Enterprise adoption of agentic AI is moving beyond experimentation and into operational deployment. As organizations work to scale AI agents across functions and environments, the challenge is no longer whether agents can deliver value, but how to govern, observe, and manage them responsibly in production. In this environment, the transition from pilot to production demands infrastructure that can support identity, access, policy enforcement, memory, and evaluation at enterprise scale.
To move agentic AI into real-world production environments, enterprises need more than model access alone. They need a platform that can address the barriers Futurum Research identifies as most critical to scale: governance and visibility, integration and context, and observability and evaluation. The most effective approaches provide a unified governance layer, persistent memory, integration flexibility, a path from no-code to full-code development, and the ability to simulate and evaluate agent behavior before and after deployment.
In our latest market brief, Gemini Enterprise: Governing and Scaling the Agentic Enterprise, completed in partnership with Google Cloud, Futurum Research examines what organizations require to move from pilot-stage agentic AI to governed, scalable production deployment. The report explores the infrastructure, governance, and lifecycle-management capabilities needed to support enterprise-ready agents, and assesses how Gemini Enterprise addresses those requirements through connected surfaces for developers, employees, and customer-facing workflows.
In this report, you will learn:
- Why the shift from pilot to production is changing enterprise requirements for agentic AI
- Which barriers most often prevent organizations from scaling agents in production
- What capabilities define a production-grade agentic platform
- How Gemini Enterprise addresses governance, observability, memory, and deployment flexibility
- Why identity, policy, evaluation, and long-context support are foundational to enterprise agentic AI at scale
If you are interested in learning more, be sure to download your copy of Gemini Enterprise: Governing and Scaling the Agentic Enterprise today.
Author Information
Nick Patience is VP and Practice Lead for AI Platforms at The Futurum Group. Nick is a thought leader on AI development, deployment, and adoption - an area he has researched for 25 years. Before Futurum, Nick was a Managing Analyst with S&P Global Market Intelligence, responsible for 451 Research’s coverage of Data, AI, Analytics, Information Security, and Risk. Nick became part of S&P Global through its 2019 acquisition of 451 Research, a pioneering analyst firm that Nick co-founded in 1999. He is a sought-after speaker and advisor, known for his expertise in the drivers of AI adoption, industry use cases, and the infrastructure behind its development and deployment. Nick also spent three years as a product marketing lead at Recommind (now part of OpenText), a machine learning-driven eDiscovery software company. Nick is based in London.
Brad Shimmin is Vice President and Practice Lead, Data Intelligence, Analytics, & Infrastructure at Futurum. He provides strategic direction and market analysis to help organizations maximize their investments in data and analytics. Currently, Brad is focused on helping companies establish an AI-first data strategy.
With over 30 years of experience in enterprise IT and emerging technologies, Brad is a distinguished thought leader specializing in data, analytics, artificial intelligence, and enterprise software development. Consulting with Fortune 100 vendors, Brad specializes in industry thought leadership, worldwide market analysis, client development, and strategic advisory services.
Brad earned his Bachelor of Arts from Utah State University, where he graduated Magna Cum Laude. Brad lives in Longmeadow, MA, with his beautiful wife and far too many LEGO sets.
