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Authors
Varsha Singh
Varsha Singh
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Thomas Schweiger
Thomas Schweiger
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Marylin Chahine
Marylin Chahine
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Government agencies are increasingly facing the challenge of modernizing and transforming their legacy systems to meet the growing expectations of citizens. NASCIO’s 2024 CIO Priorities List identifies building a digital government and modernizing legacy systems as top priorities. Thorough testing is crucial in any digital transformation and modernization project, especially if the government is to deliver the best digital services that ensure accessibility and an improved citizen experience.

Testing ensures that systems work as intended and do not disrupt the delivery of services to citizens. Although 23% of global IT budgets are reportedly spent on quality assurance and testing, a Consortium for Information & Software Quality (CISQ) report estimates that the cost of poor software quality in the US has risen to at least $2.41 trillion. A failed launch or malfunctioning software can damage public trust and significantly impact frontline employees in critical situations. Therefore, the need for efficient and effective testing methods cannot be overstated.

Although testing automation has led to accelerating processes in recent years, there is still a significant amount of manual work involved in defining test user stories, creating test cases and analyzing test results. This manual work is a drain on resources and impacts project timelines, hampering the ability of public authorities to deliver timely and high-quality digital services to citizens.

Challenges Faced by Governments in Quality Testing

The public sector faces challenges in ensuring the reliability and efficiency of its software applications. These challenges include coping with the frequent updates and changes in government systems, which lead to difficulty maintaining stability and reliability. In addition, public sector organizations often work with multiple systems and platforms, which can make comprehensive testing and problem identification difficult. Regulatory compliance, maintaining traceability, optimizing efficiency and legacy system compatibility can complicate testing and require specialized approaches and tools.

Government agencies also struggle with the scarcity of internal personnel proficient in executing these tasks. With constraints already imposed on staff, requiring them to perform highly manual and repetitive tasks impedes modernization efforts. This puts undue pressure on people who could otherwise contribute more effectively to strategic initiatives. These challenges underscore the urgent need for government agencies to invest in tools that promote efficient workforce utilization, foster cost-effectiveness, and ensure the timely implementation of impactful initiatives.

Advancements in artificial intelligence (AI) present a promising solution to streamline inspection processes, improve accuracy, and accelerate time to market. With AI, it has become possible to extend the scope of test automation to all aspects of a highly automated test cycle beyond the automatic execution of test cases. AI enables a comprehensive approach to the testing process by covering various steps, such as generating test cases, updating tests to reflect scope changes, and finding the root cause of issues.

Our cross-functional team of automation and AI experts have researched and developed groundbreaking approaches to help testers make quality testing processes more comprehensive, scalable, and faster using AI and machine learning (ML). Advanced Intelligence for Testing (AI4T) is an AI-driven testing approach that can help the public sector enhance operations by maximizing automation in all testing activities and reduce manual efforts and shorten test cycles drastically.

The AI4T approach offers several testing solutions, including Quality Copilot and Sqeed. Quality Copilot can help government agencies improve software testing by leveraging the power of AI to connect requirements to test scripts using Large Language Models. 
Nagarro's Sqeed, an automated test analysis tool, can identify the root cause of accelerated test failure analysis issues and reduce analysis time by up to 70% by aggregating, clustering, and visualizing log files in one central location.

How AI-powered testing can unlock the potential of government agencies

Let's take an in-depth look at how AI4T can improve government services:

Ensuring software functionality and reliability

AI4T provides greater insight into project reliability and functionality through smart visualization and rapid defect detection. By detecting issues early in the development lifecycle, government agencies can proactively address them, mitigating the need for last-minute changes and ensuring timely project delivery. This proactive approach improves software quality, optimizes resource utilization, and mitigates the risks associated with project delays.

Dealing with frequent updates and changes

Public sector agencies often grapple with the complicated nature of their application development processes, characterized by numerous dependencies and changing requirements. AI-driven tools can automate testing and enable agencies to test software applications quickly and accurately after updates or changes. AI4T can analyze large volumes of product specifications, user reports, and system requirements, identify patterns and predict potential use and edge cases.

The self-healing capabilities of AI-powered testing also play a crucial role in ensuring uninterrupted test execution, even when the application's scope changes. By automatically adapting scripts to changes, AI4T minimizes downtime and enables agencies to stay relevant without incurring additional time and cost overheads.

Work with multiple systems and platforms

AI-driven testing tools can provide cross-platform capabilities, allowing agencies to perform comprehensive testing across different systems and platforms. These tools can automatically adapt test cases to different environments, reducing the manual effort required to test multiple systems and making identifying issues across networked platforms easier. One of our tools, Sqeed, provides log information from multiple sources, screenshots, videos, and other information in one centralized location.

Ensuring compliance and maintaining traceability

AI-driven testing can help automate compliance testing by generating and executing test cases based on regulatory requirements. Our solution excels at creating test scripts by leveraging existing scripts and generating new scripts for analogous functionalities.
Machine learning algorithms can learn from previous test data to prioritize test cases, identify potential risk areas, and optimize testing efforts, ensuring compliance and reliability despite frequent changes. In addition, AI can analyze test data to ensure traceability between requirements, test cases, and results, facilitating compliance management and auditability.

Shortage of qualified internal staff

AI-driven testing can augment the skills of internal staff by automating manual and repetitive testing tasks. By freeing up staff from mundane testing tasks, government agencies can allocate their resources to more strategic initiatives, maximizing the efficiency and impact of their workforce. Our solution also enables agencies to overcome the challenges associated with high turnover rates and knowledge gaps in legacy systems, ensuring continuity and consistency in testing processes.

How can government agencies optimize AI-driven testing?

While AI has proven useful, it is equally important for agencies to follow some guardrails when using AI to ensure optimal performance and effectiveness.

Bias

AI systems can produce biased outcomes that reflect and perpetuate societal biases, including historical and current social inequalities. The government must be aware of biases that may impact test cases. Proper training of government employees working on AI projects is critical. By working with vendors, the government can jointly test for biases, ensuring a comprehensive approach to identifying and fixing potential problems in AI systems. This collaborative effort increases transparency and accountability and promotes a more robust and unbiased implementation of AI technologies.

Technology agnosticism

Government agencies operate in different technological landscapes and often use different platforms and systems. Therefore, any AI-powered testing approach must be compatible with different technology stacks to integrate seamlessly with existing infrastructure. Nagarro's AI4T stands out due to its technology agnosticism, which ensures that it can adapt to different environments without compromising performance or compatibility. AI4T allows government agencies to leverage existing technology investments while enhancing testing capabilities through flexibility and interoperability.

Data integrity and privacy

Given the sensitivity of government data and the regulatory requirements that govern its use, it is imperative that AI-powered testing prioritizes data integrity and protection. Nagarro's AI4T approach emphasizes strict security protocols and regulatory compliance to protect sensitive information throughout the testing process. AI4T enables agencies to conduct testing confidently, protect critical data, and mitigate the risk of data breaches by implementing access controls and privacy-enhancing technologies.

Scalability

As government agencies digitally transform and modernize, the complexity and scope of testing requirements will inevitably evolve. Therefore, choosing an AI-powered testing approach that can scale effectively to meet growing testing requirements and application complexity is essential. Nagarro's AI4T is designed with scalability in mind, providing the flexibility to expand testing capabilities without compromising performance or efficiency. AI4T enables government agencies to future-proof their testing processes and ensure long-term viability in an ever-changing technology landscape by providing scalable infrastructure and adaptable testing capabilities such as self-healing test scripts.

Takeaways

  • Government agencies prioritize modernizing legacy systems for citizen satisfaction. Thorough testing is vital for service accessibility and trust.
  • Public sector testing faces hurdles such as frequent system updates, limited test data access, and compliance issues. Efficient methodologies are needed to overcome these challenges.
  • AI streamlines testing processes, enhances accuracy, and accelerates time-to-market. Nagarro's AI4T can be tailored to addresses government-specific challenges effectively.
  • Implementing AI-enabled testing requires careful consideration of factors such as technology agnosticism, data integrity and privacy, and scalability. With the help of Nagarro's AI4T approach, these needs can be addressed effectively.

 

Nagarro’s Public sector division works with state and local governments on such digital transformation projects. Click here to find out more.