Tze Phei Tee, Group CIO at Wasco Berhad, talks to The Ortus Club about his transition from high-level consulting at IBM and Oracle to the heart of the energy sector. Tze Phei argues that while technology is straightforward, the true challenge of a CIO lies in the “people element” of change management. He emphasises that in operationally intensive industries, success depends on bridging the language gap between IT and engineering. For Tze Phei, the most effective leaders are those who seek high-level peer dialogue to move beyond theoretical AI risks and into practical, Industry 4.0 execution.
Executive Summary: Key Takeaways
- Consulting vs. Ownership: Moving from consulting to the end-user side requires a shift from delivering scope to living with the long-term human consequences of transformation.
- The IT-OT Integration: In the energy sector, digital transformation relies on sensors and IoT to integrate Information Technology with Operational Technology, moving from manual checks to predictive maintenance.
- Unlearning as a Prerequisite: Upskilling is insufficient if leaders cannot unlearn the habits and disciplines of the last 30 years to make room for AI-driven workflows.
- Safety First AI: Beyond operational productivity, AI’s most critical industrial application lies in enhancing Health, Safety, and Environment (HSE) performance to protect front-liners.
- Language as a Bridge: Transformation often fails when IT and engineering teams speak different languages; future leaders must be “multilingual” in both business and engineering terminology.
Tze Phei Tee spent a career at global consulting giants like IBM and Oracle, helping customers implement best practices from the outside looking in. However, the desire to be part of the story eventually drew him to Wasco Berhad. As Group CIO, he has moved from delivering scope to managing the complex human resistance that defines industrial transformation. Tze Phei understands that in an energy company, technology is merely a tool for a much larger mission: navigating the transition from “brown energy” to sustainable, green renewables. He believes that to stay relevant, leaders must be the first to unlearn the status quo and the first to embrace the “white space” between engineering and IT.
How does the CIO’s role differ from High-Level Consulting?
Tze Phei explains why managing human resistance is the hardest part of moving to the end-user side.
“In consulting, the focus is on implementing platforms and redesigning processes at a high level. When you are the CIO, you live with the stakeholders every day. The weightage shifts significantly toward the people elements. Technology can be straightforward if you have the right tools, but managing human resistance is one of the hardest challenges. In an energy company, we have many front-liners whose digital literacy may not be as high as office-based employees. We have to start with basic conversations about what AI and data actually mean to make a transformation stick.”
What is the IT-OT Integration in Industry 4.0?
Unlike finance or retail, Tze Phei highlights how the energy sector relies on physical sensors and machines to gather real industrial data.
“Digital transformation is a universal term, but its application varies. The energy sector relies on sensors to gather real industrial data to improve operations. This involves a revolution in how machines are automated. By integrating data, AI, IoT, and Cloud technology, we can monitor smart factories to identify anomalies. Ultimately, this allows us to move into predictive maintenance. We call this the integration between Information Technology (IT) and Operational Technology (OT). It is about making the physical machine talk to the digital dashboard.”
Why is “unlearning” the biggest challenge for IT veterans?
Tze Phei argues that upskilling is ineffective if senior staff cannot let go of the habits they have used for decades.
“Technology evolves extremely rapidly. Even experienced professionals who have been in IT for 30 years must evolve. My core philosophy is that we must know how to unlearn old things before we can learn new things. Many people upskill but struggle to let go of the disciplines they have used for decades. As technologists, we must be role models. If the IT team does not use AI correctly, we cannot expect other departments to adopt it. We pair bold young talent with the wisdom of senior staff to ensure we shave off extra tasks that no longer add value.”
How does AI move the needle on Health, Safety, and Environment (HSE)?
Beyond efficiency, Tze Phei discusses using predictive modelling to forecast disruptions and protect infrastructure workers.
“We are using AI to vet large sets of operational data to analyse the health condition of our assets. This allows us to forecast disruptions. Crucially, we are also applying this to human safety. We are a large infrastructure business, and our philosophy is that business only follows when people are safe. Therefore, we are putting significant attention on how AI can improve our Health, Safety, and Environment (HSE) performance. If these digital tools are not utilised to accelerate social and governance goals, then the progress toward modernising the sector will be limited.”
Why must Future Leaders speak “Engineering Lingo”?
With a background in both engineering and business, Tze Phei stresses the need to bridge the gap between technical silos.
“Future leaders cannot just focus on technical aspects; they must understand how the operations actually work. Energy and manufacturing are engineering-centric. You need to understand the ‘lingo’ of how engineers think. Transformation often fails because the IT team and the engineering team are speaking two different languages. Because I come from an engineering background and later went to business school, I try to bridge these two groups. Understanding engineering terminology gives me a vantage point to increase adoption and ensure the transformation goes smoothly.”
How are you going to “Live with AI” in the future?
In a final challenge to leadership, Tze Phei encourages a proactive stance toward the rapidly closing gap of AI adoption.
“I would ask: How are you going to live with AI in the future, based on your current business context? This is a question I ask myself every day. You cannot avoid it because the competition will eventually catch up. There is currently a gap between the theoretical risk of AI and the reality of its adoption, but that gap will close quickly as people become more familiar with the tools. We should not take this period of transition for granted; we must be ready to adapt to stay relevant.”
Join the Conversation: The Ortus Club’s Executive Network
Across Tze Phei’s insights on unlearning, the IT-OT integration, and the language gap between silos, one pattern is clear: these challenges aren’t solved in isolation. They require a peer-level perspective and the kind of high-trust dialogue that transcends the office walls.
His vision of the “CIO as a Bridge” reflects a broader reality: today’s technology leaders cannot rely on technical skill sets alone to lead an energy transition. The most effective executives, especially those navigating the intersection of heavy engineering and AI, actively seek out peer dialogue as a strategic necessity to challenge the status quo.
At The Ortus Club, we host curated executive roundtables that bring together senior leaders facing these exact challenges. Step away from the “way it’s always been done” and engage in the kind of open, high-value conversations that help you unlearn the past and architect the future of industrial energy.
Frequently Asked Questions
Q: What is IT-OT Integration?
A: It is the hardware and software integration that allows Information Technology (data processing) to communicate with Operational Technology (the physical machines and sensors on a factory floor or oil rig).
Q: Why is “unlearning” critical for AI adoption?
A: Because AI-driven workflows often contradict traditional, manual processes. To work efficiently with AI, leaders must be willing to abandon old habits that no longer add value in a digital-first environment.
Q: What is Predictive Maintenance in Energy?
A: It is a technique that uses data from IoT sensors and AI modelling to predict when a machine or asset will fail, allowing for repairs to be made before a disruption occurs, rather than reacting to a breakdown.
Q: How does Engineering Lingo affect digital transformation?
A: When IT teams understand the specific terminology and pain points of engineers, they can design tools that are more intuitive and useful for the people on the front lines, leading to higher adoption rates.
Q: What role does AI play in ESG (Sustainability)?
A: AI helps energy companies monitor their carbon footprint, optimise resource usage, and develop new business models for renewable energy, directly supporting net-zero and climate goals.
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