Closing the AI Confidence Gap: Cloud-Native Security as a Key to Agentic AI Adoption
In our latest market report, Closing the AI Confidence Gap: Cloud-Native Security as a Key to Agentic AI Adoption, completed in partnership with Google Cloud, Futurum Research explores how enterprises can move beyond fragmented security approaches to adopt platform-native models that enable secure…
Futurum's Fernando Montenegro,
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Fernando Montenegro, The Futurum Group, "Closing the AI Confidence Gap: Cloud-Native Security as a Key to Agentic AI Adoption," April 23, 2026. https://preview.erikbethke.com/research-reports/closing-the-ai-confidence-gap-cloud-native-security-as-a-key-to-agentic-ai-adoption/
As enterprises accelerate AI adoption, they are moving beyond early experimentation toward operationalizing agentic AI systems that can plan, act, and execute workflows autonomously. This shift introduces new levels of complexity and risk, particularly as AI systems interact directly with sensitive data, systems of record, and core business processes. While organizations continue to invest heavily in AI innovation, confidence in their ability to secure these environments has not kept pace, creating a growing gap between ambition and execution.
To close this gap, security must evolve alongside AI adoption rather than lag behind it. Traditional, bolt-on security approaches introduce architectural blind spots, integration complexity, and operational friction that are increasingly incompatible with dynamic, non-deterministic AI systems. Instead, organizations are beginning to adopt platform-native, cloud-based security models that provide integrated visibility, lifecycle protection, and governance across the full AI stack—from infrastructure and data to models and autonomous agents.
In our latest market brief, Closing the AI Confidence Gap: Cloud-Native Security as a Key to Agentic AI Adoption, completed in partnership with Google Cloud, Futurum Research examines the structural shift required to secure AI at scale. The report explores the limitations of legacy security architectures, outlines the requirements for full-stack AI defense, and highlights how platform-native approaches can enable organizations to innovate with greater confidence and control.
In this report, you will learn:
- Why the transition to agentic AI fundamentally changes enterprise security requirements
- The risks and limitations of traditional “bolt-on” security models in AI environments
- Key architectural principles for securing the full AI stack, including lifecycle protection and unified visibility
- How governance, sovereignty, and red teaming play a critical role in enabling trusted AI adoption
- How Google Cloud approaches platform-native AI security to support scalable, secure innovation
If you are interested in learning more, be sure to download your copy of Closing the AI Confidence Gap: Cloud-Native Security as a Key to Agentic AI Adoption today.
Published by Futurum.
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