IT Leader’s Fast-5: Ron Guerrier, Save the Children US
For technology leaders, the headline isnโt the training itself; itโs the operating model behind it. Mandatory AI training can reduce fear and create baseline literacy, but it only becomes useful when paired with clear rules on who may use which tools, for what data, and under what approvals. The management question is less โdid people attend?โ and more โdid the business actually change behaviour safely?โ That calls for measurable adoption targets, role-based learning paths, and visible executive participation so AI is treated as a governed capability rather than an optional experiment.
The ERP and finance refresh also highlights a familiar portfolio trap: new platforms do not fix weak data foundations. Leaders should treat data integration, master data ownership, and reporting standards as first-class workstreams, not technical cleanup. If those decisions are deferred, programme risk shifts from delivery delay to unreliable finance, CRM and analytics outcomes. The practical next question for sponsors is which data domains have named owners, what standards are mandatory, and how exceptions will be approved.
For globally distributed organisations, data sovereignty is becoming an operating-model issue, not just a legal one. The hard part is translating jurisdictional rules into repeatable policy for storage, movement and access. That means IT, legal, risk and business leaders need a shared decision framework for where data can reside, when it can cross borders, and which AI use cases are off-limits in certain markets. The trade-off is clear: tighter controls may slow deployment, but weak governance can create compliance exposure and erode trust far faster.
The Decision That Mattered
What recent decision — technical or organizational — has made the biggest difference, and why? Mandatory AI training. There was a reluctance [from employees], but it’s about building up your IQ when it comes to AI. I need everyone to be comfortable with what AI is, and more importantly, what it isn’t. We rolled out AI training modules because telling people to get trained but not giving them the tools to do it isn’t helpful. Everyone is required to do the responsible AI module, that’s a no-brainer and a mandate. Then there’s different levels of training, including foundational training and training on data protection. There are also power users that get agentic AI training, like how to create an AI agent. Lastly, every one of our executives is going to get training. Our CEO went to an executive training where she was taught rudimentary Python and practiced creating a bot. As our CEO becomes comfortable with it, it shows other people that it’s OK for them to use AI. The AI trainings launched today, but it took two and a half months of crossing the t’s, dotting the i’s and making sure legal is fine with it. It was a huge collaboration.The Hard-Won Lesson
What didn’t go as planned recently — and what did it force you to rethink? We’re working on a huge ERP [enterprise resource planning system] project and are going to upgrade our financial management system. We need to really home in on our data integration when it comes to the ERP, because that is the fuel behind financial management systems, our CRM and back office. That’s where we always struggle — making sure we get the data analytics right. Now that we have AI in the forefront, there’s more awareness around how important data is. There were some hiccups, but now we’re having more global discussions on data analytics, and we’re looking at a master data management program. It was a wake-up call that we need to do data management right, or we’re putting a new platform on a really archaic data infrastructure.The Talent Trade-Off
Where are you investing in talent right now — and what are you consciously not investing in? AI dominates things right now, so we’re upskilling folks to be agentic AI administrators, or sys admins. These are people that we already have on staff that are already doing machine learning, or they’re already doing robotic process automation. AI is just kind of an upgrade of those basic systems that we’ve been doing for years. The reason I want to upskill people within [the organization] is because they understand the data and the business the best. It’s a very hard skill set to fill — finding people who understand both the business and the technology. Agentic AI is clearly the next frontier we need to get right.The External Signal
What recent external development is most likely to change how your organization operates, even indirectly? I would say data governance — and it’s not only in the US. The differences, for example, between GDPR and Pan-African data sovereignty rules — all that comes into play. We work in three-quarters of all countries, we’re pretty much everywhere. As we start using more data, digital and AI tools, data sovereignty becomes more of an issue. Where is data at rest? Where can we transport it across lines? It’s a puzzle of rules right now. One of the things I talked about when I spoke at Davos last year — and also at London Climate Action Week — is that we need some consistency when it comes to data, governance and the rules for how we operate across political lines. It’s still somewhat opaque. I live in Chicago, but 90 minutes north in Milwaukee — the state rules on data might differ between Wisconsin and Illinois. That further complicates the ability to create some standards. The Perspective ShiftWhat have you read, watched or listened to recently that changed how you think about leadership or technology — even slightly? I read this book called “From Pessimism to Promise” by Dr. Payal Arora, and it just really resonated with me. It changed the whole way I was going to do my dissertation — I’m working toward a doctorate from the University of South California’s Rossier School of Education. I got so enamored with the book that when I found out that the author’s book tour was coming to Chicago, I went. She signed my copy, and I said, “One day, when I’m doing my dissertation, I want you to be on my committee.” I went back to her about a year later, and now she’s one of my dissertation committee members. The premise of the book is that if we could unlock AI and digital equity to the Global South — the Brazils, Indias and Africas of the world — they could unlock so much more. Her idea is that [these populations] tend to be more innovative because of scarcity. That opened my mind completely and changed my approach to my dissertation. If we do this right and unlock AI for the Global South, we could give them an ability to help us make major breakthroughs.
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