GovCIO Media & Research Podcasts

The National Institute of Standards & Technology (NIST) is expanding its DevSecOps research to explore how artificial intelligence can support software development and security workflows. Michael Ogata, a computer scientist at NIST, discussed how AI and large language models are being applied to coding, testing, security evaluation and vulnerability remediation. He also outlined NIST's emerging focus on agentic AI, including how organizations can establish identities and credentials for AI agents, authorize their actions and ensure those actions remain traceable to accountable human users.

The Navy is making AI and data central to how it operates, with a new strategy focused on faster decision-making and scaling what works. Department of the Navy CTO Justin Fanelli discussed the service's push toward an AI-first maritime force, how officials are evaluating AI projects based on return on investment and mission impact, and why the "make versus buy" mindset is becoming increasingly important in software development. He also shared how the Navy is organizing technology portfolios, moving capabilities from pilot to production faster and building a software-defined fleet that can adapt to changing mission needs.

Government software development pipelines are increasingly integrating AI coding assistants, but Air Force Sustainment Center Software Directorate CTO Kurt Jarvis said success depends on improving how developers use existing code, not just generating new code faster. Speaking with GovCIO Media & Research at the Carahsoft DevSecOps Conference, Jarvis outlined an engineer-first approach that uses retrieval-augmented generation (RAG), vector databases and established DevSecOps pipelines to safely accelerate software development. Jarvis said one of the biggest opportunities for AI is helping developers discover and reuse decades of trusted software already maintained by the Air Force. The goal, he said, is to make AI a code‑reuse engine, not a code‑generation machine. He also emphasized that AI has not changed the Air Force's software engineering standards. Existing CI/CD pipelines are still the foundation for evaluating AI-generated code. AI can accelerate development, Jarvis said, but engineering discipline and human oversight remain essential to producing mission-ready software.

Six months after War Secretary Pete Hegseth directed sweeping acquisition reforms across the department, the Defense Information Systems Agency is accelerating its transition from government-developed cybersecurity tools to commercial technologies. On this episode of CyberCast, Brian Hermann, director of PAE Cyber at DISA, discussed how the agency is modernizing its cyber acquisition strategy by prioritizing commercial solutions, software-as-a-service offerings and more flexible contracting approaches. Hermann explained why DISA believes commercial technologies can deliver capabilities faster, reduce operational risk and better keep pace with evolving cyber threats. The conversation also explored how DISA is breaking down budget silos and consolidating resources to give portfolio leaders greater flexibility to adopt new technologies and retire legacy systems more quickly. As the department's acquisition transformation takes shape, Hermann outlines DISA's evolving role as an integrator of commercial capabilities — ensuring interoperability and mission effectiveness across contested, coalition and edge environments.

Artificial intelligence is helping transform how the Energy Department approaches one of its most complex challenges: cleaning up nuclear waste. At the 2026 SCSP AI+Expo, Savannah River National Laboratory Associate Laboratory Director for Environmental and Legacy Management Eric Pierce joined GovCIO Media & Research to discuss how the lab is applying AI to improve environmental monitoring, reduce costs and accelerate cleanup efforts across the Savannah River Site. Pierce highlighted SRNL's Advanced Long-Term Environmental Monitoring Systems (ALTEMIS), which uses AI to predict contaminated groundwater plume movement. The technology has reduced monitoring requirements from quarterly sampling across 2,000 wells to a single annual verification sample, significantly lowering costs while maintaining confidence in environmental safety. He also discussed the lab's AI Accelerated Strategies and Solutions in Environmental Technology (AI-ASSET) initiative, which builds on ALTEMIS by collecting real-time, AI-ready environmental data. Currently, roughly 30% to 40% of the site's data is prepared for AI applications. Pierce also explained how SRNL is working with industry and government partners to modernize the remaining data and expand the use of AI-driven environmental cleanup technologies. The effort is part of a broader DOE initiative exploring how AI can advance scientific discovery, operational efficiency and innovation across the national laboratory system.

Astronomical data presents unique challenges for artificial intelligence, often requiring specialized AI models tailored to the needs of astrophysicists and large-scale scientific research. Scientists at the Center for Astrophysics — a collaboration between the Smithsonian Astrophysical Observatory and Harvard College Observatory — developed the AstroAI Institute to help researchers analyze massive datasets and accelerate scientific discovery through AI-driven analysis. At the 2026 SCSP AI+Expo, the institute's Founder and Director Cecilia Garraffo told GovCIO Media & Research the center is using AI to search for unexpected patterns in large data sets and cluster data based on similarity without prior coding, enabling scientists to detect new phenomena and uncover previously unseen relationships. Garraffo also discussed the growing need for AI education and workforce development across the scientific community. She explained how AstroAI is helping train researchers at all levels — from students to senior scientists — to use AI effectively in astrophysics research and discovery.

Climate surveys used by the War Department like the Defense Organizational Climate Survey (DEOCS) are annual check-ins to assess unit morale, cohesion and leadership trust. Traditionally, these surveys take a long time to gather and analyze by leadership. A pair of Marine Corps innovators told AI GovCast that they've created a new AI–enabled survey tool prototype that is designed to give commanders near‑real‑time insight the day‑to‑day stressors affecting Marines. The prototype, called PULSE Check, aims to close long‑standing feedback gaps that leaders say contribute to retention problems — particularly in the reserve component. Col. Prescott Wilson, chief of staff for the 4th Marine Logistics Group, said the idea emerged after a commanders' conference where Marines explained why they were leaving drilling status for the Individual Ready Reserve. "By the time we're talking to these Marines on stage, they've already made a decision … that's talent we can't get back," Wilson said. Lt. Col. Samuel Sung, an innovation officer with the Logistics Innovation Office and a Marine reservist who co‑developed the prototype, said the team deliberately focused first on whether the idea was even useful before tackling the complex security and compliance requirements of deploying AI inside the department. He added that AI-driven analysis enables more frequent surveys and faster feedback cycles, allowing commanders to test changes and measure results monthly instead of annually. That accelerated process, Sung said, can improve decision-making while also reinforcing to Marines that their feedback is being heard.