Monetizing AI: AI use cases among the government sector

Are your government customers interested in AI implementation and adoption, but aren’t sure where to begin? Experimenting with and trying out various use cases is a great place to start. In my role as an AI technical solutions architect, I’m seeing AI solutions brought to life every day. There’s a ton of opportunities across all industries, government and public sector included.

Within the government sector globally, IDC predicts $41.2 billion USD will be spent on AI use cases in 2026. The compound annual growth rate (CAGR) through 2029 is 31.6% — eclipsing $93 billion.¹

Let’s explore these AI use cases — your government customers may find value in giving them a try as they search for efficiency gains through AI.

Augmented software development has a CAGR of 35.9% through 2029 among government organizations globally, according to IDC. This use case helps modernize how software is built and sustained. Teams can deliver digital solutions with better user interfaces, experiences, and multimedia assets, while keeping pace with ongoing patches, bug fixes and enhancements. Notably, government environments often need to be on premise and this use case can enable that.

Recently a partner was trying to support a government customer that was seeking an air-gapped AI coding assistant deployed entirely on premise. Arrow helped the partner assess AI workloads, then supported a multivendor air-gapped coding architecture across the required hardware and software components. We worked together in our experience center to prove the concept for the end customer. The partner is also considering wrapping Arrow’s services around the technical solution — collaborating with our U.S.-based federal services team to handle initial installation, training, and knowledge transfer, before transitioning ownership to the customer.

As highlighted in our education AI use cases discussion, guided selling is attractive across many industries — and IDC forecasts spending to grow at a CAGR of 34.7% among global government customers through 2029. 

Guided selling combines contract and proposal intelligence with day-to-day seller automation. It can help teams generate and manage contracts, track deadlines, and monitor compliance with contract terms. It can also help accelerate RFI and RFP development. On the seller productivity side, guided selling can also create personalized outreach, automate repetitive tasks like email templates and CRM updates, and offer product recommendations based on purchase history.

Within Arrow and our public sector practice immixGroup, we see this use case show up consistently. We have seen an appetite for guided selling across channel partners who support public sector customers, although we see it apply more to state and local governments that are more likely to have resource constraints. We’re here to help implement vendor-agnostic reference architectures and RFP/RFI preparation. 

Spending among customers in the government sector worldwide is projected to increase by 35.1% from 2026 to 2029 for augmented contact center and field service. This use case speeds issue escalation to resolution while supporting users across digital channels, and with intelligent voice recognition (IVR), including multi-language interactions. It also helps optimize  time by layering in real-time call summaries, prescriptive recommendations, and sentiment analysis to improve consistency and service outcomes. A centralized knowledge repository, such as manuals, case studies, technician expertise, makes it easier to surface relevant articles, identify knowledge gaps, and continuously create new content so performance iterates and improves over time. 

Arrow offers federally tested, industry leading AIOps platforms to support your customers' unique needs. We can also stand up solutions and run demos in our experience center so you can see the technology simulated in a real-life scenario.

With a three-year CAGR of 29.9%, augmented defense, terrorism, investigation, and government intelligence systems turn overwhelming volumes of disparate threat data into actionable intelligence. This use case helps organizations identify, monitor, and respond to risks to personnel, assets, and critical infrastructure. We see it more applicable among customers in the federal space.

The value hinges on whether your customers are able to securely aggregate data at scale and run advanced analytics or AI on top of it, rather than treating AI as a standalone tool. Arrow teams are seeing momentum with partners who need real-world experience designing large-scale foundations, such as data lakes and web scrapers that collect and standardize information. AI outcomes are only as strong as the infrastructure underneath, and government customers need channel partners who can get that architecture right from day one.

Global spending on augmented public safety and emergency response among the government sector has a three-year CAGR of 29.2% worldwide through 2029. This is a compelling AI use case for government customers because it aims to make communities safer while improving how agencies plan, respond, and allocate resources. Smart public safety applies learned intelligence across advanced analytics, social media, collaboration and information-sharing tools to help predict, prevent, and reduce crime, address new and emerging threats, and strengthen emergency and disaster response, while reducing costs. 

One area we see being explored is body camera footage with vision language models (VLMs) that can produce a high-level summary of an incident and help automate the first draft of police reports. While this is still early-stage work, the promise is faster report creation and improved accuracy — provided a human remains involved and the appropriate guardrails are in place. 

There are dozens of other AI uses cases your customers may be interested in exploring. We’re here to help you make these a reality. Request a meeting with our technical team or visit our AI webpage to learn more about our AI capabilities.

¹Source: IDC Worldwide AI and Generative AI Spending Guide - Forecast 2026 | Mar (V1 2026)