Tenaga Nasional Berhad’s “Invisible Architect”: Building a Resilient, Data-Driven National Grid

In this episode, Ir Ts. Muhammad Al Jundi Abdullah, Lead of Analytics at Tenaga Nasional Berhad (TNB), shares how Malaysia’s national utility is leveraging AI and advanced analytics to strengthen grid management and support faster, data-driven operational decisions. 

The conversation explores how analytics can help optimise existing assets, improve reliability, support smarter investment planning, and detect unusual consumption patterns, including potential electricity theft. It also looks at how TNB views AI as a tool to augment human expertise and empower its workforce, rather than replace it.

TNB is a leading Malaysian utility company in Asia with an international presence in the United Kingdom (UK), Ireland, Australia, Turkiye, Saudi Arabia, Kuwait, Pakistan, and Cambodia. Within the renewable energy space, TNB has a total gross portfolio of 3.3 Gigawatts (GW) in Peninsular Malaysia (including 2.5GW of large hydro) and 1.3GW across the UK, Ireland, Australia, and Turkiye, comprising mainly solar, wind, and hydro energy generation assets. TNB also transmits and distributes electricity across Peninsular Malaysia, Sabah, and the Federal Territory of Labuan. As of 31 December 2025, TNB supplies electricity to over 11 million customers.

Transcript

Copy Transcript Copied

Vanessa Kwan  0:22  
.Hello and welcome to the ASEAN B to B growth podcast, where we sit down with individuals responsible for driving growth within their organizations here in Southeast Asia. My name is Vanessa, and I'll be your host for today. In this episode, we are peeling back the layers of a critical, yet often unseen powerhouse of the Malaysian economy. We are exploring the invisible architect, the digital and data driven infrastructure that ensures the lights stay on for millions while the nation pushes towards a greener, smarter future to help us understand how to build a truly resilient, data driven National Grid. We are joined by engineer, technologist Muhammad Al Jundi Abdullah, the lead of analytics at the Naga national Berhad anjik Jundi, a pleasure to have you here with us. Perhaps to start off, could you give us a brief introduction of yourself, your role at TNB, and perhaps for our audience who may not be that familiar with the company, a brief overview, a brief introduction of the company as well.

Muhammad Al Jundi Abdullah  4:05  
Okay, thank you. Vanessa, hello everyone. My name is Jundi. I'm the lead for analytics in distribution network division at tanago National Berhad or TNB for the audience. Information for the audience, TNB, tanaga National Berhad, especially the distribution network division is responsible to deliver electricity to our millions of customers across Malaysia. So for the end, TNB, the end, our focus is more on reliability, to deliver our supply in reliable manner to our customers, the offset performance, and also to maintain our asset performance and also to maintain our operational efficiency to our customers in terms of my role, I focus on applying advanced analytics and AI to improve how TNB, especially dn manage our assets, from predictive maintenance, for example, to support better decision making on the ground. And over the past few years, I've been involved in scaling up these capabilities nationwide, in particular for our critical assets, for example, the underground cable that's all for now.

Vanessa Kwan  5:39  
Understand, you know it's clear that your role sits right at the intersection of tradition and transformation also, right? I want to maybe pivot a little bit now into how that transformation translates into business value for the company, for a national utility like TNB in Malaysia, growth isn't just looking at the revenue numbers right for yourself. And Jundi, you mentioned that you are leading analytics for dn distribution network. Maybe. Could you also share how you define growth in your current role, and you know you have had to navigate through the pandemic in the last five years as well. How did that shift? How did that evolution look like for you?

Muhammad Al Jundi Abdullah  6:21  
Okay. Thank you, Vanessa, over the last five years, I would say growth, growth for TNB, especially for disruption network, has really shifted, not only to expand our assets, but more in terms of increase our optimization. Previously, growth would mean building more assets, more coverage, more capital investment. But today, I think it's more about maximizing our performance on what we already have. Yes, the pandemic was really a turning point for us at that time, starting that time, load patterns, the load patterns have become more unpredictable. We really couldn't rely on traditional planning anymore. That has forced us to accelerate the use of data AI analytics. At the same time, we are also also seeing new demand drivers that come along, such as the increase of data centers more, which require more than dynamic forms of energy consumption, also require greater flexibility in terms of our network. So I would say now the growth not really being defined as growth or increase of our assets is more like in terms of to have higher reliability, better asset utilization, and more importantly, to have faster, more informed decision making.

Vanessa Kwan  7:59  
Understand, and you mentioned a little bit about, like, data center, right for our audience as well. There's a lot of conversations now in Malaysia around data center investments. How has that? How much of the growth strategy would you say is driven, like, driven by this kind of external factors, versus, you know, like, maybe your bosses, your board of directors, pushing for digital transformation in your team.

Muhammad Al Jundi Abdullah  8:24  
Okay? In terms of growth strategy, I would say it's more like external factors versus internal factors. It's more like combination of both externally. In terms of external external factors, we are seeing strong drivers, like I mentioned before the data center, growth we're also seeing in terms of electrification, for example, EV charging infrastructure, which are increasing, and also from our consumers, changing demand patterns. When it comes to the energy transition era, increase of solar panels as well. So in terms of internal factors, TNB is pushing for accelerating digital transformation, to have a state where AI can help in terms of asset management decision making, and I would say this combination of both is really important. External demand would create pressure for TNB to increase our capacity, but at the same time, the internal factors or internal capability would determine how effectively we could respond to those external demands.

Vanessa Kwan  9:36  
Understand and what you mentioned is very true, right balancing the external and internal factors as well as you approach digital transformation. You know, last year, when we had the conversation with you and your team, the spotlight was really on underground cables, which won the 2025 AIBP enterprise innovation awards for Malaysia. Could you maybe give us a brief about that particular project? And as you know your focus, she works overhead lines this year, what kind of unique data challenges more specific to your role? And check Jundi, what kind of challenges do these assets present compared to underground?

Muhammad Al Jundi Abdullah  10:16  
Okay, yeah, yeah. Last, last year, we won the award for underground cable project, I would say that at that time, that project was really important for TNB, especially our disruption and work division, because underground cable is really our Main, pinpoint, the main contributing factor to our failures. But as you say, rightly say, just now, Vanessa, now we are not only focusing on underground cable. Now we are moving ahead for our for other asset type, which is the next one, be there, overhead line. So for your information, underground cables and overhead lines are really different type of assets they post. They have a really different data challenges. So as as you know, underground cables are buried underground, so they are hidden. So we really rely on diagnostic data, such as our insulation resistance, our partial discharge is more deep analytics problem understand internal degradation. On the other hand, for our headlines, they are more exposed to the environment. The challenge is not really the lack of data, but in terms of high variation of external factors that can contribute to this weightlike failures. So for example, the factors like weather, weather conditions, vegetation. What I mean here is from the three branches, for example, and also from third party interference. When I say third party really human animals included. Animals can climb monkeys can climb lines, bird can cross our headline, so on. So in a nutshell, I would conclude underground cable we are more predicting failure from our internal signals, but for our headlines, I'll interpret the complex external factors and also in real time. That I would say, the main difference, then one more if I would say this is why, for our weight lines, we are leveraging more in terms of drone inspections, image analytics and also video analytics, because the problem becomes more broader, and I would say more dynamic.

Vanessa Kwan  12:44  
So you basically need more people, whether people or technology on the ground, for you to look after all this exposed overhead, right, understand and when I understand correctly in some of our past conversations, one of your other key mandates as well, and check Jundi is using data analytics hotspots to predict the encounter electricity theft from Bitcoin mining, right? How do you distinguish, I mean, for yourself. How do you distinguish between a legitimate industrial search versus like illegal mining activities through data itself?

Muhammad Al Jundi Abdullah  13:21  
Okay? This an interesting question. Is quite a technical one as well. Okay, to distinguish really, between the industrial search and also illegal Bitcoin mining is not really. We are not focusing on how much the energy consumption or how much energy is being used, but more on how the energy consumption behavior, how it behaves. So we have to clearly differentiate between Bitcoin mining energy consumption behavior and the legitimate industrial search. For example. For example, the Bitcoin mining typically shows a very, I would say, flat continuous load profile. Is a 24/7 operation with minimal variation, whereas the legitimate loads for industry, it follows some some cycles, some fixed operational cycles. So it's a real time based variation or variability. Not only that, we are also looking the power quality signals, like harmonics, customer profile versus the actual usage, and also in terms of location and historical patterns. So the key idea is we are not just detecting how much energy is used or the energy consumption alone, we are also identifying the energy behavior, or the behavioral signatures of energy

Vanessa Kwan  14:51  
understand and in terms of this particular area where you look at right specifically around illegal Bitcoin mining, are there still like challenges right now That for TNB, or even for some of your industry peers, do you think this is like a common challenge that many of our southeast Asia peers are also experiencing right now?

Muhammad Al Jundi Abdullah  15:09  
Yes, I would say yes.

Vanessa Kwan  15:11  
Yeah. Understand. So this is definitely something that is top of mind for many of the utility companies, especially in Southeast Asia. I think moving on to some of the metrics that you look at, right? You know Earlier we spoke about like the underground cables, overhead lines, we spoke quite briefly about the Bitcoin mining being a key issue, a key challenge that many utility companies are facing as well. In your perspective, currently in your role, how do you measure the success of this kind of initiatives, and also, are there specific metrics that you look at when, let's say your product does ask you about the status of these projects.

Muhammad Al Jundi Abdullah  15:55  
Okay, key success factor, I would say this question relies to the how much we measure? How can we measure success? And I would not limit to the project of detecting crypto mining, legal theft alone as a whole. Traditionally, for TNB, especially for distribution network, our key focus, or our KPI, I would say, or rely on the traditional CD, what we call it, system average, interruption, duration index, the ID calculation. But now we are evolving more towards value driven metrics, or impact driven metrics, not in terms of how many minutes of outage we can avoid, but also in terms of the, I would say, for example, prediction accuracy of our solution that leads to actual action. And of course, from this prediction of this or this better decision making to reflect how much cost savings that come along with it, and all how ready for TNB to handle more dynamic and distributed demand patterns that we have now. So for my especially for my team, the most important item one, one of the most key metric is the how many operational operational decision makings that we have actually changed because of the success of our analytics or AI solution, because if the data doesn't really influence our decision making, it really doesn't create value.

Vanessa Kwan  17:40  
Understand so it's really looking at the kind of value that the data insights can provide to the leaders at TNB. Yes, got it. And when it comes to, like, the different kind of projects that your bosses, that your board of director ask you to embark on, will you ever caught in a situation whereby there's, like, say, too many projects, and then you are not sure which ones to focus on, and if you will, how do you usually find a balance between coping with all the projects?

Muhammad Al Jundi Abdullah  18:09  
Yeah, so of course, when it comes to the era of visualization, AI booming. There are a lot of initiative or use cases that come or bloom, which there is why in TNB, we have this governance to this, to ensure the delivery, the initiation and also the delivery of these projects. So when, when, what would say, what we we could say in terms of how we determine whether we want to stop a project or not, for us actually ties back to the value in terms of the practical value. For example, if the projects have shown no clear use case or operational use case. There's one example, maybe the project has high accuracy in terms of prediction, but really no actionable outcome. Also, if there is a data problem, data that cannot be sustained or scaled. And the most important thing is, I would say, whenever the initiative have has lack of trust or lack of confidence from our end users. For me, that's the biggest factor, because if the field team or the operational users doesn't trust or use the solution, for us, the project has already failed.

Vanessa Kwan  19:39  
Okay, okay, understand and when it comes to like balancing innovation again, some of the risk, right? One of the common conversations now that we are seeing across the region is, how do you balance the speed of AI implementation, AI rollout, versus certain governance guardrails, cybersecurity guardrails for the team at TNB is this also under the AI governance council, and how do you usually evaluate or find a balance between the two? Do you work together with, like the cyber security teams, the AI governance teams as well?

Muhammad Al Jundi Abdullah  20:15  
Yes, rightly say Vanessa. So in terms of governance, like I said just now, the most important thing to consider when you are evaluating a project, whether it will be carried out or not. One thing, the most important thing is the value that comes from that and in that governance that we have, we have multiple committee members that come from various backgrounds, technical it cyber security as well. So all of this aspect has been included and meticulously evaluated for each project that comes to that governance

Vanessa Kwan  20:58  
understand and for you personally, right? Anjik Jundi, how do you feel or like, When is your moment that you know that some of the projects, some of the initiatives, to you is a success? Is there like a specific eureka moment? I would say that you feel, that you experience, or when is it that you know that it's a success?

Muhammad Al Jundi Abdullah  21:19  
Okay, there's a skin question. So if you ask me personally, is innovation or innovation is really a eureka moment for me, I will say no. For me, innovation is not really, is not only about discovery, it's most important, the more important thing is about the adoption or the application. For me, innovation happens when, for example, our solution would flag a risk, or AI solution can detect any anomaly, and whenever someone on the ground changes their decision or action because of the AI or solution insights, I think that is the moment of the Eureka for me, the real world impact. That's the innovation for me,

Vanessa Kwan  22:16  
understand so really looking at like the business value, the impact, the outcomes that your AI insights can drive for the business. La, Yes, correct. Okay, got it. You know, we've spoken quite a lot about, like the different machine, the models that you are looking at, but at the end of the day, there are also people on the field interacting with these assets every day, right? You know, we mentioned before in some of our earlier conversations that you are currently brushing up, AI for work management. Maybe, can we dive a little bit deeper into that? You know, there's a lot of conversations now also around AI replacing the workforce, AI complementing the workforce. So what's your take on that, and how is TNB approaching it?

Muhammad Al Jundi Abdullah  23:00  
Yeah, that is a really common questions that we have, especially in our industry, are we going to be like a Terminator, like replace a human being? I think I would say in this, for this context, when we say that does, how does putting an AI really change the human involvement, or how we say the the change of human to asset relationship when AI is coming in. I think that is a big transformation. Previously, our decision making, our decision really relied on, heavily on our experience of our technician, field field technician or field engineers, and our standard procedures. Now, when AI is coming into the picture, AI can act as, for example, the real time assistant. Whenever this happens, this will lead to, for me, this will lead to more consistent execution. We can reduce variation. We can standardize our action, of course, and also we will have better with AI. We would have better quality control. It also allows us to capture and standardize knowledge across all levels of our teams. So for us, the relationship between human AI would evolve from previously, from human only, from human to asset. Now, human and AI working together on the asset. And as I would like to say, My leader, my management, our chief, Senior Network officer, always said whenever AI coming to the place, we would treat AI to enhance human intelligence. So the term AI to elevate IA intelligence augmentation of human so that's what we are currently moving towards to.

Vanessa Kwan  25:01  
Thank you very much for sharing antique Jundi. And I think I want to go back to where we started off, right. We introduced you as like a technologist, as an engineer. And sometimes I hear that engineers like to say they often hear or sense a thought before they see it, and like something like a sixth sense. And for yourself, you know you spoke briefly about Intelligent Automation. We spoke about AI human but for you, in your data models, in the work around AI that you are dabbling in, are you trying to also digitalize that human intuition, and you know, in conversations also with, like some of your regional utility players, they would say that the goal is not really for AI to replace, but rather is to complement the human element. What's your take on that? And do you think that humans will really be replaced by AI?

Muhammad Al Jundi Abdullah  25:57  
No, no, I would say, like I said before, human and AI should work together to increase our activity, and also, like I mentioned before, to have better quality control and reduce variation, more consistent execution. And I would say, since in industry like power utility workloads and work work orders, for example, coming from various workloads are huge. People needs, our workers needs to multiply their efforts daily to execute all those tasks, and with AI, for example, to have a better prediction that we have now, we would really save or we have, can have a targeted task or targeted executions, and would really reduce unnecessary tasks or works that we previously would do that. So I think that where AI actually come into assistance in terms of human workloads, not really replacing them, but to assist them and to augment their intelligence in every task that they have they are doing in the field.

Vanessa Kwan  27:21  
Understand. Thank you, and check Jundi for sharing. And you know, for some of our audience who are listening as well, if they wanted to drive growth through technology, where do you suggest they start from? Should it be from? Like the data fundamentals? You know, we hear one of the biggest challenges in AI implementation is that the data they have is very messy. Right at the end of the day, it's also like garbage in, garbage out. So how do you like? What kind of advice would you give to leaders who are starting to embark on their AI journey, and how big of a role does data play in it?

Muhammad Al Jundi Abdullah  27:57  
Yes, for me, start with people. Always start with people, because if for data, yes, of course, data without context can be misleading. But this the field teams, the users, the people that they really they are the ones who really understand the real asset behavior and constraint. So for for me personally, I would say my advice is to start with real operational problems, translate them into data use cases. Then from there, we would apply analytics or AI. So the best solutions come from the real pinpoints on the ground, from the people, from the users, not always from the data set data sets, that would be my advice.

Vanessa Kwan  28:48  
So to always start with the people in mind, yes, understand. And for yourself, where do you see the energy industry in the next five years, broadly, you can address it any way you'd like. And then, more specifically, also when it comes to AI applications, are there certain business use cases or like problem sets that you're looking to achieve in the next five years?

Muhammad Al Jundi Abdullah  29:15  
Okay, in the next five years, the energy industry? Why would I where I see, where do I see the energy industry in five years, is it the grid will become truly self healing? I would say we are definitely moving towards that. We are definitely moving towards more intelligent and I would say autonomous networks. In the next five years we would, we would see some improvement in terms of like self diagnosing systems or of networks, maybe increase of automated fault or failure is isolation and definitely faster Power restoration. But at the same time, we we must admit that the grid will become more complex. With this complexity, we will have more dynamic demand, and, of course, will be more we will have more distributed energy behavior. So I would say in the next five years, we will reach a state where this grid will be self aware first, before we shift a fully self healing one,

Vanessa Kwan  30:33  
okay, and from a wider perspective, also, when you Look outside the energy industry, within the technology space, this is one question that we end up for all our podcast guests as well, what excites you the most, or if I can ask it slightly differently, what keeps You up awake at night?

Muhammad Al Jundi Abdullah  30:57  
So again, is the application, whenever the application that we develop is being used and being applied consistently and making a real impact and value, that is where I truly will be truly feel appreciate, and also feel really, what may, what really May, really wake up at night. I mean, still in terms of value coming from that, understand.

Vanessa Kwan  31:36  
Thank you very much, Jundi, and it's very interesting to hear your perspectives on the invisible architect, and for sharing how TNB is balancing high tech innovation with AI with data analytics against the very physical realities of partner nation. You know, we spoke about the underground cables over headlines. We spoke very briefly about illegal Bitcoin mining activities as well. It's been great having you on the ASEAN B to B growth podcast with us today, and as TNB skills and grows in the coming years, certainly look forward more to some of the innovations that you are leading with the team, and definitely keep you more on your toes, I guess, with a lot of the other new and emerging technologies coming in. Thank you for joining us today and take Jundi.

Muhammad Al Jundi Abdullah  32:24  
Thank you Vanessa. Thank you AIB for having for having me on the podcast. Thank you very much. Thank you.

Vanessa Kwan  32:31  
Okay, I think that's all from us. Good timing when your call came. Yeah. Yeah. Can that one should be okay. LA, I think the recording itself is fine, so we will edit it. And I think the final episode would be between 27 to 30 minutes, so not too bad. Do you need us to share with you a copy before we publish it? Or do you think it's okay?

Muhammad Al Jundi Abdullah  32:59  
We can? I think you can. You can go ahead. It's just that the you try to cut something young, not really smooth, Saturday, for example. I think the last step caught me off guard because of the call, yeah,

Vanessa Kwan  33:17  
no problem. Just the ending, okay.

Muhammad Al Jundi Abdullah  33:22  
And then, like my corporate convention they want, they want TNB to be, I mean, to collaborate with any posting that you want. You will do, yeah, make sure how you will you're going to post them like social media, or,

Vanessa Kwan  33:39  
yeah, social media. So usually we post on LinkedIn, we post on YouTube, also like the video format, and then, because this one, we publish it on a podcast platform, right? So it will distribute onto Spotify Apple Music and all of that. So from your corporate comm side, right? Do they have, like, a TNB blog that we can use? Then maybe we can put that into the description also of the episode, like maybe one two liner, like TNB. What is TNB? Market cap, asset size, those kind of things, I think, like a boilerplate.

Muhammad Al Jundi Abdullah  34:12  
But it's better if you can email me the thing that you want, then I would forward to my corporate comm for them to

Vanessa Kwan  34:18  
provide to you. Okay, can also, or if easier you I send you an email after this, then you want to add them in and I can liars with them also.

Muhammad Al Jundi Abdullah  34:26  
Can, yes, I will add the person in charge.

Vanessa Kwan  34:31  
Ah, can. Then I think the editing should be okay. La, then, usually the social media posts, we will tag you. We will tag TNB also. But let's say TNB want to do their own promotional stuff, like they post on TNB platform. You can let me know, so then we can share the edited files with them, maybe a bit bigger so that one, maybe we can coordinate with them how to send it across. Maybe need like zip file, or like Google Drive or something.

Muhammad Al Jundi Abdullah  35:01  
Yeah, I think they would want to do that as well. So better after this, I can connect you with that person in charge. Then we'll discuss more from there.

Vanessa Kwan  35:13  
No problem. Okay, so I will just leave a note to remove the ending part, and then also I will sync up with your cop comes once you

Muhammad Al Jundi Abdullah  35:24  
put us together, yeah, remove the last question where you ask me awake at night. Thank you. Thank you.

Vanessa Kwan  35:36  
Okay, okay, I think that's all anything you just let me know again. Okay, Vanessa, thank you very much. Thank you, Auntie Jundi, bye,

Muhammad Al Jundi Abdullah  35:42  
bye, you soon, bye, bye.

Transcribed by https://otter.ai