Tag Archives: Federal Government

Better Together: How Nutanix and Omnissa Are Building the Modern Government Workspace

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Public Sector IT leaders navigate rapid change including geopolitical shifts, evolving cyber threats, vendor consolidation and pressure to do more with constrained budgets. For agencies modernizing end-user computing (EUC) and digital workspace environments, progress increasingly depends on integrated infrastructure, flexible architecture and trusted partnerships. Nutanix and Omnissa, distributed by Carahsoft, The Trusted It Solutions Provider™, deliver a combined platform that reduces complexity, accelerates deployment and keeps agency employees productive and secure.

A Partnership Built for the Public Sector

Carahsoft is the bridge between technology innovators and Government agencies, providing procurement vehicles, technical resources and partner support that simplify adoption. That relationship extends to Nutanix and Omnissa, with Carahsoft serving as a distribution partner that helps Federal, State, Local and Education agencies access both platforms through streamlined procurement. The partnership spans years of General Services Administration (GSA) Schedule contracting support, proof-of-concept assistance and technical resources that help agencies evaluate, deploy and scale their environments with confidence.

Nutanix brings a unified, software-defined infrastructure platform that combines compute, storage and virtualization into one hyper-converged stack. Rather than managing firmware updates across siloed server, storage and networking components, agencies can use Nutanix Prism Central and its Lifecycle Manager (LCM) to manage lifecycles holistically, reducing administrative overhead and compatibility risks. Nutanix’s cloud platform, NC2, also enables consistent operations across on-premises environments, AWS, Azure and Google Clouds without requiring agencies to re-architect their applications.

Omnissa is fully focused on the modern digital workspace. Through Workspace ONE, Omnissa unifies management of virtual desktops (VDI), mobile devices and Software-as-a-Service (SaaS) applications while providing enterprise-grade security, conditional access and unified endpoint management (UEM). Omnissa also uses AI to proactively monitor and improve the digital employee experience, identifying performance issues before they affect end users.

A Stronger Solution Together

The integration between Nutanix and Omnissa Horizon on AHV, Nutanix’s native hypervisor, reached general availability at the end of December 2025 and has seen significant market response. Its beta program was the largest and most successful in Horizon’s history, and within weeks of general availability, the combined solution had already scaled to over 70,000 users. That momentum reflects real demand from agencies seeking a high-performance, fully supported alternative that avoids the constraints of legacy vendor agreements.

The technical case for combining the platforms centers on optimization. Running Horizon on Nutanix’s hyper-converged infrastructure positions compute and storage in the same stack, delivering measurably stronger VDI performance than traditional three-tier architectures. The operational experience combines Nutanix’s infrastructure management through Prism with Horizon’s app delivery and provisioning capabilities, including App Volumes, giving IT teams a more unified view across their virtual desktop environment. The outcome is faster deployment, lower total cost of ownership and reduced complexity.

Nutanix and Omnissa Better Together Blog, embedded image, 2026

Rethinking How Apps Are Delivered

One meaningful Omnissa capability is its apps-on-demand delivery model through App Volumes. Many agencies still use persistent desktop environments, pre-loading large application libraries onto each VDI instance whether or not they are needed. For engineering teams managing hundreds of applications, this creates unnecessary bloat, complicates patching and introduces avoidable performance overhead.

Omnissa shifts that model by delivering applications on demand, so they are available when needed without the administrative burden of persistent installation. This speeds patching, reduces the management footprint and gives IT teams tighter control over the application environment.

Addressing the Evolving Demands of Government IT

The Nutanix and Omnissa partnership is designed to grow with agency requirements. Hybrid deployments spanning on-premises data centers and cloud environments are now the norm, and both platforms support that reality. Nutanix Cloud Cluster (NC2) enables Nutanix workloads to run natively on AWS and Azure while maintaining consistent management while Omnissa Horizon extends seamlessly across those environments so agencies can place workloads based on performance, compliance and cost requirements.

Licensing flexibility reinforces that adaptability. Nutanix offers End-User Computing (EUC) licensing on a per-user basis so agencies can license per user or by core count. For organizations with power users who need high-performance environments, this model delivers direct cost savings, a meaningful consideration for Public Sector agencies that must justify every technology investment.

Security is embedded, not added on. Nutanix incorporates Nutanix Flow Network Security micro-segmentation and Zero Trust networking capabilities at the infrastructure layer while Omnissa brings conditional access policies, endpoint compliance enforcement and AI-driven threat monitoring at the workspace layer. Together, they create a layered security posture that supports the rigorous Government compliance demands.

Simplifying the Path to Modernization

For agencies running VMware or Citrix environments and navigating the complexity of transition costs, structured migration support removes a common barrier to change. Nutanix and Omnissa both offer migration tools, validated reference designs, pre-sales architects and post-sales services teams designed to move agencies from existing platforms to the integrated stack. Environment sizing tools help partners and agencies right-size deployments before committing resources, reducing the risk of over- or under-provisioning.

Preparing for an AI-Driven Future

Looking ahead, both organizations are investing in AI integration as a core platform capability, an approach particularly relevant for Public Sector agencies working to adopt AI responsibly. Nutanix supports AI and containerized workloads on the same infrastructure used for VDI, using Nutanix GPT-in-a-Box and reducing the need for separate AI infrastructure. Running AI workloads in a virtualized environment has also shown total cost of ownership (TCO) advantages over bare-metal deployments.

Omnissa is building AI into autonomous digital workspace management, enabling more self-healing, self-optimizing environments that detect and resolve performance issues before they impact productivity. For agencies exploring AI use cases, VDI environments offer a controlled deployment path that routes sensitive data within agency boundaries rather than public cloud AI services.

For Public Sector agencies evaluating their next phase of IT modernization, the combination of Nutanix’s infrastructure simplicity, Omnissa’s workspace management depth and Carahsoft’s procurement and support ecosystem represents a practical, proven path forward.

To learn more about the Nutanix and Omnissa integrated solution, including the general availability of Omnissa Horizon 8 support for Nutanix AHV, visit the Omnissa blog.

Carahsoft Technology Corp. is The Trusted Government IT Solutions Provider, supporting Public Sector organizations across Federal, State and Local Government agencies and Education and Healthcare markets. As the Master Government Aggregator for our vendor partners, including Nutanix and Omnissa, we deliver solutions for Geospatial, Cybersecurity, MultiCloud, DevSecOps, Artificial Intelligence, Customer Experience and Engagement, Open Source and more. Working with resellers, systems integrators and consultants, our sales and marketing teams provide industry leading IT products, services and training through hundreds of contract vehicles. Explore the Carahsoft Blog to learn more about the latest trends in Government technology markets and solutions, as well as Carahsoft’s ecosystem of partner thought-leaders.

Making Existing Government Intelligence Systems Agentic Without Losing Control

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How an Agentic Intelligence Fabric connects the tools agencies already use.

Government and enterprise intelligence teams do not usually suffer from having too few tools.

They suffer from having too many tools that do not work together.

An analyst may work across OSINT platforms, risk intelligence feeds, investigative databases, geospatial tools, link analysis software, internal knowledge bases, case management systems, spreadsheets, ticketing workflows, chat channels and reporting templates.

Each system may be valuable. Each may be approved, procured, trained and trusted for a specific part of the mission.

But the work between them is often manual.

Analysts copy data from one tool into another. They reconcile entity names by hand. They compare screenshots, exports, notes, alerts, maps and source references across disconnected environments. They merge findings into a case narrative after the fact. They preserve evidence in one place, make judgments in another and produce reports in a third.

This is where intelligence work slows down.

It is also where risk enters.

The next step for Government AI is not to replace trusted platforms with a standalone AI application.

The next step is to connect existing systems into governed agentic workflows that can retrieve context, compare signals, merge findings, preserve evidence and support human judgment without losing auditability or control.

That is the role of an Agentic Intelligence Fabric.

The Real Problem Is Tool Fragmentation

OSINT is essential to modern intelligence and risk work. Publicly available information, media, infrastructure data, corporate records, social platforms, geospatial signals, breach data and live event streams can all help analysts understand what is changing in the world.

But most organizations do not consume OSINT through one clean workflow.

They consume it through many tools.

One tool may surface an entity. Another may provide enrichment. Another may hold geospatial context. Another may contain internal history. Another may hold the case file. Another may be used for reporting. Another may be where the final decision is documented.

The problem is not that these tools are useless. The problem is that they rarely share operational context.

They do not automatically know that two slightly different names refer to the same organization. They do not preserve the analyst’s reasoning across systems. They do not carry uncertainty from discovery into reporting. They do not maintain one accountable path from source to case to decision.

When tools are disconnected, analysts become the integration layer.

That is expensive, slow and fragile.

It creates practical questions that matter under pressure:

  • Where did this claim come from?
  • What evidence supports it?
  • What weakens it?
  • Which tool produced this signal?
  • Which system has the most recent context?
  • Which duplicate entity should be merged?
  • What assumptions are being made?
  • What was copied manually?
  • Who accepted those assumptions?
  • What decision is this work meant to support?

These are not cosmetic workflow issues. They are intelligence quality issues.

Merging data is not clerical work when the decision depends on whether the merge is correct.

If the wrong records are joined, a weak correlation can become an assessment. If source context is lost, a claim can become harder to challenge. If evidence is copied without provenance, the output may look clean while becoming less defensible.

The real problem is not OSINT alone.

The real problem is disconnected intelligence operations.

Agentic AI Changes the Workflow

AI agents create a practical way to address this problem.

Instead of using AI only to summarize a document or answer a question, agentic systems can perform sequences of work across approved tools: retrieving context, calling APIs, comparing entities, checking case history, preserving source references, preparing analyst-ready outputs, flagging uncertainty and routing tasks to the right human decision point.

That matters because the analyst’s real burden is often not one difficult query.

It is the repeated movement across systems.

An agent can help search an approved OSINT platform, compare the finding with internal case context, check whether an entity already exists in another system, retrieve relevant prior reporting, preserve source references, identify contradictions and prepare a structured draft for analyst review.

The agent is not replacing the underlying tools.

It is operating across them.

But agentic AI also introduces a control problem.

The more an agent can do, the more important it becomes to define what it is allowed to do, when, why and under whose authority.

An agent with broad tool access and weak governance is not operational maturity. It is risk. It can use the wrong tool, trust the wrong source, merge the wrong entities, lose the evidence chain, summarize uncertainty away or create outputs that are difficult to defend after the fact.

In serious environments, agentic AI needs more than model capability.

It needs a fabric that connects tools while enforcing boundaries.

The Missing Layer Between Tools and Decisions

Most organizations do not have a single intelligence system. They have a landscape of systems.

Some are specialized OSINT platforms. Some are investigative tools. Some are internal data repositories. Some are knowledge bases, ticketing systems, reporting workflows, watch floors or classified and controlled environments. Many are already embedded in procurement, security, training and operational practice.

Replacing all of that is rarely realistic and often undesirable.

The more practical path is to add an operating layer that can connect existing platforms, tools, data sources, agents, evidence, cases and human approvals into one governed workflow.

That is what an Agentic Intelligence Fabric is designed to do.

An AIF is not just another AI application sitting beside existing systems. It is the connective layer that lets approved agents work across existing systems without surrendering control.

At minimum, the layer must do three things. It must connect approved external and internal systems so that governed agents can work across them—preserving case context, source references and entity resolution across tool boundaries. It must govern access through role-based controls, audit trails for both agent and human actions and intervention points tied to real operational risk. And it must deploy in the environments where the mission actually runs—cloud, sovereign cloud, on-premises, air-gapped or edge—without forcing the buyer to compromise on security posture or sovereignty.

The point is not to automate intelligence away from analysts.

The point is to let analysts operate faster while keeping judgment, accountability and mission authority where they belong.

Where the Work Runs Matters as Much as What Runs

Federal missions do not run in one environment.

The same workflow may need to operate in cloud today, in a sovereign or Government cloud tomorrow, in an on-premises environment for sensitive cases and air-gapped or at the edge for classified or forward-deployed work.

A fabric layer earns its name only if the operating model—cases, evidence, controls, agents—is preserved across all of them. Anything less forces the agency to maintain different intelligence operations in different boundaries, with different audit posture and different governance gaps.

Deployment is not an afterthought to the workflow. It is part of the workflow.

A Practical Example

Consider an analyst preparing a targeting assessment ahead of an inbound shipment. The case begins with one question: does this consignment, this consignor or this route warrant a closer look?

Answering that question pulls the analyst across five systems—an OSINT platform for entity discovery, an internal targeting database, a sanctions screening tool, a trade-data source and a case management application. The work gets done. But the evidence trail lives across five exports, the entity matches are made by hand and the assumptions behind each step are remembered, not recorded.

The goal should not be to replace any of those systems with a separate AI interface.

The better model is to let governed agents work across them.

A governed agent can retrieve the entity context, surface candidate matches across systems, preserve source references, highlight the sanctions hits that need escalation, identify contradictions and prepare a structured draft for the analyst’s review.

The analyst remains responsible for the assessment.

The system preserves what the agent did, which tool it used, which records it merged, what it ignored, what assumptions it made and where the human accepted, changed or rejected the output.

In this model, agentic AI does not become an uncontrolled layer of automation. It becomes a governed extension of the operational workflow.

That is the difference between using AI as a sidecar and operating AI as the connective tissue between intelligence tools.

Why This Matters for Government Adoption

Government AI adoption will not be decided only by model quality.

It will be decided by whether AI can work inside real operational constraints: existing systems, procurement realities, security controls, audit requirements, human review, deployment restrictions and the need to defend decisions under scrutiny.

Standalone AI tools can demonstrate impressive capability in isolation. But Government work rarely happens in isolation.

The work happens across systems, authorities, policies, teams and environments. The AI architecture has to respect that reality.

This is why the next generation of intelligence systems needs to unify four layers:

  • OSINT as a source layer.
  • Agentic AI as the workflow capability that can operate across tools.
  • Intelligence as the governed production of judgment, evidence and action.
  • Agentic Intelligence Fabric as the operating layer that connects existing systems, data, agents, cases and decisions.

When those layers are separated, organizations get more tools, more interfaces and more risk. When they are connected properly, AI can help existing investments become more useful without weakening control.

From AI Tools to Agentic Operations

The Government and enterprise market does not need AI for its own sake.

It needs AI that can operate responsibly inside mission workflows.

That means agents must be able to use approved tools, but not exceed their authority. They must accelerate analysis, but not hide uncertainty. They must produce outputs, but keep those outputs attached to evidence. They must work across platforms, but leave a trail that can be audited, challenged and reviewed.

This is the category WhoMeta is building toward with Arqent: an Agentic Intelligence Fabric for evidence-native, human-governed, sovereign intelligence operations.

The future of intelligence will not be defined by the organization that collects the most data or deploys the most AI features.

It will be defined by the organization that can connect its existing systems into accountable agentic workflows and still prove what it knows.

Ready to connect your intelligence systems without losing control? Explore how WhoMeta’s Agentic Intelligence Fabric brings your existing tools into one governed, auditable workflow.

Carahsoft Technology Corp. is The Trusted Government IT Solutions Provider, supporting Public Sector organizations across Federal, State and Local Government agencies and Education and Healthcare markets. As the Master Government Aggregator for our vendor partners, including WhoMeta, we deliver solutions for Geospatial, Cybersecurity, MultiCloud, DevSecOps, Artificial Intelligence, Customer Experience and Engagement, Open Source and more. Working with resellers, systems integrators and consultants, our sales and marketing teams provide industry leading IT products, services and training through hundreds of contract vehicles. Explore the Carahsoft Blog to learn more about the latest trends in Government technology markets and solutions, as well as Carahsoft’s ecosystem of partner thought-leaders.

Better Together: How Nutanix and AccuKnox Are Securing the Tactical Edge, and Beyond

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Modern defense operations demand more than connectivity; they demand resilience. As mission environments grow increasingly contested and disconnected, the ability to process intelligence, deploy applications and enforce security at the edge has become a strategic imperative. Nutanix and AccuKnox have built a compelling answer: a tightly integrated platform that pairs the Nutanix Kubernetes Platform (NKP) with AccuKnox’s Zero Trust security layer to deliver a complete, hardened stack, from the software factory to forward-deployed vessels to orbiting satellites. This hardened stack is also hardware agnostic and can be deployed on bare metal tactical servers, and up to IL6+ Govcloud instances. For the Department of War (DoW) architects, system integrators and space operations professionals, the critical question is no longer whether to modernize, but how to do it in environments where reach back is unreliable, swap space is constrained and the cost of failure is operational.

Kubernetes as the Foundation for Tactical Edge Operations

Delivering enterprise-grade infrastructure to physically remote, resource-constrained environments requires more than Kubernetes alone. Kubernetes represents roughly 30% of the solution; the remainder is a curated ecosystem of microservices, service mesh, observability tools and storage integrations that together form a complete operational platform. Without that full stack, organizations risk spending months assembling disparate open source components, only to find that their workloads are still unable to reach production. The NKP addresses this by delivering a pre-integrated, hardware-agnostic solution deployable on bare metal, in the cloud or fully air-gapped at the tactical edge. Whether the use case is a carrier strike group operating disconnected at sea, a forward-deployed Army unit running legacy virtual machines (VMs) alongside containers, or an Unmanned Aerial Vehicle (UAV) requiring a minimal footprint, NKP provides a single platform capable of self-healing, automated scaling and continuous operation, regardless of connectivity status.

AI Delivery and Agentic Capabilities in Disconnected Environments

In contested environments, artificial intelligence (AI) cannot depend on cloud inference. It must run locally, reliably and securely. Nutanix Enterprise AI layers on top of NKP to provide a managed platform for running Large Language Models (LLMs), Retrieval-Augmented Generation (RAG) systems and agentic AI applications with full GPU support, all within disconnected environments. At a recent TechNet San Diego demonstration, RAG AI was used to surface answers from complex naval system maintenance manuals in seconds, a direct application for shipboard readiness operations. Agentic platforms are now deployed with Army units and fielding requests from naval activities, running fully on NKP hardware aboard vessels and mobile command centers without internet dependency. AI models trained at core installations are pushed to forward-deployed assets, where they run locally and queue updates for synchronization upon reconnection, preserving operational continuity without compromising security or model integrity.

Zero Trust Security Woven Into Every Layer

Security at the tactical edge requires continuous policy enforcement at every layer of the software stack, from code commit to container runtime in the field. AccuKnox integrates below the application layer to enforce least-permissive security policies at the kernel level using eBPF-based telemetry. Its Discovery Engine analyzes applications both statically and dynamically, automatically generating security manifests that accompany each application throughout its full deployment lifecycle. These policies define exactly where an application can communicate, what data it can access and how it may interact with adjacent system components—creating enforcement that is architectural rather than reactive. For acquisition officials and Authorizing Officials (AOs) managing distributed mission systems, the platform also automates the generation of compliance evidence covering Security Technical Implementation Guides (STIGs), Common Vulnerabilities and Exposures (CVEs) and relevant security frameworks, compressing what has historically been a months-long manual process into continuous, audit-ready assurance.

Extending the Stack to Orbit: DevSpaceOps

The Nutanix and AccuKnox partnership extends beyond the terrestrial edge to software-defined satellites and orbital platforms. Modern satellite platforms support containerized payloads, multi-tenancy and high-tempo software updates, and they carry significant security exposure. A representative sample of open source software deployed across current satellite initiatives contains more than 60 million lines of code and upwards of 20,000 CVEs. Unlike ground-based nodes, satellites cannot rely on real-time downlink for security decisions; they require local policy enforcement, runtime monitoring and eventually consistent posture reporting to the ground. The concept of DevSpaceOps, modeled on DevSecOps but adapted to the constraints of orbit, addresses how development teams can certify, deploy and manage satellite software with verifiable confidence, leveraging lightweight versions of KubeArmor, automated SPARTA TTP mapping and orbital security dashboards that give Space Operations Center (SOC) teams constellation-wide visibility into STIG compliance, CVE exposure and runtime violations.

One Stack, Every Domain

NKP delivers the hardware-agnostic, cloud-native platform that enables continuous operations across disconnected, multi-domain environments, from carrier strike groups to Army forward units to orbital constellations. AccuKnox ensures that everything running on that platform is secured, monitored and compliant at every layer of the stack. For defense organizations looking to reduce decision latency, accelerate the Authorization to Operate (ATO) lifecycle and ensure security travels with every workload, this joint solution offers a proven, fielded path forward.

To explore these capabilities in greater depth, including live demonstrations of sensor-to-shooter workflows, orbital security posture management and agentic AI in disconnected environments, watch the full webinar presented by Nutanix and Carahsoft.

Carahsoft Technology Corp. is The Trusted Government IT Solutions Provider, supporting Public Sector organizations across Federal, State and Local Government agencies and Education and Healthcare markets. As the Master Government Aggregator for our vendor partners, including Nutanix, we deliver solutions for Geospatial, Cybersecurity, MultiCloud, DevSecOps, Artificial Intelligence, Customer Experience and Engagement, Open Source and more. Working with resellers, systems integrators and consultants, our sales and marketing teams provide industry leading IT products, services and training through hundreds of contract vehicles. Explore the Carahsoft Blog to learn more about the latest trends in Government technology markets and solutions, as well as Carahsoft’s ecosystem of partner thought-leaders.

The Top 5 Insights for Government from GSMCON 2026

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As expectations evolve, Government agencies are redefining how they communicate with the public online. The Government Social Media Conference 2026 (GSMCON) highlighted how Public Sector organizations are adapting their approaches to constituent engagement. The conference gathered over 1,000 Government communicators, senior leaders and social media professionals from across the country in New Orleans, LA to learn strategies on how to build trust, deliver meaningful experiences and demonstrate value across the organization through social channels. 

This year, speakers highlighted how Government agencies can better serve their communities while navigating resources, evolving leadership priorities and platform changes from multilingual communication strategies to stronger internal alignment. 

Here are the top takeaways from the conference. 

Human-Centered Storytelling Builds Trust and Engagement 

Across all sessions, the importance of authenticity emerged as a consistent theme. Constituents are more likely to engage with content that reflects real people and real experiences rather than overly polished messaging. 

Leading agencies are prioritizing: 

  • Frontline individuals who represent the day-to-day work of Government 
  • Simple, approachable content that removes barriers to participation 
  • Internal recognition to encourage staff involvement and ownership 

Whether highlighting public safety personnel, infrastructure teams or community outreach efforts, these human moments strengthen credibility and foster meaningful connections. 

For Public Sector organizations, storytelling is a strategic tool for reinforcing transparency, trust and genuine relationships with the community. 

Effective Content Must Capture Attention Immediately 

Today’s digital environment requires Government communicators to deliver significant impact quickly. Agencies have just a few seconds to capture attention and communicate mission-critical messages. 

High-performing content typically: 

  • Begins with the most compelling moment or insight 
  • Uses clear, concise visual and text elements 
  • Creates curiosity that encourages continued engagement 

Short-form video remains one of the most effective formats for reaching constituents. Successful execution depends on pacing, clarity and intentional storytelling that aligns with how audiences consume information. 

Agencies should focus on designing content that is both efficient and engaging while maintaining accuracy and professionalism. 

A Structured Campaign Approach Improves Results 

As Government social media programs develop, a more intentional and consistent campaign approach is becoming essential for sustaining effective communication over time. Zack Seipert, Marketing and Communications Specialist at the Central Utah Water Conservancy District, highlighted the value of the Plan-Build-Run (PBR) framework as a reliable, repeatable model for planning and executing these efforts: 

  • Plan: Define clear objectives, identify your audience, establish Key Performance Indicators (KPIs) and select the right channels based on where constituents engage 
  • Build: Develop compelling creative, implement tracking tools and refine audience targeting for accuracy and relevance 
  • Run: Monitor performance, optimize in real time and apply insights to strengthen future campaigns 

This structured approach helps Public Sector teams create more data-driven campaigns aligned with organizational priorities while delivering measurable results. 

With social media management solutions from our partners at Hootsuite, Public Sector social media teams can maximize limited resources by streamlining workflows and gaining clearer visibility into performance across channels. 

Internal Alignment Strengthens External Impact  

When a Public Sector agency is imparting the same message internally as it is to the public, the impact delivered is much stronger. In the session “This is How We Do It: How to Turn Employees into the Stars of Our Social Story”, Charles Newman of the City of Columbus Department of Public Service emphasized that strong internal alignment starts with bringing employees into the communication process, helping connect day-to-day work to broader messaging goals. 

In “Managing Social Media Response Through Crisis and High-Pressure Events”, Kate Stegall of the Louisiana State Police highlighted the importance of clear internal coordination during high-pressure situations to ensure messaging remains consistent across teams and aligned with agency priorities. 

Effective strategies include: 

  • Delivering regular reports that clearly link performance to agency priorities  
  • Using clear language that supports informed decision-making  
  • Providing actionable insights and recommendations alongside metrics  
  • Building relationships through cross-department collaboration 

Short-Form Video Plays a Key Role in Government Communication  

Multiple sessions emphasized that short-form video has become a core channel for effective Government communication and audience reach. In “60-Second Stories: Trim the Fat & Hold Attention”, Daniel Robinson of the Wisconsin Department of Natural Resources (DNR) highlighted how concise storytelling is essential for maintaining viewer attention in fast-moving social feeds, especially when communicating public updates and educational content. 

Similarly, in “Reels for Social Recruitment”, Wendy Aguilar of the Sacramento Fire Department demonstrated how short-form video can be used strategically for workforce recruitment. Aguilar showed that authentic, behind-the-scenes content often outperforms highly produced messaging when building trust and interest. 

In “Strategy, Workflow & Team Culture for Consistent Reel Creation,” Meredith Haynes and Tony Adamo of the City of McKinney, TX, reinforced that success with short-form video depends less on one-off content and more on building repeatable workflows and cross-team collaboration. 

Across these breakouts, speakers consistently pointed to short-form video as a high-impact tool for storytelling, recruitment and public information, especially when supported by clear strategy, consistent execution and content designed for how audiences consume information today. 

GSMCON 2026 highlighted a continued evolution in how Government and Public Sector organizations approach social media. The focus is shifting toward intentional, strategic communication that prioritizes trust, clarity and measurable impact. 

By applying these best practices, Government organizations can build a stronger social media presence and foster stronger, more meaningful relationships with the constituents they serve. 

To further explore the tools, trends and strategies shaping digital engagement in Government, visit Carahsoft’s Customer Experience and Engagement Solutions page and see our portfolio of Government Social Media solutions. 

Contact the Hootsuite Team at Hootsuite@Carahsoft.com to learn more about how Carahsoft’s Government social media management tools can support your organization’s digital strategy. 

OSINT and Executive Protection: A Critical Capability for Modern Security Operations

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As threats to executives, public officials and high-profile individuals continue to evolve, Executive Protection (EP) programs are increasingly reliant on Open Source Intelligence (OSINT) to anticipate, detect and mitigate risk. From online harassment and doxxing to geopolitical instability and lone-actor threats, the modern threat landscape is shaped—and often signaled—by publicly available information.

OSINT has emerged as a foundational capability for EP teams, enabling proactive, intelligence-led security decisions that are faster, more adaptive and more comprehensive than traditional approaches alone.

Why OSINT Matters for Executive Protection

EP is no longer limited to physical security and close-in protection. Today’s threats often originate in the digital domain before manifesting in the physical world. OSINT allows EP teams to monitor and assess:

  • Online threats, grievances and fixation behaviors
  • Social media activity and emerging narratives targeting executives
  • Event-driven risks tied to protests, activism or geopolitical developments
  • Travel-related threats, including local crime trends and unrest
  • Digital exposure, doxxing risks and personal data leakage

By analyzing these open-source signals, EP teams gain early warning indicators that can inform protective posture, travel planning and resource allocation.

Supporting Proactive, Intelligence-Led Protection

OSINT enables a shift from reactive protection to proactive threat management. Rather than responding only after an incident or credible threat emerges, EP teams can continuously assess risk and identify patterns that indicate escalation.

Key benefits include:

  • Threat Identification & Prioritization: Distinguishing between credible threats and background noise
  • Advance Planning: Enhancing route selection, venue security and travel assessments
  • Protective Intelligence Integration: Feeding OSINT into broader intelligence and security workflows
  • Scalability: Supporting protection for multiple executives across global environments

This intelligence-driven approach is especially critical as executives maintain a growing digital presence and operate in increasingly complex security environments.

Ethical, Legal and Privacy Considerations

As with any intelligence activity, OSINT for EP must be conducted responsibly. EP programs must balance threat awareness with privacy, civil liberties and legal compliance, ensuring that collection and analysis focus on publicly available, lawful sources.

Clear governance-defined use cases and analyst training are essential to maintaining ethical OSINT practices while still delivering actionable security insights.

The Growing Role of OSINT in Executive Protection Programs

Across Government, Private Sector and critical infrastructure organizations, OSINT is becoming a standard component of mature EP programs. Whether supporting senior Government officials, corporate leadership or high-visibility executives, OSINT enhances situational awareness and strengthens protective outcomes.

As digital information continues to expand and threats grow more asymmetric, OSINT will remain a vital tool—helping EP teams stay ahead of risk, adapt to change and protect their principals in an increasingly interconnected world.

Ready to Strengthen Your Executive Protection Program with OSINT?

As The Trusted Government IT Solutions Provider™, Carahsoft helps Government agencies, defense organizations and critical infrastructure teams access the OSINT tools and expertise needed to build proactive, intelligence-led protection programs.

From Visibility to Zero Trust: Enabling Federal Agency Cybersecurity at Scale

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As Federal agencies accelerate their Zero Trust journeys in response to executive mandates and evolving compliance requirements, cybersecurity leaders face a fundamental challenge: they cannot protect what they cannot see. Zero Trust depends on complete, reliable visibility across modern cloud environments and legacy Operational Technology (OT) systems. Without that packet-level visibility, Zero Trust cannot be effectively enforced.

Closing the Network Visibility Gap

Most agencies rely on Switched Port Analyzer (SPAN) ports to correspond network traffic to security tools, but this approach can leave security sensors with incomplete data, especially in legacy OT environments. Garland Technology’s network Traffic Access Points (TAPs) address this directly. Passive hardware TAPs sit in line between network devices, duplicating traffic for monitoring tools. TAPs carry no Media Access Control (MAC) or Internet Protocol (IP) address, making them invisible to adversaries and work across virtually any vendor ecosystem without creating new visibility constraints.

For environments that need strict one-way data flow, hardware data diodes add another layer of protection. They enforce unidirectional traffic at the circuit level, replacing or working alongside existing SPAN or mirror ports without requiring a full infrastructure overhaul. With National Cross Domain Strategy & Management Office (NCD SMO) certification in its final stages, hardware-based data diodes offer Federal agencies a compliance-ready path to enforce one-way traffic.

Distributing Visibility Intelligently with Packet Brokers

Complete network visibility across a Federal environment involves more than a single TAP or sensor. Traffic moves across multiple links, environments and speeds, and it must be routed to the right monitoring and security tools. Network packet brokers from Garland Technology help agencies receive data from multiple sources and distribute them.

Packet brokers make large-scale visibility manageable through capabilities including:

  • Aggregating traffic from multiple feeds
  • Filtering relevant data streams
  • Load balancing across tool sets
  • Deduplicating redundant packets
  • Slicing and timestamping packets for precision analysis
  • Tunneling traffic across segmented environments

These features reduce overload and improve monitoring performance. In practice, packet brokers can feed targeted traffic simultaneously into Security Information and Event Management (SIEM) platforms, intrusion detection systems, network performance monitors and other sensors.

In OT environments structured around the Purdue model, packet brokers typically sit at the operations systems level, aggregating traffic from TAPs and SPAN ports at lower network layers and routing it upward, through data diodes where required, into the tool sets where security teams can act.

Converging IT and OT for Zero Trust Compliance

Zero Trust is accelerating IT and OT convergence. The National Institute of Standards and Technology (NIST) Zero Trust Architecture (ZTA) framework, along with agency-specific guidance, demands continuous verification of users, devices and applications across the entire network. This is especially challenging because many OT devices in Government networks are decades old and cannot support software updates or inline security tooling without disrupting critical operations.

A practical approach is to leave those systems in place while using network TAPs to pull traffic from legacy OT devices without interrupting operations. That allows security platforms to analyze activity, apply threat intelligence and enforce policy at the network level without touching the devices themselves.

This visibility also enables virtual patching. When a firewall platform can identify an OT device’s version and known vulnerabilities, it can block traffic patterns associated with known threats at the network level without interrupting critical operations. Security teams can also tailor the virtual patching profile to the devices in their environment, resulting in a consolidated, visual asset inventory that maps how OT devices are organized across the network.

A Unified Security Fabric for Continuous Assessment

Zero Trust depends on multiple capabilities working together, including identity, access permissions, segmentation, policy enforcement and continuous assessment. At Federal scale, those functions are most effective when they are integrated rather than spread across disconnected tools. That is where Fortinet Federal brings its security fabric alongside Garland Technology’s visibility infrastructure.

A unified next-generation firewall platform, Fortinet Federal’s FortiGate platform combines routing, Software-Defined Wide Area Network (SD-WAN), segmentation and threat detection into a single operating system, FortiOS, reducing blind spots. FortiGate also extends visibility across switches and wireless access points, enabling security teams to enforce policy more consistently across users, devices and applications.

This consolidated visibility supports Zero Trust Network Access (ZTNA) by applying consistent policy and authentication standards across remote and on-premises users. Threat intelligence further strengthens this model by continuously updating and distributing protections across the environment. FortiGuard Labs sustains this visibility and enforcement through a global threat intelligence network that continuously feeds into Network Operations Center (NOC), Security Operations Center (SOC), Security Orchestration, Automation and Response (SOAR) and SIEM platforms, enabling teams to investigate threats and respond in a coordinated manner.

A Trusted, Compliant and Isolated Security Supply Chain

For Federal agencies, Zero Trust readiness also depends on the integrity of the security supply chain. Security tools must come from vendors with the structure, compliance posture and operational safeguards required for Federal deployment.

Fortinet Federal delivers industry-leading cybersecurity and secure networking capabilities to the U.S. Government through a dedicated, independently operated and federally aligned organization. Its purpose is to serve as a trusted mission partner—providing validated, secure supply chain assurance as well as high-performance and cost-efficient technology.

On the visibility side, Garland Technology’s American-manufactured hardware purpose-built for network TAPs, packet brokers, inline bypass and data diodes helps agencies scale to full-time continuous monitoring architectures without requiring major platform changes or vendor transitions.

Building Toward a More Secure Future

The path to Zero Trust in Federal environments requires the right partners working together. Garland Technology provides purpose-built visibility infrastructure that reliably delivers packet data across IT and OT environments without disrupting legacy systems or creating new points of failure. Fortinet Federal’s federally vetted, supply-chain-isolated security platform turns that visibility into enforceable policy through threat intelligence, network segmentation, ZTNA and continuous assessment. Together, Garland Technology and Fortinet Federal give agencies the integrated foundation needed to implement Zero Trust at scale, protect critical infrastructure and stay ahead of evolving threats.

To learn more about achieving packet visibility and Zero Trust at scale, watch Fortinet Federal and Garland Technology’s webinar, “From Visibility to Zero Trust: Enabling Federal Agency Cybersecurity at Scale.”

Carahsoft Technology Corp. is The Trusted Government IT Solutions Provider, supporting Public Sector organizations across Federal, State and Local Government agencies and Education and Healthcare markets. As the Master Government Aggregator for our vendor partners, including Fortinet and Garland Technology, we deliver solutions for Geospatial, Cybersecurity, MultiCloud, DevSecOps, Artificial Intelligence, Customer Experience and Engagement, Open Source and more. Working with resellers, systems integrators and consultants, our sales and marketing teams provide industry leading IT products, services and training through hundreds of contract vehicles. Explore the Carahsoft Blog to learn more about the latest trends in Government technology markets and solutions, as well as Carahsoft’s ecosystem of partner thought-leaders.

From Data Islands to Defensible Intelligence: Modernizing Public Sector Transportation Infrastructure

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Across the United States, transportation agencies are operating in a moment of historic opportunity, and equally significant pressure. With more than $200 billion in capital funds required to be obligated before the 2026 deadline, agencies are tasked not only with delivering projects at scale but also with doing so with a level of transparency, accountability and precision that withstands public and regulatory scrutiny.

Yet while funding has accelerated, many of the systems used to manage transportation programs have not kept pace with the complexity of the initiatives themselves. The result is a growing disconnect between project activity in the field and decision-making at the program level.

Closing that gap requires more than new tools. It requires a shift from fragmented data to defensible intelligence.

The New Reality: High Stakes, Limited Visibility

Transportation leaders today are navigating a complex operating environment shaped by three converging pressures:

  • Federal funding deadlines and obligation requirements that leave little room for delay
  • Technical complexity, where construction teams must not only lead traditional construction effort, but also the tech associated with those projects
  • Increased audit and compliance scrutiny, requiring agencies to demonstrate clear, traceable use of public funds

Individually, these challenges are manageable. Together, they expose two systemic issues: limited visibility across the capital program lifecycle and unnecessary complexity.

Without a unified view of project information, cost, field activity and performance, agencies are

often forced to rely on lagging indicators, manual reporting and disconnected systems, making it difficult to act with confidence.

The Persistence of Data Silos

Despite advances in digital tools, many Public Sector transportation programs still operate across fragmented environments:

  • Field data is captured inconsistently or stored locally
  • Financial tracking exists separately from project execution
  • Compliance documentation is often assembled in an ad hoc manner
  • Key intelligence gathering during the build phase is often not handed off to operational teams

This creates what can be described as data islands, pockets of information that are not easily connected, validated, or scaled across the portfolio.

The implications are significant:

  • Delayed decision-making due to incomplete or outdated information
  • Inconsistent reporting across projects and stakeholders
  • Limited ability to identify risks early
  • Increased exposure during audits and compliance reviews

In this environment, even well-managed projects can appear fragmented at the program level, making it difficult to demonstrate accountability with confidence.

A Shift Toward Defensible Intelligence

To address these challenges, transportation agencies are beginning to rethink how data is structured, governed and used across the lifecycle of capital programs.

This shift can be understood as a move from data collection to defensible intelligence.

A defensible approach ensures that:

  • Data is captured consistently from the field
  • Information is standardized across projects
  • Data is not only collected, but analyzed to proactively mitigate risk
  • Documentation is audit-ready at every stage, not just at project closeout

At its core, this is about establishing a system of record that allows teams to shift from looking at projects in the rearview window after the fact, to having clear project visibility through the entire asset lifecycle.

Building the Foundation: Governance & Clarity

The first step in this transformation is strengthening governance.

Adoption as a Prerequisite for Insight

Even the most advanced systems fall short if they are not consistently used. In transportation programs, where multiple stakeholders, contractors and teams are involved, adoption is critical to ensuring that data is both accurate and timely.

An adoption-first approach helps ensure:

  • Consistent data capture across the field
  • Standardized workflows across projects
  • Greater confidence in reporting and analytics

Establishing Secure, Traceable Oversight

Given the scale of public investment, transportation agencies must demonstrate fiduciary responsibility at every stage of a project.

This requires:

  • A clear audit trail of decisions, approvals and changes
  • Centralized access to financial and project data
  • Alignment with Federal security and compliance standards

Advancing the Model: Connected Control

With a strong governance foundation in place, agencies can begin to unlock the next level of capability: connected control over project delivery.

Improving Responsiveness Through Visibility

Access to timely, integrated data allows program leaders to:

  • Identify schedule variances as they emerge
  • Understand cost impacts in context
  • Drive corrective actions, whether on site, at the office or on the Hill
  • Use historical data to make informed forecasting decisions today

This represents a shift from retrospective reporting to proactive program management.

Bridging Construction and Operations

One of the most persistent challenges in transportation infrastructure is the transition from construction to operational readiness.

When systems are disconnected:

  • Critical asset data may be lost or duplicated
  • Operations teams lack visibility into construction decisions
  • Time to project delivery is delayed

By maintaining continuity of information across the lifecycle, agencies can:

  • Enable smoother transitions into active service
  • Reduce rework and data re-entry
  • Support long-term asset management from day one

Looking Ahead: A More Connected Future for Transportation Programs

The modernization of transportation infrastructure is not solely a matter of funding or scale. It is increasingly a matter of data maturity.

Agencies that continue to rely on fragmented systems may find it difficult to keep pace with evolving requirements around compliance, reporting and delivery speed.

Those that invest in connected, well-governed data environments will be better positioned to:

  • Navigate funding deadlines with confidence
  • Respond to issues in real time
  • Demonstrate accountability across the full lifecycle of their programs

As transportation programs grow in complexity and visibility, the need for clarity, consistency and control becomes more critical.

Moving from data islands to defensible intelligence is not just a technology shift; it is an operational one. It reflects a broader evolution in how agencies plan, deliver and oversee infrastructure in a high-stakes environment.

By strengthening governance and enabling connected control, Public Sector transportation leaders can build not only infrastructure, but also predictability, transparency, accountability and efficiency.

Ready to improve visibility and control across your transportation projects? Connect with us.

Hybrid AI That Moves with the Mission

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Federal missions operate across complex, distributed environments, from secure data centers to cloud enclaves and tactical platforms in disconnected conditions. Artificial intelligence (AI) must now match this operational agility.

Hybrid AI integrates cloud, on-premises and edge compute, enabling intelligence where and when it is needed. Whether inside a SCIF, within a FedRAMP-moderate enclave or in contested environments, hybrid architectures ensure trusted intelligence is continuously available to support mission outcomes.

Why Hybrid AI is Mission-Critical for Federal Agencies

As mission data becomes more dynamic and dispersed, centralized compute models alone cannot meet operational demands. Agencies must process, generate and act on information securely, whether in the field, across partner networks or in highly regulated environments.

Hybrid AI brings compute to the data, respecting governance and sovereignty while maintaining flexibility. AI capabilities must function reliably in environments where connectivity is degraded or unavailable, and where data cannot move freely due to classification or jurisdictional constraints.

This ensures real-time inference and decision support at the point of need while safeguarding CUI, PII and FOUO data under FISMA, EO 14110 and Zero Trust principles. AI-powered insights remain accessible even when the network does not.

The Technology Foundations of Mission-Ready Hybrid AI

Data sovereignty is essential
Agencies must process, train and infer within regulatory boundaries, maintaining full control of sensitive data across its lifecycle, from edge ISR streams to classified model development. Containerized and optimized AI software must run flexibly across accelerated environments, from enterprise cloud to air-gapped data centers.

Infrastructure must scale seamlessly
Hybrid environments enable compute to move across core, cloud and field deployments, keeping AI aligned with changing mission needs.

Accelerated computing powers mission AI
Advanced generative and deep learning models demand high-efficiency, accelerated compute platforms. Hybrid AI leverages this capability to deliver high-throughput, low-latency insights not only in data centers but also at the tactical edge—essential for mission-aligned generative AI and emerging agentic applications.

Interoperability drives flexibility
Containerized AI microservices and API-driven architectures ensure seamless integration with mission platforms like health and geospatial, while enabling secure, policy-compliant operations across hybrid environments. Architectures should also support flexible integration of retrieval pipelines and evolving data governance models, ensuring mission intelligence is grounded in trusted, up-to-date sources.

Real-World Applications: Hybrid AI in Action

Agencies are applying hybrid AI today to extend mission capabilities beyond what centralized architectures allow.

In public health, sovereign data platforms combined with edge analytics support real-time outbreak modeling and informed containment planning. Disaster response teams ingest and analyze aerial imagery and IoT data locally, providing actionable insights even when disconnected from central networks.

Generative AI is transforming document-centric workflows. It accelerates the summarization of complex reports and regulatory analysis while maintaining strict control over sensitive content.

Sovereign AI innovation is advancing rapidly. National AI clusters allow agencies to train and refine models domestically, ensuring compliance with governance mandates while enhancing operational independence. Many of these efforts begin under SBIR, OTA or BPA contracts and evolve into modular architectures that scale with mission requirements.

Key Considerations for Building Hybrid AI

Hybrid AI success requires intentional architecture, policy fluency and alignment with mission realities.

Architectures must enable agility, supporting rapid adaptation to evolving mission needs, data sources and model advancements. Flexibility ensures AI remains relevant as both operational risks and opportunities evolve. Hybrid environments should also be designed to support emerging model types, including multi-modal, agentic and retrieval-augmented AI, and to accommodate evolving policy mandates.

Interoperability is essential. Open, standards-based pipelines and containerized services enable integration with evolving toolchains, partner ecosystems and commercial innovation while maintaining governance.

Federal leaders are using hybrid architectures to operationalize responsible AI principles outlined in EO 14110. Early alignment with procurement vehicles—OTAs, GWACs and BPAs—ensures scalable, policy-ready architectures. High-impact use cases, such as edge-deployed generative AI assistants and sovereign model training pipelines, continue to demonstrate the value of this approach.

Next Steps for Federal AI Leaders

Hybrid AI represents an inflection point for Federal missions. Leaders who invest in scalable, policy-aligned AI infrastructure today will be positioned to harness tomorrow’s AI innovations at mission speed.

By supporting secure, accelerated AI capabilities across edge, cloud and on-premises environments, hybrid architectures help agencies maintain operational advantage in any scenario. The focus is not just on deploying AI models, but on building adaptive infrastructure that delivers intelligence wherever the mission requires it.

Hybrid AI architectures also lay the operational foundation for the emerging era of AI Factories—systems that continuously generate, adapt and deploy intelligence at scale, across mission environments.

Federal leaders who establish this foundation today will ensure that AI serves the mission with the trust, agility and resilience it demands—and with the flexibility to evolve alongside the accelerating pace of innovation.

Deploy AI in Days, Not Months: The Infrastructure Imperative for Mission-Aligned Models

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What makes one agency able to move artificial intelligence (AI) into mission production in days, while another still navigates the same barriers months or even years later? The answer isn’t technical talent or budget alone. It’s whether infrastructure is intentionally built to support velocity, trust and scale.

As Federal leaders sharpen their focus on operational AI, speed is becoming the key differentiator. Not speed for its own sake, but speed that is purposeful, compliant and aligned with outcomes the public and the mission demand. Moving AI from pilot to production quickly now defines AI leadership in Government.

Rethinking AI Readiness for Federal Missions

Simply demonstrating isolated AI successes is no longer sufficient. Federal agencies are now expected to embed AI into core workflows, drive outcomes and uphold public trust. CAIOs are shifting focus from pilots to impact. That shift requires more than technical oversight; it demands leadership that can drive operational change and enable the workforce to prioritize higher-value work.

Scaling mission-aligned AI requires rethinking old norms. Agencies embracing this shift are achieving faster deployments, greater agility and increased transparency, while others risk getting stuck in pilot mode without the proper foundation.

Building the Foundation for Mission-Aligned AI

Reliable acceleration comes from an intentional foundation, not shortcuts. Agencies moving AI from concept to capability consistently align strategy, data, infrastructure, teams and governance from the outset.

Mission Strategy First

Successful AI efforts prioritize mission impact over technical novelty. Clear goals ensure leadership, infrastructure and resources move in sync toward measurable outcomes.

Data That Moves at Mission Speed

AI needs fast, secure access to trusted structured and unstructured data. Retrieval-based architectures anchored in vetted sources support both performance and privacy.

Scalable, AI-Optimized Infrastructure

Traditional IT can’t handle AI’s demands. Agencies moving at mission speed rely on infrastructure optimized for accelerated computing and seamless operations across domains.

Integrated, Agile Teams

Scaling AI takes more than data science. Cross-disciplinary teams aligned on outcomes and able to deliver in agile cycles are key.

Compliance as an Enabler

Built-in transparency and risk management turn compliance into an asset. Agencies that embed governance early shorten ATO timelines and boost public trust.

A Roadmap for Responsible Acceleration

Moving fast without structure is risky. Moving fast with structure enables repeatable, responsible AI delivery. A maturity roadmap helps agencies balance acceleration with alignment to Federal guidance.

1.    Baseline Assessment

Clear visibility into current data maturity, infrastructure readiness, governance posture and workforce capabilities helps agencies prioritize investments. Addressing common gaps, like fragmented data pipelines and siloed teams, systematically gives AI initiatives a foundation that scales without risk.

2.    Mission-Driven Objectives

Successful AI leaders define what “mission success” looks like in concrete terms. This discipline prevents overbuilding, keeps efforts tied to operational outcomes and builds clear value stories to sustain leadership support.

3.    Phased Testing Environments

Test beds and controlled environments provide space to validate AI approaches before full production. These environments foster safe iteration, surface governance needs early and create reusable patterns that accelerate future deployments.

4.    Continuous Model Feedback

AI systems must adapt over time, not just at launch. Embedding continuous monitoring, performance tuning and user-driven feedback ensures models remain mission-relevant and trustworthy as operational contexts evolve.

From Use Case to Outcome: What Speed Requires

Agencies moving AI into production quickly focus on the right use cases. Logistics optimization, document analysis and fraud detection are examples of areas where AI at mission speed delivers immediate benefit.

Another key enabler is avoiding unnecessary reinvention. Pre-trained, enterprise-grade models tailored to agency needs dramatically reduce development time.

Modern platforms that support containerized deployment and orchestration of AI microservices across cloud and on-prem environments accelerate this process. Agencies gain flexibility to optimize cost, performance and control based on mission needs. Modular, adaptable architectures also help avoid lock-in and support evolving policy and security requirements.

Security and compliance must be integrated from day one. Systems aligned with FedRAMP, FISMA and Executive Order 14110 requirements to avoid rework that can stall even well-intentioned efforts late in the process.

The Capabilities That Make Rapid AI Possible

To deploy AI at mission speed, infrastructure must deliver scalability, explainability, risk management and collaboration-readiness.

Systems must handle expanding data sources, dynamic mission demands and increased user load without degradation. Models must produce outputs that analysts, operators and oversight bodies can trust and interpret.

Ethical risk management must be proactive, not reactive. Bias checks, audit trails and transparency must be built in from training through ongoing monitoring. Collaboration across agencies and partners must be seamless to maximize impact and minimize duplication of effort.

These capabilities must be grounded in alignment with Federal frameworks such as the AI Risk Management Framework and GSA’s AI guidance. Infrastructure that is “policy-ready” supports faster delivery and greater trust in outcomes.

Leading with Principles That Scale

For Federal AI leaders, the challenge is scaling AI to deliver real mission outcomes while maintaining public trust. Success requires investing in scalable, policy-aligned infrastructure and fostering a culture where speed and governance go hand in hand.

Sustainable, enterprise-wide impact demands leadership that connects vision with execution. The CAIO must drive cross-agency collaboration, operational change and continuous feedback to keep AI responsive to evolving mission needs.

Fast, Mission-Driven AI is Achievable—If You Build for It

Deploying AI in days—not months—is possible when infrastructure, strategy and culture align to support it. Agencies embracing this imperative are setting the pace for responsible, impactful AI in Government.

When AI systems are grounded in mission need, accelerated by the proper infrastructure and governed with intention, they enable something bigger: a Government workforce empowered to focus less on routine tasks and more on the high-impact decisions and public outcomes that matter most.

For Federal AI leaders, the opportunity is now: to move from pilot to production with velocity, governance and trust—and to deliver mission outcomes at a speed that matches the urgency of the moment.

Evolving AI Infrastructure Without Disrupting Government Operations

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You’ve launched artificial intelligence (AI) pilots and proven their initial value. Now comes the harder question: how do you scale that progress without disrupting core operations or exceeding current system constraints? For Government AI leaders, the goal isn’t just AI adoption—it’s enabling AI evolution through resilient infrastructure that aligns with mission continuity and operational control.

Many agencies face the same tension. They need modernized systems to meet new expectations from Executive Order 14110 and similar mandates, without risking service downtime or fragmenting mission workflows. This requires moving beyond piecemeal integration and toward a scalable, secure and interoperable AI deployment architecture that fits within existing environments.

From Integration to Evolution

Agencies often begin with targeted AI pilots or API-based tools. But real progress means transitioning to infrastructure designed to support high-reliability, mission-aligned AI deployments at scale. AI stacks built for performance, observability and governance, not just experimentation, will allow agencies to achieve this progress.

What does this look like in practice? It means infrastructure that supports model training, inference, lifecycle management and secure data movement are all underpinned by capabilities like versioning, rollback, audit logging and support for MLOps practices. These capabilities help ensure operational readiness as agencies move from pilot to production.

This evolution doesn’t require scrapping functional systems. By using modular designs and accelerated computing, agencies can layer AI capabilities onto their existing IT backbones. Compatibility with containerized environments and orchestration tools enables phased implementation, which reduces duplication, minimizes disruption and supports operational continuity.

What to Look for in a Modern AI Infrastructure

Adaptable and Modular Design
Agencies benefit from modular infrastructures, with reusable building blocks such as containerized microservices, pre-trained models and policy-controlled pipelines. Modern designs accelerate deployment while maintaining alignment with internal security and governance frameworks’ practices.

Deployment Flexibility
Support for on-premises, hybrid and Government-authorized cloud environments ensures that sensitive workloads can be managed without vendor lock-in. AI capabilities should be deployable across systems with varying levels of connectivity, compliance and mission assurance requirements.

Embedded Security and Compliance
Encryption, runtime integrity checks, secure boot and audit trails with access controls must be native, not bolted on later. Compliance-readiness for frameworks like FedRAMP, NIST and digital sovereignty requirements is critical in regulated environments. These controls support zero-trust principles and enable responsible AI deployment across sensitive Government workloads.

Performance and Scale
AI workloads, from large-scale model training to low-latency inference, require optimized systems. Optimizations may include high-throughput, accelerated computing and GPU-based operations. Support for retrieval-augmented generation (RAG) can further extend GenAI capabilities by safely leveraging agency-specific grounded, context-aware outputs aligned with mission requirements.

Modernization Without Disruption

A step-by-step modernization plan helps agencies validate functionality, performance and alignment before scaling enterprise-wide. AI infrastructure should offer version control, rollback capabilities and seamless patching to reduce service risks in live environments.

Integration with legacy systems is equally vital. AI systems must coexist with core IT functions, avoiding the need for redundant tooling or excessive abstraction layers. Using standardized APIs and interoperable components helps limit rewrites and eases workforce adoption.

Cost containment and alignment

Managing cost also plays a central role. Modular infrastructure helps reduce unnecessary spend, avoids one-off duplications across programs and supports coordinated cross-agency deployments, especially as centralized AI procurement strategies evolve.

Building a Future-Ready AI Strategy

Lifecycle Alignment
AI Infrastructure should span the entire lifecycle, from data ingestion and labeling to training, inference, deployment, monitoring and governance. Gaps between these phases introduce risk and slow down scaling.

Support for What Already Works
Agencies shouldn’t be forced to abandon functioning legacy systems. Look for infrastructure that layers AI capabilities onto existing environments, enabling incremental expansion without disrupting current operations or compromising system security.

Security and Trust at the Core
From day one, AI infrastructure must enforce robust controls, auditability and observability to satisfy both internal oversight and external regulatory demands. These safeguards are essential for enabling secure, compliant and trustworthy AI operations across the entire model lifecycle.

Scalable by Design
From pilots to full-scale rollouts, AI infrastructure should scale efficiently, without sacrificing reliability, operational control or observability.

Governance and Workforce Enablement
Mature infrastructure strategies pair AI capability with internal enablement. Documentation, integrated MLOps tooling and standardized lifecycle workflows ensure teams are ready to manage and scale AI sustainably. Support from an ecosystem of trusted technology partners can further accelerate enablement and integration, helping agencies stand up Centers of Excellence, streamline operational onboarding and drive long-term capability transfer.

The Path Forward

Government AI leaders have a clear opportunity: to advance innovation without compromising operational resilience. The right infrastructure strategy doesn’t require starting from scratch; it builds on existing investments with modular, accelerated and secure components that integrate into mission workflows. When agencies align their AI deployment architecture with mission demands by embracing capabilities like retrieval-augmented generation, hybrid deployment models and full-lifecycle support, they can scale AI with control, trust and lasting impact.

The most effective AI infrastructure is more than a technical foundation; it’s a strategic enabler. When AI is embraced as part of a bigger strategy, it ensures Government agencies are not only ready for today’s AI challenges but also equipped to lead through tomorrow’s opportunities.