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Explore Why Ungoverned AI Connectivity Is Your Next Compliance Risk | AppDevANGLE with 9,935 views, 0 likes, and 0 comments. Experience the impact of this video content that has captured audience attention.

On this episode of AppDevANGLE, Paul Nashawaty speaks with Amit Naik, VP of AI Architecture at CData Software, about what a governed, production-ready AI connectivity layer actually requires and where enterprise teams are underestimating the complexity and cost of building it themselves. As organizations move from generative text use cases toward agentic systems that can read from and write to live business platforms, the exposure profile changes fundamentally. According to survey data, 29.2% of respondents cite high maintenance costs absorbing budget meant for new development as the primary operational risk their legacy systems present — and AI connectivity sits directly on top of that unresolved infrastructure debt. What we get into- How unscoped context windows create a compounding cost problem that can exhaust AI budgets well before a project delivers value - Why the shift to agentic AI demands a different governance posture than traditional RPA or workflow automation - How agent identity, permission scoping, and attribution to a human or upstream agent principal become compliance requirements at scale - Why open-source and vibe-coded MCP servers introduce OWASP-class vulnerabilities into core AI connectivity infrastructure - What a managed MCP platform provides that self-built connectors structurally cannot: consistent control, observability, and auditability 00:00 - Navigating Enterprise AI: Challenges, Compliance, and Connectivity 04:02 - Importance of Context in AI Models 06:57 - Real-Time Data Access and Token Economics 08:58 - Agentic AI and Data Quality 12:25 - Governance in Agentic AI 16:13 - Compliance Risks in AI Connectivity 19:34 - Conclusion and Where to Learn More

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