Jimmy Oribiana started his career in 2008 as part of Hitachi Energy's Engineering Training Program. Over 17 years, he rotated through three cities and multiple functions — engineering, market analysis, sales operations — building what he calls a "systems-and-process mindset with an engineering mindset."
His pivot into AI wasn't a sudden leap. It grew gradually from his work building increasingly complex data models for reports and dashboards. About five years ago, he realized the standard reporting tools weren't capturing the full picture of what was happening in the business. He wanted to understand how AI systems could automate insight, not just visualize it. So he went back to school, learning programming, software development, and the fundamentals of AI from the ground up.
"What I had to learn was essentially a new language: the terminology, methodologies, and workflows that connect business needs to AI development," he told The Muse.
Today, as Global Lead of AI in Transformers at Hitachi Energy, Oribiana develops the roadmap for deploying AI across Marketing and Sales globally. He uncovers where AI can unlock value for customers and employees, then works with technical delivery teams to break down requirements and determine the right solutions — some of which call for complex multi-agent systems.
"Leading AI globally means balancing innovation with practicality — ensuring that the solutions we develop are scalable, aligned with strategy, and rooted in real business needs," he says.
His advice for other professionals considering a pivot into AI? "Expertise is built, not inherited. Your non-technical background isn't a weakness — it's context that most engineers lack. The companies that get AI right won't be the ones with the most models. They'll be the ones that figured out how to translate AI capability into business outcomes."