Insights into the technologies driving our nation forward.
Welcome to GDIT Perspectives Highlights. Here you will find a selection of our latest insights from people supporting some of the most complex government. defense, and intelligence projects across the country - delivering the art of the possible.
Explore more insights from GDIT at www.gdit.com/perspectives.
Effective AI: Harnessing the Power of Data Normalization
GDIT's AI/ML Solutions Director Matt Pearce discusses how data normalization ensures diverse data sources align, making data reliable and ready for effective model deployment.
Applying AI at Speed with Mission Insight and Technology Partnerships
In our latest Voices of Innovation podcast episode, GDIT President Amy Gilliland joined Goldy Kamali, CEO of Scoop News Group, to discuss the intersection of mission and AI at speed for government.
Left of Boom in a Fragmented Enterprise: How Agencies Can Regain Cyber Visibility
Dr. Matthew McFadden, GDIT VP of Cyber, shares how agencies can unify visibility, minimize cyber risk, and prepare for tomorrow's advanced threats.
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Loved this edition, especially the focus on AI at speed and the reminder that modernization isn’t just about adoption, but integration. What stood out most: the emphasis on data normalization and proactive cyber defense. At scale, that means your architecture must treat every component as an observable, enforceable asset, from dev environments to mission systems. In practice, staying ahead of cyber threats isn’t about reviewing logs after the fact, it’s about identifying policy drift or malicious behavior as it happens, within the dev pipeline or live runtime. Not through bolt-on alerts, but by embedding automated detection, enforcement, and traceability into the very fabric of how systems are built and run. That’s how you accelerate with confidence, without sacrificing trust, speed, or mission agility. How are your teams approaching this balance between velocity and enforcement as AI capabilities expand across operational infrastructure?
One idea that stood out: data normalisation is the real unlock for AI at scale. Without clean, aligned data, even the best models can misfire. This foundation can’t be skipped.
Gracias por compartir
Looking forward to testing out Luna.
Some new insights through highlights, thank you GDIT