Navigating the AI landscape: practical applications for state and local government

Like your favorite mystery novel, following the twists and turns of artificial intelligence (AI) can prove elusive. How can state and local government organizations distill AI concepts into actionable solutions in this landscape of continuous growth, with new solutions coming to market every week? At CGI, we’re here to help. By consolidating the government AI landscape and providing real-world use cases, we can unravel the mystery of AI together. 

What are the 4 pillars of AI implementation?

To understand the intricacies of AI applications in government, you’ll need to think bigger. In this blog, we focus on the four pillars of the AI landscape that best align with state and local governments’ future vision: interactive AI, intelligent discovery and insights, hyperautomation and intelligent operations. When focused on in conjunction, these pillars empower governments to improve end-to-end operations, effectively use taxpayer funds and better serve their citizens. 

4 pillars of the AI landscape: 

1. Interactive AI
2. Discovery and insights
3. Hyperautomation
4. Operations

1. What is interactive AI?

Interactive AI refers to government applications that use artificial intelligence to engage with users in a dynamic, responsive manner. This can be achieved by various solutions, including a virtual assistant, custom large language models (LLMs) and conversational automation. Generative AI, like ChatGPT, is also included in this focus area. 

How does interactive AI enhance engagement? 

By transforming traditionally passive content consumers into active partners, interactive AI shifts technology from an unchanging tool to a responsive participant. The hyper-personalization, whether that be tailoring content, suggesting dynamic recommendations or encouraging users to explore at their own speed and immediate responsiveness of interactive AI applications used in government keep consumers engaged and give them confidence in your organization’s services. 

What human resources use cases should governments consider when leveraging interactive AI?

A virtual assistant can support employees during an unexpected life event, like jury duty. It happens to all of us, but how many members of your workforce know exactly how to manage jury duty absences? Do they need to log it as PTO? Is there a particular category on their timesheet? When was the last time they looked at the leave policy? 

For many employees, this policy is reviewed when they are hired and then quickly forgotten. While employees can likely find the appropriate HR policy through your organization’s intranet, they may be less familiar with that platform than the enterprise resource planning (ERP) solution they use every day. With a virtual assistant, your organization can streamline HR processes by making them available in a familiar solution. 

In this scenario, an employee could ask the assistant from the AI government application, “What is the jury duty policy?” and instantaneously receive proactive guidance with links that summarize only the content they need. With a virtual assistant, your organization will train the AI alongside your IT partner, giving you more control over the data shared than with other AI solutions. 

Examples of interactive AI applications in government: 

• Citizen support: AI government applications that are citizen-facing utilize interactive technology to help users navigate complex processes, answer routine questions and find multilingual support 24/7, as seen in the Department of Homeland Security’s assistant EMMA.
• Administrative management: Interactive AI applications in government are implemented in back-office scenarios to summarize important documents, reduce backlogs and interpret guidance.
• Workflow automation: AI government applications can be trained to automatically digitize vital public records and campaign finance forms, as well as draft operational reports and inspect existing infrastructure. 
• Public health and social services: AI applications in government are often used by local health departments in analyzing patient information to help case workers spot anomalies and forecast needs.
• Fraud detection: AI government applications can monitor and analyze data or transactions to flag issues, improve public safety, encourage compliance and help bolster cybersecurity measures. 

How are conversational AI applications helpful to government agencies?

While a virtual assistant is trained to provide the same guidance to each user, conversational automation is context-aware and specific to one user. Apple’s Siri is a well-known example of conversational AI. By leveraging natural language processing (NLP), recognizing the intent of each query and identifying the specific entities within a query, Siri can provide personalized recommendations to users. 

This concept translates to increased digital adoption for your workforce’s ERP processes. Conversational automation can automate complex tasks through a simple conversation, but let’s focus on a common, time-consuming task: submitting a leave request. With a conversational AI government application, employees can check their leave balance and submit a leave request from any page within the ERP solution. By simply writing a prompt like “Submit a leave request,” the AI can initiate the transaction, gather the required information, recommend related actions and submit the transaction for approval. 

Interactive tools are an accessible entry point into the AI landscape for many government organizations. With a relatively low time investment, organizations can see measurable improvements in user satisfaction and operational efficiency.

2. What is intelligent discovery?

Intelligent discovery helps organizations uncover critical insights, digitally map and visualize business processes and leverage historical data to enhance the user experience. From advanced and predictive analytics and fraud detection to process and task mining, this is a powerful AI application for state and local governments. 

How can your organization unlock strategic insights with intelligent discovery?

In recent years, the prevention of fraud, waste and abuse (FWA) has come to the forefront of many organizations’ annual priorities. Whether it’s closely watching spending related to government assistance programs or tracking the use of government property, many organizations have too much data and not enough resource bandwidth to analyze manually. Cue one of the most intelligent tools: advanced analytics. 

These types of AI government applications and solutions can help organizations make sense of their data and identify data outliers and trends to help improve the discovery rate of FWA. Take, for example, vendor management. Advanced analytics can quickly determine if any vendors have the same address or bank account as employees and notify the designated users for further investigation. Intelligent discovery surfaces suspicious activity so it can be investigated and addressed promptly.

How to effectively manage time with process and task mining

Other key functionalities within intelligent discovery are process and task mining, two types of automation that help to remove process debt by eliminating redundant work and inconsistencies. For example, to help improve the vendor experience and increase the accuracy of submissions, an agency can use process and/or task mining to analyze vendor self-service forms. This analysis may produce critical information to drive website redesign, process refinement, and other optimization opportunities. 

Organizations can save thousands of hours each year by utilizing this kind of AI government application. Thanks to intelligent discovery, government entities can gain visibility into process performance, leverage historical data and statistical models to identify trends and predict outcomes and improve data quality while completing tasks faster. 

3. What is hyperautomation and how is it beneficial?

Hyperautomation is a great buzzword, but what does it mean? In AI applications to government, hyperautomation refers to a disciplined, business-driven approach utilized by organizations to rapidly identify, vet and automate as many processes as possible. 

Simply put, hyperautomation is automating everything that can be automated. In governments, this usually takes the form of low-code development and UI and API automation. 

Hyperautomation enables organizations to rapidly respond to evolving business requirements, improving accuracy, consistency and productivity. In terms of benefits for the citizens, hyperautomation helps users navigate complex tasks and quickly learn new business processes. It’s a win-win. 

What are real-world use cases where hyperautomation improves efficiency in government? 

Many organizations have begun their journey by utilizing robotic process automation (RPA) to process invoices. With tens of thousands of invoices going through government systems annually, this is an obvious starting point for many organizations. Historically, the variation in document types (e.g., images, PDFs) and layouts meant that time-consuming, error-prone manual entry was the only path forward. With RPA and hyperautomation, handling high-volume, low-value-add and error-prone activities like invoice processing is possible. 

Here’s how the process works: AI and optimal character recognition (OCR) technology come together to extract and categorize the relevant data. Once the data is scraped and categorized, the ERP solution is fed only the information it needs to create the transaction, which can also be automated. This allows organizations to make human tasks more efficient by limiting interaction to review and oversight. Over the past ten years, AI has been trained to recognize tens of thousands of different invoice formats, meaning upfront work for government organizations is minimal. 

7 ways hyperautomation can help a government organization:

1. Hyperautomation provides 24/7 access to services
2. Hyperautomation speeds up application approval times
3. Hyperautomation frees up workable hours for employees
4. Hyperautomation predicts emerging challenges to prevent crises
5. Hyperautomation oversees audits and minimizes human errors
6. Hyperautomation provides instant scalability and handles surge capacity 
7. Hyperautomation negates the need for emergency hiring in times of change

The latest advance in hyperautomation: computer vision 

Computer vision is a relatively new OCR technology for state and local governments. This is the layer of AI over OCR technology that infers what the data is and categorizes it. Have you ever uploaded a picture of a bird to Google Image search to determine the species? This is computer vision at work. 

Think of the impact this could have on your inventory management. Instead of scanning barcodes or manually entering information, employees could snap a picture, review the information and move on to the next item. While computer vision does provide exciting possibilities for governments, there are privacy concerns to consider whenever photographic technology is involved. The ways we can utilize this particular type of hyperautomation are ongoing, but we can expect to see computer vision become a common phrase in the near future. 

4. How can AI-powered operations optimize performance?

AI-powered operations are the behind-the-scenes heroes that help organizations collect and analyze infrastructure metrics (detect, diagnose and report on application health performance) and automate routine operations tasks. In the world of state and local government operations, where every second counts, the robustness and reliability of your ERP system can significantly impact service delivery and operational efficiency. 

AI government applications advance how an organization can monitor and maintain its ERP solutions, ensuring they run at peak performance with minimal downtime. Utilizing AI software, these solutions continuously monitor the health and performance of infrastructure and track a wide array of metrics, such as server load, to provide real-time insights into operational status. 

More than just a monitoring tool, AI-powered operations can intelligently analyze data, identify potential issues before they escalate and even initiate corrective actions automatically. By detecting anomalies and potential problems early, the AI government application can execute predefined actions to mitigate risks, often resolving issues before users notice. 

What is the future of the government AI landscape?

While the government AI landscape has matured exponentially over the past 10 years, there is still an enormous amount of untapped potential. By leveraging AI’s predictive analytics and data modeling capabilities, governments could simulate the potential impacts of policies or legislative changes before implementation, considering various economic, social, and environmental factors. This would allow for more informed decision-making, reducing unintended consequences and ensuring that policies are more effective and equitable. 

Imagine a future where AI-driven autonomous systems deliver a range of public services without human intervention. From self-maintaining public infrastructure—like roads and bridges that can detect and schedule their repairs—to environmental monitoring drones that can predict and mitigate natural disasters before they occur, the integration of AI promises a leap toward more resilient and efficient public services. These systems will optimize resource allocation and significantly reduce response times to public needs and emergencies, making government services more proactive and less reactive.

Expect to see the rise of fully integrated smart cities, where AI optimizes traffic and energy use and plays a crucial role in public safety, urban planning, and environmental monitoring. AI government applications could enable real-time data analysis from a network of interconnected sensors across the city, leading to more responsive and adaptive city services. For example, AI-driven systems could dynamically adjust traffic signals to reduce congestion based on current traffic conditions or manage public utilities in real time to conserve resources. 

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