CASE STUDY
Palo Alto Networks
Training the Team to Own AI
The Challenge
As Palo Alto Networks increased its emphasis on AI-driven efficiency, the marketing teams supporting Unit 42 and Cortex faced a familiar enterprise problem: leadership expectations were rising quickly, but practical guidance on “how” wasn’t standardized.
From compliance to ownership
David Moulton didn’t want his team to simply adopt AI to meet a mandate. He wanted them to own the shift. He wanted his team to become confident practitioners who could set the standard internally, help peers avoid common pitfalls, and act as trusted guides as adoption expanded across the organization.
The Approach
We began with an AI readiness assessment across the team to understand true starting points: who was already experimenting, who felt behind, where uncertainty was showing up in daily work, and what knowledge gaps were preventing consistent adoption. The assessment showed strong motivation but uneven confidence and fragmented tool use, making a shared baseline the first priority.
Build capability that scales across roles
Using those findings, we designed a 12-week training program with twice-weekly sessions to move the team from AI fundamentals to confident, practical application in marketing and communications work. The training centered on Google Gemini (aligned to their Google Workspace environment), while also introducing complementary tools, including ChatGPT, Claude, and Notion AI, so team members could learn to choose the right tool for the task rather than forcing every use case into one platform.
The Solution
As we took the marketing team through a series of tailored trainings, we also reinforced the learnings through real-time practical support, turning the training into actual behavior change.
We paired structured sessions with office hours that helped individuals apply concepts to their specific responsibilities. Our teachers used the time to help trainees solve actual problems in their daily workflows with AI tools.
The engagement delivered an assessment-informed enablement program that emphasized repeatable skill-building over one-off experimentation.
Instead of relying on a few power users, the program created a broader, more resilient baseline—making it easier for the team to model effective AI usage, support peers, and contribute to broader organization-wide adoption as expectations continue to evolve.
Results
When we heard the mandate to integrate AI into our jobs, we knew there was a change on the horizon. I didn’t just want my team to know about AI—I wanted us to own it within our organization. This training helped us benchmark our abilities, learn to use the tools available to us, and build better workflows that reduce tedious tasks and increase creative productivity.
- David Moulton, Palo Alto Networks
Unit 42 and Cortex moved beyond “AI readiness” into AI leadership capability: consistent foundational knowledge, clearer decision-making about where AI adds value, and shared resources that supported ongoing use.
But the end of the training, the team developed:
A shared language and baseline understanding, with 95% of trainees reporting they feel prepared to keep learning as AI tools evolve.
Trainees reported getting actual time back, with 30% saving 3-4 hours, 45% reporting 5-8 saved hours, and 15% reporting more than 9 hours of savings per week.
With a benchmark AI Readiness score of 79, the marketing team now shows Stronger AI confidence across roles, with a 91 AI Readiness score, reducing the gap between early adopters and teammates new to AI.
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