Original Broadcast Date: 09/21/2026

Sponsored by Amentum

Artificial intelligence is changing the way federal agencies approach mission delivery, cybersecurity, and workforce productivity. According to Jill Bruning, Chief Technology Officer at Amentum, the key to realizing AI’s potential is not simply adopting the technology itself, but ensuring agencies have the secure digital foundation necessary to support it.

During an interview on Fed Gov Today, Bruning explains that AI is helping organizations move from a reactive posture to a proactive one. In enterprise information technology, agencies are increasingly using AI to anticipate issues before they become problems. In cybersecurity, AI is becoming essential due to the sheer volume of threat activity and telemetry data organizations must analyze and respond to every day.

Bruning says AI is also having a direct impact on the workforce. By putting more information at employees’ fingertips, AI enables people to make smarter decisions in real time. At the same time, it helps automate manual and repetitive tasks, allowing workers to focus on higher-value activities. However, she emphasizes that technology should enhance human performance rather than replace it.

“The important part is making sure we're not taking the people out of the loop,” Bruning says. “We're keeping the human in the lead.”

That balance between technology and human oversight is becoming increasingly important as agencies expand their use of AI across mission environments.

Bruning argues that successful AI adoption begins with a strong digital foundation. For cybersecurity organizations in particular, that foundation starts with visibility.

Agencies must understand what devices, assets, tools, and data they possess before they can effectively secure them or use AI to derive meaningful insights. Without that visibility, organizations risk building advanced capabilities on top of an unstable or incomplete infrastructure.

The challenge becomes even more complex because government environments are constantly evolving. New data is generated continuously, architectures change, and mission requirements shift over time. As a result, Bruning says agencies need governance structures that can adapt alongside the technology.

Rather than viewing AI implementation as a one-time project, organizations should establish guardrails, processes, and governance frameworks that enable ongoing management and oversight.

One concept Bruning highlights is what she calls “right-sized AI.” As enthusiasm for AI continues to grow, organizations may be tempted to apply the technology to every challenge they encounter. Bruning cautions against that approach.

Instead, right-sized AI means selecting the appropriate tool for the appropriate environment while ensuring cybersecurity requirements are met. It also requires strong governance and realistic expectations about organizational readiness.

According to Bruning, agencies should avoid the extremes of either rejecting AI entirely or attempting to transform their entire enterprise before the necessary foundations are in place. The goal is to deploy AI where it delivers the greatest value and produces measurable outcomes.

“Right size is really about making sure AI gives you the best value and outcomes,” she explains.

Cybersecurity remains a central component of that strategy. Bruning notes that while conversations around AI continue to evolve, many of the core principles of cybersecurity remain unchanged.

She points to zero trust as an example. While AI was not a major part of the original zero trust discussions several years ago, the underlying principles still apply. Bruning describes zero trust not as a product, but as an operational model built upon a secure digital foundation.

For organizations implementing both AI and zero trust, resilience is critical. Strong cybersecurity depends on maintaining a secure technology stack and ensuring systems can continue to operate effectively in the face of threats and disruptions.

Bruning also addresses the ongoing discussion surrounding compliance and resilience. Historically, many organizations viewed those objectives as competing priorities. Agencies often focused heavily on meeting compliance requirements, sometimes at the expense of broader security outcomes.

Today, Bruning believes the conversation should focus on how compliance and resilience work together.

Compliance remains necessary because organizations must satisfy regulatory and security requirements. At the same time, resilience is essential for ensuring mission continuity and operational effectiveness. Rather than choosing one over the other, agencies should integrate both into their overall cybersecurity strategies.

One way to accomplish that, she says, is through a disciplined systems engineering approach. Not every system is the same, and not every environment requires identical solutions. Agencies must carefully evaluate mission needs and apply appropriate technologies and practices to achieve desired outcomes.

As federal organizations continue their AI journeys, Bruning’s message is clear: success depends on more than deploying new tools. Agencies must build secure digital foundations, establish strong governance, maintain human oversight, and focus on practical outcomes. By taking a measured, mission-focused approach, organizations can harness AI’s benefits while strengthening cybersecurity, resilience, and operational performance across government.