Google has launched Gemini for Government, a secure AI platform priced at just 47 cents per year for federal agencies.
The platform is rolling out through a partnership with the Department of Energy’s (DoE) 17 National Labs. The partnership will support the U.S. government’s Genesis Mission, which aims to improve national scientific productivity. Procurement will be streamlined for agencies via the General Services Administration’s OneGov Strategy.
Google’s low-cost launch illustrates an aggressive effort to take a leading role in AI adoption across government research and operational workflows.
Agentic Workflows, Deep Research, and Federated Collaboration
Gemini for Government goes beyond standard chat interfaces to offer agentic AI workflows designed for complex scientific and operational tasks.
Its Deep Research tool can traverse decades of scientific literature and experimental databases to identify previously unseen connections or flag contradictory findings. The AI Co-Scientist, a multi-agent virtual collaborator, helps manage simulation ensembles and accelerates hypothesis development from years to days.
The platform supports multimodal reasoning, processing diverse data types including technical reports, code repositories, experimental images, and organizational datasets. Integrated tools such as NotebookLM assist with research synthesis, while Veo enables automated video generation for knowledge sharing.
All capabilities operate on Google Cloud’s secure infrastructure, with individual components holding FedRAMP High Authorization. The platform also supports federated workflows across the DoE National Labs. This will provide a foundation for collaborative, cross-laboratory research that can scale efficiently while maintaining data security.
Pricing, Procurement, and Big Team Science
Google’s 47-cent pricing model reflects its aim to position Gemini for Government as a foundational platform for what it calls “Big Team Science,” or large-scale, collaborative research across multiple labs and agencies.
Like the $1 contracts secured by OpenAI and Anthropic, this nominal pricing is a strategic mechanism to bypass procurement hurdles, allowing vendors to embed their infrastructure into federal workflows at minimal upfront cost and encourage integration.
However, Google’s established presence in federal cloud infrastructure strengthens its position against competitors. Meanwhile, Google’s approach stands out for enabling federated collaboration across DOE National Labs and other research entities. By integrating Gemini into mission-critical tasks early, agencies may develop long-term reliance on the platform, particularly as research is built around its capabilities.
The initiative underscores a broader trend: technology adoption in government is driven as much by policy mandates and procurement strategies as technical capabilities. Gemini for Government will reshape adoption pathways in federal research, influencing the future of government scientific workflows.
What This Means for ERP Insiders
Early adoption shapes agency workflows and integration. In a competitive federal AI market, vendors offered low-cost access to encourage early adoption. When similar opportunities arise in the private sector, ERP leaders may consider how early adoption may influence workflow design and future system integration.
Federated, agentic AI workflows are emerging as a defining trend. They combine autonomous task management, multimodal data integration, and secure cross-team collaboration, enabling organizations to automate complex research or operational processes efficiently. While adoption remains in its early stages, vendors are likely to incorporate these capabilities into next‑generation enterprise and research systems.
Policy and procurement guide AI adoption in government. Federal adoption of AI platforms like Gemini is shaped by pricing strategies, GSA OneGov contracts, and policy mandates, affecting how systems are integrated and scaled. ERP vendors and implementers should account for procurement and regulatory frameworks when planning government AI integration strategies.
