In February 2026, Paul Nielsen announced that he will transition out of his role as director and chief executive officer of the Software Engineering Institute (SEI) at Carnegie Mellon University. During Nielsen's tenure, the SEI has marked major institutional milestones that underscore its enduring role in strengthening the security, resilience, and reliability of the nation's software- and AI-intensive systems. The institute recently celebrated 40 years of innovation and saw its contract renewed, which paved the way for CMU to operate the SEI for another five years. In our latest SEI podcast, Nielsen recently sat down with Matthew Butkovic, technical director of Risk and Resilience in the SEI's CERT Division, to discuss his legacy at the SEI, the impact of mentors, and the importance of encouraging scientists and engineers to do their best work.

Cybersecurity staffing shortages are a major concern in the government given the increasingly sophisticated cyber attacks on the nation's critical infrastructure. In the FY2023 National Defense Authorization Act (NDAA), Congress tasked the Pentagon with finding flexible options to address cyber staffing needs. The Pentagon commissioned the SEI to conduct an independent study to assess the feasibility and advisability of creating a civilian cybersecurity reserve (CCR) that could harness cyber expertise from the private sector to mobilize a mission-ready workforce capable of operating in contested environments. In our latest podcast from the Carnegie Mellon University Software Engineering Institute (SEI), the lead authors on the report, Marie Baker, a technical manager in the SEI's CERT Division, and Chris May, technical director of the CERT Cyber Mission Readiness directorate, sit down with Mike Winter, deputy technical director of threat analysis, to discuss their findings.

While Stanford University found that AI investments, optimism, and accessibility are rising, a recent MIT report suggests that 95 percent of organizations are realizing no returns on their generative AI investments. Research from Accenture found that only 8 percent of companies are scaling AI at an enterprise level and embedding the technology into core business strategy to maximize value.

Mismatched expectations, misaligned applications, and poorly executed or untested implementation practices—not the technology itself—often keep organizations from realizing immediate value from an AI investment. For AI to increase efficiency, productivity, and value while conserving resources and lowering overall costs, organizations need to shift their focus from hype-driven experimentation to foundational capabilities and practical, measurable outcomes. In our latest podcast from the Carnegie Mellon University Software Engineering Institute, Dr. Ipek Ozkaya, technical director of AI-Native Software Engineering, sits down with Matthew Butkovic, technical director of Risk and Resilience in the SEI's CERT Division, to discuss their work on an AI Adoption Maturity Model that organizations can use to create a roadmap for predictable AI adoption and realization of AI benefits.