2027 Leadership for Enterprise Architects : What Changes ? | Architecting the Inner Transformation

So welcome, welcome, welcome everyone. So let's get started today's webinar. So before we start, from which city and which organization you are joining from, just type it out in the chat. Or if you're watching from the YouTube, in the comment section you can note it down that from which city, from which location you are joining from, and welcome to our today's webinar entitled 2027 Leadership for Enterprise Architects and what are the challenges, what are the changes which is going to happen. That is something we are going to talk about. So let me present my presentation, so slides here, so let me share my screen and we will be going from here. So we will spotlight this, presentation. So let's tell that. Okay, so here what I notice, you might be wondering, we are still having 4 months for 2027, right? But still, why we are starting early, right? So you might be wondering, also there are roadmaps happening from people are already having started the roadmap, people who are especially in enterprise architect, strategy team, and all. They have already started those activities exclusively for roadmap activity, product roadmap. It could be strategy, it could be anything, right? So why not then leadership, right? So they have to be also be particular about this. At today's topic, we'll be focusing on that side of it. 2027 leadership for enterprise architects. What changes is going to happen in this AI era, right? So in this note, as we speak, as I say, Today, most of the enterprises treat the AI as a shiny playground, shiny, you know, that's like everybody is doing, so I am also doing it, right? Isn't it? Many a times I also feel that that is what exactly there's a competing rather than the value-driven. So very few, and also you might have seen a lot of pilot projects, it doesn't go to the actual production, okay? And what does it take to the production? That's a different strategy. And as I said, based on the reports, based on different research, okay, the different reports they are saying, okay, 90— 80 to 90% of the projects fails, okay, are just after the prototype. Prototype is very shiny, you know, it should be very good, but when it comes to the actual thing, it is not, okay. So technology is the entire piece of the puzzle, is just one of the layer, right? The entire of the architecture. By the end of this today's sessions, today we'll be looking at You will be having an entire end-to-end, you know, a complete battle-tested enterprise architecture blueprint which will be connecting to your business capability with your clean core. Clean core is exactly— we're coming from an SAP side of it, so we'll be touching upon— although we are technology agnostic, product agnostic, but primarily I have learned a lot from SAP side of it when it comes to clean core philosophy, that their North Star architecture, if you have seen that, right? And also autonomous AI agents, what is coming up. So now we will be seeing that how exactly these things are happening in this era. Okay, so marketing leadership for the AI-driven enterprise point of view. So now with that note, we will be going moving ahead. The next part is we'll be talking about, uh, here let's In 2026-2027, people will be no more looking only for the AI demos. Enough of enough demos. People have seen the demos for a couple of years, so now no more demos, show some reality. Okay, so that is what exactly even most of the corporates they are now emphasizing in. So we have to see the reality, not the demo only, right? And that requires a decent architecture, decent, you know, all those things are required. And though core enterprise fixture, whatever we have seen, it is, uh, most challenges is the leadership, okay? And it's a mixed response is coming from the industries as well as we progress, as this entire journey goes beyond that. So it was typically, if you might have seen, if you have observed it also, Coordinating people, tasks, and processes within defined hierarchies. Okay, from management it is moving towards the decisions. Okay, we have to take individual judgment calls made by leaders in real-time decisions. And lack of architectural alignment. So if there is a lack of architectural alignment between all of your teams, whether it's a strategy and architecture and all of these things, if it is also from a strategic reasoning point of view, and human teams and autonomous AI system, if there is a There's a proper alignment required among all of these things, okay? And in this entire thing, whatever we are doing for— so your core systems and if your AI experiment, these are decoupled. If you are seeing that, right, you don't have a transformation, right? So you have to have those core systems and AI experiments talking to each other. There should be aligned, there's a proper alignment, okay? So you might be having a lot of spent, okay, expense already have done it, invested already. But now we have to also examine the clean core. Clean core should be the key thing, and the architecture also should follow the clean core mechanism so that you can unleash the high-value AI in this, uh, and also at the same time mitigate the entire compliance-related issues, any kind of data-related data leakage risk point of view, okay. So those things are really, you can do it. Okay, so now as we are saying, so we are moving towards a section. So basically we're talking about from a team's point of view also, human-only groups executing defined responsibilities. So there's a human in the loop always, and we are not again talking about any particular AI product here. We're talking about entire AI ecosystems. Okay, we have to think about ecosystem architecture, ecosystem approach we have to take here, and we are saying that is the human plus AI ecosystem. Systems. We are not particular about any AI product or any AI features, okay? So that is what exactly we have to think about. So most effective leaders, they will not be those who manage the most people, rather who architect the most intelligent, autonomous, and adaptive operating systems. So that is the keyword here— you have to adapt, okay? And also we must examine our entire thing end to end. Okay, so this is what exactly we have to think about it in this entire journey, and when it comes to the leadership in 2027 from an EA perspective, from an enterprise architecture perspective, that is the highlight here. Okay, so now with that, so let's move on. Okay, so now we are seeing here as Can enterprise architects lead AI transformation or they only will be designing? So this part we will be going a little bit depth here. So we would like to understand in this particular segment, many times people forget about the business architecture. So before, nowadays SAP also talks about— I have seen a lot of programs and a lot of attendance, couple of sessions, something there's a concept of the intent-driven Programming, right? You might have heard about it. And also now it is not only SAP but any other product-based companies, and they are also moving in that direction. So you will be finding called as intent-based development. Intent-based development, you can— you'll be finding something like that, okay? Mostly SAP has popularized it here, but you will be finding more of, you know, AI transformation, intent-based development. So this is what exactly You know, people are more focusing here. Intent capture, entire thing, you can see that intent-based everything, okay? And they are doing, look, looking for that only, okay? So this is the entire thing, intent-based development for, uh, creating and running AI agents. So there's a blog also you'll be finding here, very similar. So it all tells the same thing. Okay, these are all intent-based development. So this is nothing new now, it has been very popular. What should be your intent? You should be understanding before write any of the code. And also it will be, uh, it is nothing new again. So you have to must anchor the business capability, the business architecture side of it. Many times people ignore that segment of it, business architecture of it. And always look at your, whenever it comes to the capability heat map, so always look at your level 1, level 2 capabilities whenever you're starting with. And also check for the entire critical bottleneck. What are the bottlenecks you are having in the entire process? And where is the— in this entire journey, journey map also, you will check where is the human workflow is getting stalled. Okay, so in this entire journey, we have to decouple your entire business capabilities from the underlying technical implementation. So we have to take care of that part of it, and this will allow all the business leaders. So this is the, again, a business point of view. It will be moving all those pieces, it will allow the people to what, okay, what, while architects define the how, okay. So leader will be always deciding here the what part of it, which is again based on business capabilities and all, and architects will define the how part of it. So that is again just an understanding. So define the strategy defined by the enterprise It will be going there and it must go and why it matters. Then architecture will design the capabilities, systems, and flows that make it possible. And leadership will be orchestrating that entire thing— people, AI, and governance— to bring it to life. Okay, so we have to have a— only technology systems will not be enough. So we have to also having become architects of any kind of a decision-making you are doing it, right? So that should be also properly Done. So this is what exactly we expect from leaders in 2027 and beyond, right? So that is what exactly, okay, it will be helping you to define the how part of it. And also we have to align with the customer outcome. We already talked about intent-based development. At the same time, we will be looking for an outcome. We are not looking for features. This, this product having 10 features, that product having 20 features. Rather, we will be looking for an outcome. What is the outcome we are getting out of it? So that should be the priority. Okay, so this segment we already talked about that strategy, architecture, and leadership, how they will be aligning and they will be orchestrating the people, AI, and the entire governance structure of it, of an organization, to proceed ahead. Okay, so now in your organization, so let's have a prompt like which capability in your enterprise is काम से काफी ज़्यादा ऑपरेशनल डेले। ओके, सो यू मेड बी समबडी सेइंग आईटी, समबडी सेइंग एचआर, समबडी सेइंग समथिंग एल्स। सो व्हाट डू यू थिंक? दिस इज़ जस्ट अ पॉप क्विज़ फॉर यू, दिस इज़ जस्ट क्विज़ फॉर यू। सो व्हाट डू यू थिंक? व्हिच इज़ योर की थिंग व्हिच इज़ लैकिंग, राइट? सो यू क In your enterprise, it is causing the greatest operational delay. So there are operational delays happening right everywhere. It could be anything. It could be any right. So from your experience, okay, we are not pinpointing a particular department's good or bad. Rather, we are saying or capability. We are saying which is causing the maximum delay and why. Okay, and what can be done? Okay, for to eliminate that. Right. So you just think about it and put down. You put those. And I'll be reading each and every comments whenever you're watching this. And yeah, so that is what exactly I just thought of sharing with all of you. The next part is 2027. So when it comes to 2027, so why it should be different? Okay, so also you like to understand that why 2027 will be different. So we'll be moving here, here in this context, because every era has introduced different thing. Okay, so when we go here and 2024, it is all about the Copilot. We talked about AI assistant, humans with suggestions, draft and surface-level analysis we have done. 2025, a lot of AI platform came into picture. Intelligence is connected. Previously intelligence not that much across the system data and business functions. We have seen that. Now the next part is we have to 2026 currently a lot of AI agents. Okay, if you have seen the Discovery Center, from SAP perspective, there are 400+ AI agents across. Okay, so if you go there, Discovery Center SAP, okay, or any other marketplace, you will be finding a lot of AI agents. Discovery Center, if you go there, you'll be finding same. Go with your ServiceNow also. If you see ServiceNow AI agents, okay, in their library, again they have a marketplace. Okay, so Salesforce, ServiceNow, all leading products in the market, they have their list of agents. Okay, so you'll be finding in their marketplace a lot of AI agents coming up. Okay, it's already up and running and people are again exploring a lot, right? So these are the 400+ I was saying, right? So, so many agents, so many assistants you'll be finding in this case. Right? And, uh, you'll be finding all the things here, right? So there are agents, assistants, lot many are there, okay? You will be finding so and so. Similarly, if you go for any other products, you can search for it. ServiceNow AI Control Tower, they're having AI platform everywhere, AI, okay? You can see that AI platform capabilities, all of these things, okay? So now what is the the outcome. So yeah, now AI agents are in 2026, they are executing the entire workflow with increasing the autonomy. So that is what exactly we have learned. Okay, so 2027 will be the true, you know, test for a real autonomous enterprise. Okay, already SAP has announced and many other organizations also, we are targeting, we are becoming autonomous enterprise, but how sooner or how, you know, better. We will be the time will tell. So now in autonomous enterprise, what will happen? Multi-agent system. So agents will be calling to each other, talking to each other. They will coordinating and they will take their decisions across the entire enterprise. Definitely human in the loop is will be out there, but this is what exactly expecting. So 2024 to 2027. So this is what exactly we are talking about. Now we have whenever moving to this. So we have in this context. It is not fixing a broken operating model. Okay, if your operating model itself is broken, it will not going to fix. Okay, so idea is here what exactly we are going to do in this thing. Definitely there are AI experiments where their data silos are there in organizations, fragmented data, it cannot be trusted. So you have to ensure the data silos is gone. Okay, an application's point of view, if you're having a lot of applications, they are disconnected with each other. And there are overlapping logics, right? So we have to ensure those are— those things AI will not be fixing it, so you have to fix it yourself, okay, before you implement AI at a scale. Similarly, from process point of view, people do not know how many processes are they still doing running manual. I'm not talking about small companies, bigger companies, medium-sized companies, they also have a lot of processes which is still manual legacy. And that requires modernization. It is still inconsistent, very difficult to govern also, right? And still it is going on. So those things are also to be fixed. And people, their overall decisions, AI should be supporting. So this is also required in this segment, right? And whenever I'm saying disconnected AI, if it will always give you a disconnected— garbage in, garbage out, right? So if you are having a layering in AI which is a fragmented model, definitely it will be amplifying your dysfunctions, definitely. Okay, it will not solve any of your problem. Okay, so in this era, so definitely in this segment, definitely EA must fix that architecture, then introducing intelligence. So first fix the architecture, then inject the intelligence into it. That is what exactly I can say, right? So if you may invest because other XYZ companies are investing in AI tooling, right? So before do that, you have always ask yourself Really, do you have a coherent operating model which that AI can enhance? If the answer is no, do not go for that. Okay, so take a pause in all of your investments, okay, and you just check it out whether your technology, what are the things is actually not working and all these things, you just to fix that first, then you inject or introduce the intelligence of AI into it, right? So it's very basic, go Go back to your basics, okay? Before you start with AI and all of these things, check your data quality, check your applications connectedness, check your processes, how consistent and coherent they are. Check with your people, right? So you need their support, their inputs, okay? Human in the loop, okay? So then only you can go for the next stage, okay? So the new mandate for any of the enterprise architects is role of— their role is not being eliminated, by AI, but rather you are having to be elevated. It is common for every other jobs as well. So all the tactical, all the operational things are slowly getting eliminated, and it is now being elevated to a next level. So the scope is shifting from designing a system to orchestrating the transformation across business technology intelligence layer. Are you able to orchestrate as an architect, right? So that is what exactly the new mandate for the new era, the new year. So traditionally we have been doing architectural governance, technology alignment, system architecture, all those high-level design, low-level design discussions, ARBs, standards, frameworks, roadmaps, whatnot. Okay, human processes, a lot of things we are doing it. Now with this AI 2077 onwards, what exactly will be adding on? So we have to think about transformation first, outcome first. We have to do a transformation orchestration. So you are going to play a role of orchestration, orchestrator, right? Business and AI should be in alignment. So there should not be different, 2 different doors, 2 different paths. Rather, they should be aligned from day one. And there should be a, instead of system architecture, you have to take a decision architecture. So you will not be having those kind of, I know there are organizations still doing the templates, go paperless architecture, but at the same time, the decisions should be based on various parameters and should be taken properly. Standards and frameworks will be there, but at the same time we had also talked about guardrails and governance, whether governance is taken care or not. So we have to think about all those areas. Then also continuous evolution, so whatever you are learning today may be not relevant another 2 or 3 weeks because the way the pace is, the speed, the Change is changing, as we say, or okay, whatever it evolving, right? So evolve itself evolving, right? Your change is changing, we are saying, right? So human plus AI workflows should be there at the same place. A continuous learning for everyone, continuous, you know, lifelong learning, as we say in our learning platform as well. So we have to have that spirit of learning, okay? So now, uh, in your— I have a question for all of you once again so that In the chat, you can put it here. So does your organization currently enforce strict clean core principles for your enterprise extensions or not? Okay, there are, I know there are a lot of custom objects you might be having, custom things you might be having it, right? But are you still having those custom extensions side by side into cloud platforms via event mesh or standard APIs? Or are you still utilizing your, you think about it. So from a Core principles of a clean core point of view, right? That is something we have to talk about here. Now moving on, business architecture. So now we have already have talked a lot about the leadership segment of it, but now we will see how you really apply it. Okay, so most important mistake, most common mistake in AI transformation: people always start with the technology. Okay, never. So even I have seen people start with the technology. This technology, this Gartner Magic Quadrant, this product is doing well, IDC says that product is doing well, the Forrester report is saying that product is doing well, my colleagues, my friends in other companies, they implemented this technology, that technology, you might be wondering. Even the product-driven companies also, they conduct a lot of events, conclave, whatnot, right? So conduct those events to grab those eyeballs and take people influence with the technology, but most successful enterprises, they do not start with the technology, they start with the business-first approach, and they always think the outcomes what they need and then they go beyond that, they go downward through the capabilities, value streams, and processes. If these 3 things are not there, you should not start anything. So before selecting any kind of single tool or platform, the recommendation is Always go back to the basics of your data foundation, your transitional core. What is your core business layer and what are your orchestration layer, experience layer? These are all non-negotiable, right? And clean code is non-negotiable everywhere, okay? And isolate your custom extension into side-by-side cloud platform. You can— if it can be done via different any kind of event mesh or APIs, okay? So that your core system will be driven core, and, uh, it should be always upgradable, definitely. And with your— while your AI models are there as well, so which can access the zero latency enterprises, uh, latency in the context without any kind of a schema, uh, corruption you are having it, right? So in this context, as I say, business architecture is a must. This is the first thing first we have to take care, and we have to always think strategically, vision, okay? Your vision team. So be having that. Then what the business must do well, so you may have 10 different things to do well, 20 different to-do lists in your, but you drill down into 5-7 capabilities, so do not go beyond that, your L1, what the business must do well, what is the core capabilities, so that is what exactly you should be designing your capabilities, should be operating your capabilities, then how value actually Flowing to the customer, right? We always talk about that value streams, right? So how value flows to the customers across whenever you are starting with a journey like this, then comes your process and technology. So where actually you can apply your AI tools and all those things you can do, right? So this is the critical bridge, the business capability critical bridge between your strategic intent. As I say, we always start with intent and to architectural decisions. Whenever you're taking any architectural decisions. And we have to ensure AI is actually deployed wherever it's creating any value. So without value, don't go for anything whichever is people even if there is a market trend, okay? So always focus on your business side of it, your vision, your strategy goals, your capabilities, your value streams. Then you go for the process and technology, okay? So in this case, we have to understood the business capability layer is the bridge between that your translate your strategic intent at the top whatever you are having. To your architectural decisions, okay, and ensure AI is deployed in between, and it is then only to create the magic, whatever you are thinking about it, isn't it, right? So now you think about it, uh, so did you design a business capability in your organization? If no, go back to drawing board, create your business capability first, okay, not in paper, rather in a tool, and there are so many tools available, and you can start with that that if you're a RISE customer in SAP focusing, and you will be having those details also in the capabilities map and everything, you will be having definitely, right? So those capabilities you need to focus, business outcome, intent-based value streams, process and technology. Then we comes to your tools, technologies, tactics and paths. So that is what exactly we expect here. So now let's go to the next segment. So we will come to the next segment part of it. The five layer architecture which we are talking about here, we will start with every AI ready enterprise. Okay, is built on five interconnected layers. So weakness, if you are having any one layer is not properly functioning, it will be impacting the entire ecosystem, entire system you're focusing, right? So for any of the AI ready enterprises, we are saying that. Okay, so we will be having this. 4, 5 layers. Okay, so it starts with the strategy, and if you go from bottom to top, strategy, you are having vision, outcomes, KPIs, your key performance indicator. Then you must be having a business model and operating model. Both are different, by the way. So what is the difference between business operating— business model and operating model? You just note down. Okay, just check it out. Okay, it's a homework for all of you. And here we talk about the capabilities, the how part of it— sorry, the what part of it. The process is all about how, the capability, business capability is all about what. So value streams, accountability, all those things we talk about here. From a data applications point of view, we have enterprise data applications, API and everything. AI and agents, we are having a model, we have agents executing workflows. And the top, last but not the least, we have your typically risk, security, compliance, and human oversight point of view. So those things also we have to understand, and in total, right? So these are the different 5 interconnected layers, and it should be talking to each other, right? So that is the key criteria here, and that is we call it the AI-ready enterprise, okay? And the data course should be there, clean course should be maintained, right? So those things are really, really required, okay? So now we're giving an example of SAP. So let's— whatever you understood, the entire Architectural theory into SAP ecosystem execution, right? And in this specific blueprint, our primary anchor will be the SAP Clean Core, whatever we are actually talking about, the Clean Core strategy of SAP. And you will also talk about the enterprise architecture governance here, and also the cross-functional BTP. Now it's the BAIP, Business Architecture Business AI Platform. And also we will see that so many more things coming up nowadays. So if you see in SAP now, no longer a system of record. It's, uh, in 2027, talking about clean core, BTP, everything, right? They're forming an integrated intelligent enterprise fabric. We also call it now autonomous enterprise. And the business processes are continuously optimized by the embedded AI agents. So embedded AI agent, they will go working day in, day out to optimize your process and everything. Okay, so definitely the core ERP will be S/4HANA clean core. Stable extensible foundation. There's a platform layer to it, SAP BTP. There is SAP BIP, Integration Extension Services. Then there's an outcome layer, integration data, AI, and processes driving the entire business outcome. So that is what exactly we are expecting here. And clean core is— what is it doing? It is not just a technical best practice, it is an architectural prerequisite for AI. If you're not having a clean core, forget about AI. AI will be giving all the wrong results. Okay, it is not effective. So for that reason, focus on the clean core and then everything will be taken care. AI-driven business processes, we can do automation, whatever you want to do it, you know, everything you can do in automation at a scale. So now moving on, so now as we are moving on from a pilot project, from a copilot to multi-agent enterprises, okay, so assistant will be helping you to answer whatever questions you are demanding, right? So So whenever you are having those questions and answers, because everything is questions and answers here, right? So you will be finding all the things as question and answers. So you have to have a copilot, or I will say supports will be helping you augmenting whatever decisions you are taking. Then agent will be executing your defined task autonomously, whatever the— okay, so assistant will be helping your queries and all these things, but it will not be taking any action as such, okay? Agent will be the really executing the defined task, okay, autonomously. Then we have multi-agent system. I already talked about here, right? So it will be concentrating entire thing in one place, right? So that is what exactly we have here, okay? Multi-agent system towards this complaint, okay? So this is perfectly fine. So now ultimately the goal is autonomous enterprise. So we have to continuously optimize the business outcomes and all of this thing, right? So that is the ultimate North Star for anyone in SAP or overall in general also, technology agnostic or diagnostic point of view, right? So this is the North Star for SAP and we have to become a, you know, autonomous enterprise, not theory but in practice, correct? So now we will be going for the boundary. So for do to do this entire activities and everything, right? So we also need a boundary for it, right? Isn't it? So we will see that what are different boundaries, okay? What AI will be doing, what AI is already good in that, and now also we'll see what human is doing for, okay? Any kind of analysis, recommendation, execution analysis, it can add and do much better, right? But any kind of an approval, governance. Set while setting a policy, guardrails, boundaries. You have to think about it thoughtful. Okay, escalate if any exceptions happening to exceed AI authority. You can override. Okay, with if anything is required, right? So these things are really really required. Okay, so this is what exactly the architecture defining the decision. Boundary. We have to be very clear about it. And human in the loop is always there. So auditability point of every AI action is logged and traceable. At the same time, we'll be having explainability. Decisions can be interpreted by normal human being even if they do not understand all the details, right? So that is the thing, human in the loop. So now moving on Accountability also should be there from a human-in-the-loop point of view. So now from a leadership point of view, if you talk about the architecture side of it, they have a vision, they have to see that strategy direction, that outcome, they have to fix it, purpose of the organizations. They would always talk about that in any of the communication channel, and then you decide basically who is deciding, what is they are deciding, right? All the details are here. Okay, so now the architecture, we are talking about the entire system rather than the only a fixed point-based solution, right? So this entire ecosystem we are talking about when it comes to the architecture, right? So vision, this is the decisions, governance, who, what controls. This is more of a self-explanatory, I don't want to read all of these things. So whenever you're moving such a kind of an architecture layer, right, so we have to have a Data foundation, you have to have a transitional core, you should be having structured, agentic orchestration, and experience. These are the 4 things you must be having, okay? And I think this is okay. So now what I will go purely talking about a particular case study, then we will move on. So from an overall case studies point of view, as I said, Okay, you will be going to a case study. In this industrial case study, across manufacturing or finance, whatever it may be, there's a particular pattern they follow, right? So there are fragmented decisions making. You will be agreeing with me also in your organizations. So there are different, different people, they have different, different opinions, okay? And everything is— I will not say perfect, right? And in that context, you will be having a different— when it comes to the case studies, so in this, we will be seeing that the problem will be the common. So whatever the case study even we have solved in the last boot camps and hackathons and all, right? The problem is the fragmented leadership decisions made in silos, and they do have— do not have the— with no CI data foundation, they're consistent, all the things. So now what we see is the problem is the fragmented leadership decisions, okay, made in silos. Which is a very common thing, okay? And there is no data sharing across the foundation, right? So this actually, that is the main problem. It will be leading to any kind of data silos happening or any issue happening inside your organization, right? Then how we can fix it? Definitely from architecture point of view, start the business capability mapping. Then you do the entire unified enterprise data layer. If you're utilizing SAP, go for clean core, BTP, VAIP, and everything. Then ask for the AI agents and from the platform, and then you can do the entire integrated governance framework, right? So that is what exactly you can do. Autonomous workflow— this is the continuous loop. Sense— it will be sensing your market signal, checking there via AI, decide decision making, and it is recommending, okay, based on that which are the topics You may be wondering, right? So you have to act through automated workflows, and this is what exactly you'll be learning from here, right? So now we will go into the next segment. So going to the next segment, you go to the autonomous workflow we are talking about. So we have outcome: faster, high-quality decisions, because that is what exactly we require. Greater transparency, and it should be auditable, right? And scalable operations that adapt with the manual intervention. So recently I was participating in one of the contests, uh, so I'm yet to submit it, but again I can showcase that whenever we are doing such activities, uh, those things, okay, should be properly done, okay? So this GitHub file I'll be sharing with all of you. So it was really in the MVP stage. It is all about the compliance, security, and risk heat map. Okay, this is what exactly I have recently did. We built an entire MVP for SAP Linux custom report and providing executive level overview of application portfolio and all. And this was the structure for it and the entire application portfolio. And to start with, we have started the 5 compliance framework like GDPR, PCI, ISO X HIPAA, ISO 27001, and supported application risk dimensions. So talked about business criticality, functional suitability, technical suitability. Obsolescence risk, six R time priority, AI risk, S availabilities and a lot of things, right? But we we have what we have to do is here I will be also talking about that is in this as I say we have to think about the architecture first that should be our approach, right? Now this entire from a skill stack point of view how does it look like? We'll also try to understand, right? So So now if you go to the skills stack, and we have these are the different 5 levels. So people will start with the level 1. So level 1 is all about the foundations. Are you understanding the business? Are you understanding the intent? Are you understanding system thinking, architectural principles? Okay, so this is again not so theoretical, but you have to also understand what are those areas you understand part Then we go for your digital platform in the level two, right? And SAP Cloud API integration everything will be there. Then level three is all about business BIDAT business data application and technology. Okay. So now the fourth one. Yeah. So we don't have anything here. So I will click. So I'll go for the leadership. I have to influence the people. They have their logic. So these are the different levels we are having in AI architecture. Then the 5th level is leadership. Okay, they have influence, vision, and change, right? So this is what exactly we are talking about from a skill stack point of view, from an EA perspective. Okay, this be really helpful. Now it's time for actions. So what actions you are going to take? Okay, so it is not about whenever starting any other program, it could be any other project, any type of initiative, any other program or project or any such thing, right? It starts with a— doesn't start with a program name or a budget. Rather, you have to— it starts with an architect who is deciding to act. Okay, there are so many people in the outside But you are the only those people who is really watching this, right? They could have done something else. So how this they are connected? So now what you are going to do here in this activity, we are given a three. Activity first of all, you do the mapping. Go back to your drawing board. Identify one critical business capability in your organizations that is underperforming or at risk. Make it visible. Make it specific. Okay, so that is the one thing you have to do. How does the business capability look like? So I will be quickly show you that. Okay, I have a system access. So if you go to your if you're utilizing SFL Linux or very similar tool, you will be having an access like this. So I will detail. Okay, so I will go there and inside this you will be finding the details about. So I am logging in. So if I go here, if I go to inventory, I will be giving an example of business capability. So I'm just showing you the business capabilities here. These are different business capabilities. You can see HR is already there, human resources, IT platform integrations, all the things are here. So these are different, all the things you can see, PBV like that. Okay, level 1, there we have a 10. Okay, and below that we have level 2, level 3, like that. In level 1 already we are having a human Resources, file and performance. Okay, so now this part is done. So there are different— as I say, highlight these things should be clear. Okay, this is the business capability. You must clearly maintain all of these things like this would be your thing, okay? Then you go for level 2, level 3, that is not required at this moment, okay? But you start with this activity in your organization first, okay? So these are different, we call it business capabilities, and you must create all of these things, okay, in your organizations. Now having said that, we will go to the next segment. Okay, so these are the things which I thought of sharing. Now going back to the mapping, mapping you have to ensure make it visible, make it specific. Then you architect, map that complex data dependency, what kind of data dependencies are there for that particular data. So map— after the mapping is done, identify the data dependency, supporting applications, what are the AI opportunities, governance requirements. So again, we are getting a template based on that, we'll be following that. Then you design the full picture in the architect level. Then that is not the end of the game, okay? After strategic architecture, definitely you have to experiment, you have to do here yourself, right? And test with how does it look like, uh, You know prototyping and how we are going to design. Okay, design entire thing, right? So let's see. So now we are having a map architect and experiment thing. So start architecting. It will take some time. So they say the future enterprise won't just be digital. System, it will be architected. So you have to design that, okay? So focus on your leadership and enterprise architect leader. Now, what leadership capability must enterprise architects develop before 2027? Okay, so I will be seeing your comments. Put your all the comments, okay, and feedback inside this particular YouTube channel. Otherwise, anyway, these videos will go up in the LMS as well. Okay, so that was what exactly I thought of sharing, what leadership ability must you have to have, and architecting, so that you can architecting design experiences for a better world for dermatographers, right? I think that's all for today. If you have any questions, you can ask. Otherwise, we have an announcement. So those who want to join our platform, you have an opportunity for you now to join quickly. Otherwise you'll be losing whatever we are offering here. So this is our main website, successlabsacademy.com. Those who want to enroll any of your program, okay, we start with the foundations. We have an L1 and it's a very simple membership model and we are having 4 hackathons per year. September month hackathon is already done, so we'll start a new hackathon in the next October and these are few details will be filled up, and this is also pretty much affordable. So this is the one thing. Then we have also other thing, that a heatmap is already ready for some of the projects, but some projects are still running. So now we will go for the— so this is what exactly you can— once you start, within 15 minutes the timer will go up and it will be again changing in So ensure you're registering. You'll be having hands-on hackathons. So how does it look like? So you'll be finding when you go for our platform. Now if you have missed any of the previous hackathons, those recordings will be available. You can always watch that. Okay, so what I'm trying to say here is So now we will check it out how it can be done. So, so you'll find the recordings. As I was saying, we have all the sessions recordings here. Those who are joining in, so your first course is this one. You have to enroll, you have to attend the members-only orientation. This is having a 6, uh, okay, video— no, so here do not have videos as such directly. You have to have orientation, general orientation, followed by a 12-20-11 formula. 12 architecture streams, 20 learning tracks, and 11 GIS sectors. So I think this is good. I will go ahead with here. So now we will be going— there are different projective orientation for different orientation for— so now you will see. So these are different things you will be finding in the previous sessions, and as well as I say hackathons. Hackathons are actually, I say, there 6 missions happening every quarter, and you should join. You can join at any point of time, even if it is finished or even it is starting new, right? But at least stay connected, okay? So that is the mantra for success. And a lot of more, many more courses will be coming up. And also we have segregated all the 7 business— 6 business domains, right? Enterprise Active domain. So all the HR topics will be coming up here. So these are the things I thought of sharing. And join the program if you are interested, if you are serious, and if you want to go deep level. Okay, this is the basic model we are following. It is affordable and it's a lifetime. The good thing is it's a lifetime access. You'll be getting this to this membership. Just to go for it and let me know. So with that note, God bless, take care, thank you very much, bye-bye.