Building the AI Operating Model for Global Communications
Turning early experimentation into a structured adoption model for a global communications function.
Context
As AI adoption accelerated across RTX, Global Communications needed a clearer way to turn interest into practical, responsible use. What started as scattered experimentation became a broader effort to build standards, increase confidence, and apply AI more effectively across communications work.
Challenge
The challenge was not getting people excited about AI. It was turning that interest into something useful, coordinated, and credible across a large communications organization.
Insight
AI adoption would not scale through isolated experiments alone. It needed structure: clear standards, visible priorities, practical training, and use cases tied to real communications work.
Role
I became the strategic lead helping Global Communications move from informal exploration to a more disciplined AI adoption model. Within six months, I grew from an active member of the working group to leading it, shaping priorities for the function, guiding cross-functional adoption, and translating team needs into actionable recommendations for leadership.
My role sat at the intersection of communications strategy, enablement, governance, and change leadership. I helped define where AI could create real value, built the frameworks that made adoption more repeatable, and now report progress, priorities, and opportunities to VPs and the broader Global Communications leadership team on a monthly basis.
Execution
Led AI strategy for Global Communications, helping define priorities across content development, reporting, media monitoring, and workflow improvement.
Scaled the AI Adoption Working Group from an early collaboration forum into a more structured cross-functional program focused on enablement, alignment, and practical use-case development.
Authored SOPs and governance guidance to support responsible AI use and more consistent adoption across teams.
Built GenAI-enabled experimentation frameworks across owned and social channels to improve optimization and performance learning.
Co-hosted AI Labs, a bi-weekly community of practice that created space for hands-on experimentation, peer learning, and knowledge sharing.
Trained more than 100 communicators and helped extend AI guidance across seven Centers of Excellence, creating a stronger foundation for scaled adoption.
Impact
Within eight months, adoption increased 153%, rising from 30% to 76% usage, while participation in the cross-functional working group grew 80%, from 25 to 45 people.
The experimentation frameworks also improved engagement by up to 45%, showing that AI could strengthen communications performance in addition to improving how teams worked.
More broadly, this work helped move Global Communications from fragmented testing to a more visible, governed, and scalable capability. It gave leadership a clearer view of progress, gave teams more confidence in how to apply AI, and created a stronger bridge between strategic priorities and day-to-day execution.
[ Media: screenshots / video / embeds — add assets here ]
Next case study
RTX