
12:50 Managing AI Complexity and Security
16:31 "Agility and AI Vendor Risks"
19:50 Model Performance Testing and Flexibility
22:31 "AI Investments Failing Businesses"
25:44 "AI Risks: Security and Weaponization"
28:39 "AI Awareness and Discovery"
Keywords:
AI sprawl, shadow AI, managing AI chaos, enterprise AI security, AI orchestration platform, unsanctioned AI tools, AI spaghetti, AI agents, business process automation, secure AI implementation, modular AI setup, model garden, vendor lock-in, multiple AI models, open source AI, GenAI ROI, financial risk of AI, prompt injection attack, indirect prompt injection, agentic AI, token consumption, AI operational complexity, departmental AI usage, security vulnerabilities, data protection, unauthorized AI tools, central inventory for AI tools, scalable AI solutions, cloud AI attacks, domain-specific models, failover models, autonomy in AI agents, model benchmarking, latency testing, budget management for AI, positive ROI on AI, cross-platform AI management, AI system redundancy, natural language security risks, AI-powered business growth, AI strategy for organizations, business continuity with AI agents, large language models evolution, AI-driven productivity.
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