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Modernizing Government DevSecOps with Artificial Intelligence

Discover how leveraging artificial intelligence in DevSecOps can revolutionize federal government operations and foster public sector innovation.

Artificial intelligence (AI) and machine learning present remarkable opportunities for enhancing efficiency and fostering innovation. However, challenges related to outdated legacy systems, code security, and legislative gaps continue to hinder modernization efforts. By integrating AI with DevSecOps processes, we can strengthen code security and address these concerns. Furthermore, blending AI capabilities with human intelligence allows for a more comprehensive approach to security, ensuring that government operations are both future-proof and resilient against emerging threats.

Current state: Exploring AI across the software development lifecycle

Government agencies are increasingly exploring AI adoption to improve productivity by automating complex tasks in the software development process. However, agencies face hurdles such as outdated procurement laws, a shortage of skilled professionals, and the challenge of bridging the gap between modern technology and legacy systems. These challenges highlight the need for evolving policies to support AI’s role in government DevSecOps practices.

According to GitLab research, 67% of security professionals in the public sector find it challenging to get development teams to prioritize remediation of security issues.

Future vision: Embracing AI for enhanced DevSecOps

Looking ahead to 2025 and beyond, AI is expected to become integral to government operations, particularly in streamlining processes, identifying and addressing potential vulnerabilities, and modernizing legacy code. AI-driven automation will allow agencies to move their focus from repetitive tasks to strategic innovation, addressing inefficiencies and managing increased workloads. Anticipated policy changes will align AI advancements with ethical standards and data privacy, ensuring responsible AI adoption. Additionally, AI will enhance the security of the software supply chain by proactively identifying security vulnerabilities and streamlining incident responses, driving a new era of government efficiency and smarter cybersecurity.

What comes next?

AI and machine learning are already automating routine tasks, enabling DevSecOps engineers to dedicate more time to strategic initiatives, innovation, and the continuous improvement of software development and operations processes. As AI evolves, it will become a key partner for developers across all stages of the software development lifecycle, augmenting their capabilities and enhancing productivity. This will drive significant improvements in government efficiency and security. Through thoughtful adoption and integration, AI can transform public sector service delivery, creating a secure, efficient, and innovative government that better meets the needs of citizens.

Presently, AI plays a crucial role in enhancing efficiency and driving innovation across the public sector. As we look ahead to 2025 and beyond, AI is poised to advance these applications, further embedding itself in government operations and helping agencies build secure software, faster.

Read the full whitepaper for a deep dive into the current and future role of AI and machine learning in federal government DevSecOps, focusing on its evolution in critical areas like vulnerability management, incident response, and legacy code modernization.

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Modernizing Government DevSecOps with Artificial Intelligence

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Key takeaways
  • AI is a powerful tool for enhancing operational efficiency in federal agencies, helping to overcome hurdles such as strict security requirements and a lack of skilled workers.
  • By 2025, AI is anticipated to be a core component of government functions, refining processes, updating outdated systems, improving security practices, and promoting efficiency.
  • Implementation of AI within the federal government could bring about substantial advancements in decision-making, effectiveness, and innovation, revolutionizing the sector and refining DevSecOps methodologies.