PegaWorld 2025: AI-Driven Smart Cities & Compliance: MOMAH & Aaseya’s Journey in Inspections, CRM, and Urban Transformation

PegaWorld 2025: AI-Driven Smart Cities and Compliance – MOMRAH & Aaseyaʼs Journey

For smart cities in Saudi Arabia. And we have implemented AI solutions at a national scale to increase the productivity and the efficiency in inspection, compliance and citizen services across all the municipalities in Saudi Arabia. So while other cities in the world are still exploring the idea of digital transformation, Saudi Arabia actually is ranked fourth globally in the UN 2024 for e- government Development Index, which reflects our national commitment to digital excellence. So today I'm not going to talk about the automation, but moving from automation to autonomy, because it's not only about the technology, it's not only about digitizing the processes or digitizing the workflows, but also to change the way we think to rethink how government sectors or private sector should serve people intelligently, proactively and with purpose. So allow me today to take you through the journey where we put AI into work to increase our efficiency in operation and business and decision making. This is who we are. We were taught to stay in our lane and to know right from wrong. We were taught to slow down and be patient, because a bump in the road isn't the end of the road when the way is blocked. We don't stop but look for what's next. We were taught that to truly know a place, you have to know it from the inside too. Since the start, we found our way. Our way. Building next generation local maps and more. Nobody knows Saudi like Baladi. So Baladi actually is an Arabic word for my city. And that's our main focus, is to connect people to the city through providing map and navigation services, lifestyle and day to day activities so people would be connected to the city through our super app, which is Baladi. Plus we have strategic focus on growth optimization, increase the citizen satisfaction and sustainability. So in the in the first section, I will celebrate the success by giving you a recap of what happened from 2021 until 2024. When it comes to inspection and compliance. So we had three main pillars of transformation. We started in 2021 by thinking of digitizing the inspection in Saudi Arabia. So we used to we used to have different inspection systems for each municipality. They they have their own system. They do inspections. Actually we are we are good in doing inspection and compliance since the beginning. So the idea in 2021 was to digitize the process, to unify the process for the users and citizen to to have the same experience in every city, the same complete value chain in one system. So if you talk about the field survey, if you talk about reviewing the visit and approving the visit, issuing the fines, informing the establishment owner, and also give the right to appeal or to object to the to the visit, let's say results all in one system that has to be used by all the municipalities in Saudi Arabia. That was the goal in 2020, 2021. And we accomplished that after that. As I said, it's not about digitizing. It's not about the technology we need. We need to enhance and increase the productivity by eliminating the human intervention and saving effort and time of people by utilizing AI. So when you say we use AI, we're just not using AI to for the like, say for the sake of using AI. No, but how do you use AI to help people and not to replace them? So we embedded AI solutions into the inspection to increase the productivity and to save time and effort for the inspectors, for them to focus on, on, on other things to do. So did we stop there? No. We want to be more productive.

We want to be more smart. So we moved to the city management system, which is how to manage the system, how to manage the city completely through AI. So it's not only about eliminating the time or saving the effort, but also how do you use AI to find the hidden value in data? So you have automated systems. Maybe you have a couple of systems that has complete value chain in each system, but they're not talking to each other. So using AI to connect the dots is what we're planning to do. And what we we're working on in 2024 and 2025. So if we want to talk about the transformation impact by numbers, we're talking about 600 million US dollar revenues since 2021. We're activating the system in 70 municipalities across the whole kingdom. We have more than 6000 users that are using the compliance platform as we speak. And we reduced the processing time by 67% just by implementing AI in the right places. If we talk from operational excellence perspective, we reduced the human dependency by 82%. We increased the geographical coverage every month by 12 x. We used to cover the priority areas in the city and reach 11%. After we implemented AI to do the computer visioning and to do the scanning and using satellite images do the change detection. And so we increased that by 12 more. And also we reduced the expenses by 60 by 76%. We are saving 150 million riyal every year by just utilizing AI in the right place. So from automated to autonomous, what do I mean by that? So in 2021 we did the digital transformation. We built the inspection platform, which we call it. It means compliant. It's an Arabic word. Then we enhanced and adopt the technology in 2022 2023, 2024. Was the AI implementation in 2025? We're moving to autonomous operation. So what's the difference between the two? Automated system. It's a predefined patterns because you created the workflow and you're expecting the system to to go with the workflow. So it's a rule based. But with autonomous system we want the machine to think. We want the machine to find the problems, to find the bottleneck and to generate decisions, to generate actions. So the main idea is to transfer the data to insight and transfer that insight for the decision makers to transfer it as actions at the end. I'll give you an example. So we used to do a field survey to find all the issues regarding the construction. Are they following the building code? Are they following the regulation when it comes to issuing licenses and so on. So doing a field survey is not is not sufficient. You cannot do this unless you will continue like hiring people, which is not that which is not the right solution. So if you have, let's say, a satellite image for the kingdom, then you use AI to detect the change. Then you know if something happened and you have your own data to validate with. There are construction in that area and there is no license because you own the data, you have the data. So you know there is an issue there. So the system can detect the change automatically issue a case, automatically assign it to inspector to go on the field and visit and make sure that everything is is compliant and the license is there. So when we did this, we detected number of buildings without a license. Then we did the field survey just to confirm the accuracy, and the accuracy was 94%. So imagine that thousands of cases was assigned automatically with zero human intervention by depending on AI. So this is what I

mean by autonomous system. OK number of use cases that we we worked for is the optimizing the route for for the inspectors according to their daily, uh, let's say, schedule or daily tasks. Predictive violation detection. The unlicensed building activity is one of the examples that we're working on. And it's not only construction, it's excavation. It's it's a construction waste. The green area, anything that can be detected through AI, we will not use human for that. It's about the the remote sensing that we're looking for and that we're implementing now. So having this huge amount of data and these systems that are automated and talking to each other helped us to come up with something that we call a city view for the top management. So City View is a new analytical platform that helps the decision makers to know what's going on in the city in real time, so they know about everything in the city the contracts, the the inspectors, the compliance, the even for the investment, for the assets in the city. They know, because we do have a fresh scan on all the cities in Saudi Arabia every month. And not only we're not only showing data to the management, but we're using AI to generate insights for them to support taking the right decision, how to run the city and how to operate the city. So City View can be used by the minister. Can be used by the mayor. Can be used by the decision maker to have the right insights that would support to take decision. It does remote sensing. It does generate automated alert. It does generate automated tasks for the people to go on the ground and check it, and it will be reflected back as an update on the city view. So Pega Blueprint. I think you've attended sessions. Everyone is talking about it, so I will not go and define or give you introduction about Pega Blueprint because you know about it. But I will give you the impact on melody when we use the melody, when we use the the Blueprint. So 70% faster application development cycle, which also helped us to increase the stakeholder satisfaction by 40%. Because, you know, we're developing a lot of things like 70% is is huge, right? 85% reduction in the requirement misalignment because you are depending on the AI logic there when you write the requirements. 60% decrease in the compliance related delays. Moving to process AI intelligent operation. So again what do we mean by that? We want the engine. We want the machine to think and generate insights that help us to do the inspection proactively. So the idea is not to react to an incident that happened. We want you to be proactive to prevent from incident, to prevent the incident from happening, because you have an eye on the Citi and you know what's going on. So it will help you to direct your contractors. It will help you to direct your inspectors. And we're not expecting you to do this manually because it's also automated in the system. Like you don't have to go and assign inspectors for specific use case because we have a risk based engine, for example, for establishment, you know, we have more than 600,000 establishments in Saudi Arabia, so it's not logical for me to say that I will visit them all with the same period, period, let's say frequency. So we created AI tool to predict the risk. So we like depend on on so many, let's say so many entries here. For example Google reviews or poisoning, let's say events or depending on historical

information for the last three visits or last seven visits of the of the establishment. So if this establishment tend to have certain violation, the engine will give it a high risk. Then it will be automatically assigned to one of the inspectors. If the establishment is doing fine, they are compliant. The Google reviews are good, there are no poisoning and this is just an example. Then you need to prioritize another establishment to visit. We cannot do this if we just take the data and try to do it by ourselves. But I can provide that. So again examples. We used it for inspection time estimation objection resolution. We used it also to predict the SLA delays and do automatic let's say reassigning to avoid the breaching the SLA and the results. We had 40% reduction in inspection review time 80%. 80% accuracy in violation. Violation. Okay. Sorry. 80% accuracy in the assessment predictions. 25. Improvement in resource utilization and 65 improvement in SLA compliance. So the future. We will not stop here. And we have many ideas that will be transferred to real products in the near future. But we want to focus on how to use Pega features to continue our journey. For example, Pega Process Mining. Because we did Process Mining ourselves, we injected a tool to do process mining in CRM because we used Pega for CRM, so it helped us to find the hidden bottlenecks in the process. So if you receive a case, then it goes to the supervisor, then it will be assigned to a contractor to deal with. Then the contractor will deal with it. It will send it to the quality team to check it. So we know the process, but we cannot find where is the mistake, where are we breaching the SLA? What are the area of weaknesses that the users can use to reset the SLA, for example. So using Process Mining, actually we found many, many hidden bottlenecks and hidden like let's say broken process that help us to enhance in the system. So if we have it in Pega embedded in the system, that would help us tremendously. GenAI intelligent assistant at every level is something that we are willing to explore with Aaseya team to implement in our systems. So Pega, Agentic, AI, and MCP, we are expecting these features to increase the time of development to to find the hidden, let's say, bottlenecks and drawbacks in the processes and the workflows to help the decision making by providing the right insights for us to take the right decision. So, as you can see, finally, our journey shows how AI can enable not only efficient governance but proactive, citizen centric cities. Thank you so much. If you allow me to invite Hema and Lukasz to the stage for us to have any questions that you have. Yes. All right. So this was indeed very exciting. To be honest, I think more than what I was hoping for, I could see there is a lot, right? And I'm sure it's very satisfying for you, as well as a proficient professional as an individual to work on something like this, which creates huge outcome for your citizen in general. Congratulations once again for the successful work. I think we are now open for a few questions and answers, and anybody who thinks they have a question, uh, you can use either of these mics and you can come here. Uh, Sarah will be joined by a few colleagues of ours from RCA, uh, to support, uh, answering a few questions if you have. But before we go, Sarah, let me ask something which may not be very, uh, you know, convenient, but, you know, I love Aaseya.

We love Aaseya and Pega. Uh, how had been your experience of working with RCA in this journey? What has been some of your key takeaways? Listen, you cannot gain success individually if you don't have the right team, if you don't have the right partner, if you don't have the right vendor, you wouldn't be able to accomplish all of this. So this is not like one person job. It was tremendous hours and hours, like hundreds of thousands of man hours to accomplish whatever you saw today. And Aaseya was part of the journey since the beginning. Wonderful. Good to hear that. Uh, any other question from the audience? Uh, hello. Hello. I'm from the Netherlands, responsible for the Dutch government. Can you elaborate more on the impacts from an organizational perspective, how you help them to move into this transformation to the effect that you have right now? Okay. So for us, if we talk about organizational, last year when I was here, I was telling everyone that we are hoping to move this platform to be a national platform, which we accomplished in December 1st, 2024. We became a national platform. Thank you. So we're serving more organization, but let me take the municipalities as an example. So if you're on the city or if you operate the city, what do you need to know? You need fresh data. Fresh scan and giving the data is not enough. So you need to provide them with the data, the insight and what the what they should do as an action. So when we provided that we increase their productivity. They run the city proactively. They know how to, let's say put the resources, the assets, the maintenance, the contractors and so on. So providing the data in that format help them to run the city in a better and efficient way. If you don't have any other questions, we might go to lunch early. That's fine. Thank you so much.