A New Era of AI Infrastructure and Agentic Workflows 

/ AI, Application Development, Programming, Software Development

Government & regulated-industry focus signals broader implications for enterprise app development

The News

During the October 2025 Google Public Sector Summit in Washington, D.C., Google Cloud outlined a sweeping set of announcements aimed at empowering the public sector, many of which have direct implications for enterprise application development and modernization.

Key announcements include:

  • Public-sector organizations reported that 46% have seen productivity double or more as a result of generative AI deployment, and 42% of respondents have deployed more than ten AI agents
  • The launch of Gemini for Government, a secure, enterprise-grade agentic AI platform, with features including an AI Agent Gallery, agent-to-agent communication protocols, connectors into enterprise data sets, and pre-built agents
  • A deepened partnership between Google Cloud and NVIDIA, bringing Gemini models into on-premises and fully air-gapped environments for sensitive mission workloads
  • New investment in the partner ecosystem for public-sector pilots, including enhanced badges, training and financial support through the Partner Connect programme

Analyst Take

The public-sector announcements are significant not just for government agencies but for the broader enterprise application landscape. With Gemini for Government launching connectors, agent-to-agent protocols, and an Agent Gallery, this signals the maturation of agentic AI platforms as a development foundation, not just for domain-specific workflows but for generalized application services. Enterprises can look to these public-sector frameworks as a model for building internal platforms where multiple AI agents collaborate, are governed centrally, and integrate with data ecosystems.

For developers and modernization teams, the implications include building applications that treat AI agents as first-class components, designing for agent-to-agent choreography, and architecting agent lifecycle management. This shifts the application development paradigm from “embed an AI model” to “compose an ecosystem of agents” that coordinate, delegate and integrate within app workflows.

On-Premises & Sovereign Infrastructure Unlocks Modernization in Regulated Industries

A key development is the extension of Google’s AI capabilities into on-premises and air-gapped environments via its partnership with NVIDIA. For industries such as financial services, healthcare, defense and manufacturing (where data sovereignty, compliance, and latency matter), the ability to develop and deploy agentic AI within controlled infrastructure is a game-changer.

Modernization initiatives in such sectors often stall at the infrastructure boundary: cloud only, or isolated islands. With Google Cloud and NVIDIA enabling agentic AI factories in hybrid or sovereign settings, enterprise application development opens up to AI-first workflows even in constrained infrastructure environments. Developers must now plan for “AI-native” applications that respect governance, but still deliver agile innovation.

Productivity Gains and Workforce Transformation

Google’s ROI survey results (46% of public-sector organizations doubling productivity, and 42% deploying more than ten agents) align to a broader trend where AI agents are becoming labor multipliers. For enterprise application development, this means that modern apps must incorporate agent-integrated user experiences, where workflows are enhanced by intelligent assistants and automation rather than merely augmented.

Development teams will need to invest in agent UX design, agent governance, and change management for this like how users switch from manual steps to agent-orchestrated workflows, how those agents get trained with enterprise data, and how the app monitors and adapts agent behavior over time.

Partner Ecosystems and Platform-Driven Innovation

The focus on partner programs and the Agent Gallery shows that Google Cloud is evolving its ecosystem to support platform-led application development, rather than point solutions. For enterprises considering modernization, this suggests a shift toward platform partnerships, reuse of agent libraries, and collaborative marketplaces. Application development strategy now includes selecting an agent marketplace, integrating pre-built agents, and managing extension points, similar to how mobile apps rely on app stores and SDKs.

For example, a modernization project may now include: “Which agents from the gallery do we adopt?”, “How do we govern them?”, and “How do we integrate them into our custom workflows?” This raises the importance of architectural practices around agent composition, catalog management, and governance pipelines.

Looking Ahead

These public-sector announcements prove that application development is no longer just about building traditional user-interfaces and back-end services, but about designing and orchestrating intelligent agent ecosystems. Enterprises embarking on modernization projects should prioritize three areas in the upcoming 12–24 months:

  • Agent architecture planning: define how agents will be discovered, composed, governed and evolve
  • Hybrid/sovereign AI infrastructure: ensure your application platforms can host agentic AI in compliant, controlled environments
  • Agent-first user experience: shift from apps that embed models to apps that build on agent orchestration, enabling workflows where agents assist, inform, and act

As application development teams align to this new model, the winners will be organizations that move beyond “AI as a feature” toward “agents as infrastructure,” where applications are woven from cooperating, governed AI agents working across data, workflows and users.

Key Takeaways

  • Platform-led development: Agent ecosystems (via Gemini for Government) become central to application design.
  • Sovereign AI infrastructure opens up modernization in regulated and hybrid environments.
  • AI agents are significantly boosting productivity (46% of public sector organizations) and scale (42% deploy >10 agents).
  • Development must shift from point-models to agent-orchestration, governance and lifecycle management.
  • Partner ecosystems (Agent Gallery, marketplace) shape future application extension and reuse strategies.

Authors

  • Paul Nashawaty

    Paul Nashawaty, Practice Leader and Lead Principal Analyst, specializes in application modernization across build, release and operations. With a wealth of expertise in digital transformation initiatives spanning front-end and back-end systems, he also possesses comprehensive knowledge of the underlying infrastructure ecosystem crucial for supporting modernization endeavors. With over 25 years of experience, Paul has a proven track record in implementing effective go-to-market strategies, including the identification of new market channels, the growth and cultivation of partner ecosystems, and the successful execution of strategic plans resulting in positive business outcomes for his clients.

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  • With over 15 years of hands-on experience in operations roles across legal, financial, and technology sectors, Sam Weston brings deep expertise in the systems that power modern enterprises such as ERP, CRM, HCM, CX, and beyond. Her career has spanned the full spectrum of enterprise applications, from optimizing business processes and managing platforms to leading digital transformation initiatives.

    Sam has transitioned her expertise into the analyst arena, focusing on enterprise applications and the evolving role they play in business productivity and transformation. She provides independent insights that bridge technology capabilities with business outcomes, helping organizations and vendors alike navigate a changing enterprise software landscape.

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