Engineer Transitions to AI Leadership at Hitachi Energy

The moment things shifted

Jimmy Oribiana joined Hitachi Energy in 2008 as part of the Engineering Training Program, beginning his career in sales operations. For more than a decade, he worked within this function, building knowledge of how the company operated and where value was generated. But by the early 2020s, something had become impossible to ignore: artificial intelligence was reshaping the energy sector in fundamental ways.

The recognition wasn't sudden or dramatic. Rather, it emerged from watching market trends, understanding where client needs were moving, and observing which capabilities would matter most in the years ahead. Oribiana saw that AI would become central to how Hitachi Energy competed and served its customers. This awareness created a professional inflection point—he could continue in his existing role, or he could attempt to position himself at the centre of this shift.

What they tried

In 2021, Oribiana made the transition to artificial intelligence leadership. But this move required more than a job change. He lacked the technical foundation that AI leadership demanded. Rather than assume he could learn entirely on the job, he took a deliberate step: he enrolled in courses to build his knowledge of programming and AI fundamentals.

This was not a casual upskilling effort. Oribiana invested time in formal education to close the gap between his existing expertise and the technical depth required for his new role. He treated the acquisition of these skills as essential groundwork, not as optional supplementary learning. The coursework gave him both practical knowledge and credibility as he stepped into a leadership position in a field that was still relatively new to the company.

What worked, what didn't

The education investment worked. By acquiring foundational skills in programming and AI, Oribiana was able to assume his role as Global Lead of Artificial Intelligence with a genuine understanding of the technical landscape. This wasn't theoretical knowledge divorced from business reality—he was learning with a specific application in mind, which made the learning more focused and relevant.

What also worked was the timing of his transition. By moving into AI leadership in 2021, Oribiana positioned himself ahead of the curve in his industry, rather than behind it. He was building expertise and leadership capability at a moment when the energy sector was beginning to prioritize AI more seriously. His background in sales operations also provided an advantage: he understood how business decisions were made at Hitachi Energy, which allowed him to balance innovation with practical business needs rather than pursuing AI initiatives disconnected from commercial reality.

The approach required him to be honest about what he didn't know and willing to invest time in learning. There was no shortcut through the technical material, and there was no substitute for actually doing the work of education.

What they'd tell someone else

Oribiana's approach to career development reflects a disciplined perspective on change. Rather than waiting for industry shifts to happen around him, he identified the trend early and took action. Rather than assuming his existing experience would be sufficient, he invested in new skills. Rather than treating the transition as complete once the job title changed, he continued to build depth in his new domain.

Every five years, I reassess my career and ask myself, 'What am I missing?'

This practice of periodic reassessment—of stepping back to examine what skills, knowledge, or positioning might be lacking—creates the conditions for intentional career moves. It's not reactive. It's not waiting for a crisis or a missed promotion to prompt change. Instead, it's a regular discipline that allows someone to notice industry trends early and to act on them before they become obvious to everyone else.

For someone considering a similar transition into an emerging field, the lesson is straightforward: identify the shift, understand what skills you lack, invest in acquiring them, and do this work before you need it. The energy sector's turn toward AI didn't happen overnight, and Oribiana's decision to build technical literacy ahead of his leadership role gave him time to learn without the pressure of immediate performance demands. That combination—early recognition, proactive skill-building, and the willingness to be a student in your own field—creates the conditions for a transition that is both credible and sustainable.