Hello, everyone. I'm Babita Kumari, senior software engineer at Microsoft. Today, I'm excited to discuss innovative cloud architectures, revolutionizing enterprise operations for AI integration. We will explore how AI and ML are transforming the way business operates and innovate, driving efficiency, and creating new possibilities. In this presentation, I'll cover four key areas. Advancement in AI powered cloud architectures. A case study showcasing real world applications. Best practices for designing innovative architectures. Future developments shaping enterprise operations. So without further ado, let's dive in. Let's talk about key advancements. AI and ML are reshaping enterprise cloud architectures through these three pivotal advancements. First one is productive resource management. Enterprises nowadays are using AI to dynamically allocate resources, achieving up to 91 percent accuracy. Thanks. In resource management and also minimizing waste with automated scaling, machine learning enables systems to adjust resources automatically during peak uses, and that improves efficiency by 67%. Last but not the least, intelligent security, AI driven threat detection models now prevent up to 99. 7 percent of potential security breaches. which provides unmatched reliability and trust. So these advancements enable any enterprise to be agile, efficient, and also secure, which is the topmost priority. So now let's talk about multi cloud frameworks. Most enterprises are now embracing multi cloud frameworks, combining both public and private clouds. So public clouds like Azure, AWS ensure scalability and 99 percent uptime, hosting the majority of workloads. Whereas private clouds offer more secure environments for like credit sensitive data, ensuring compliance and control. So this hybrid approach balances flexibility, performance, and also cost effectiveness. So let's talk about what are the four key layers or key components for any modern cloud architectures The first one is data processing layer which handles up to 100, 000 transactions per second and this ensure real time insights Then next comes the AI and ML integration layer. It supports over 1. 5 million daily intelligent operations and it helps in automated decision making. The security framework is the most important one as well. So it gives and implements zero trust models, safeguarding sensitive data, and achieving industry leading compliance. Monitoring and analytics is also very key, player here. So real time monitoring ensures 99 percent of time and predictive uses, reservations. So each layer is essential for delivering high performing and reliable systems. So, let's talk about a, case study of a global manufacturing corporation. So we'll talk about these principles and actions. The challenge we faced was a global manufacturer based efficiencies in supply chain, which costed around 12. 3 million annually. So we implemented a AI driven predictive analytics and real time monitoring to improve decision making and reduce downtime. The solution was to include predictive analytics and also add monitoring which can help in more insightful decision making and can reduce the downtime. The outcome were transforming 47 percent downtime reduction and 4. 2 million in annual savings and a 52 percent improvement in supply chain reliability. This use case or this global manufacturer corporation case study demonstrates How AI can drive a very miserable impact. Now let's talk about the best practices. So to replicate such a success, consider these three best practices. Access infrastructure regularly. Evaluate your cloud setup to ensure it aligns with evolving business needs. It's not like one time setup is done because we ever evolve our needs. Then we need to access infrastructure, whether it's meeting, whether we need, more or less. so we need, we should be accessing the infrastructure regularly. Then gradual migration strategies. But if very huge enterprises, This is the best approach. Transition workloads incrementally to reduce risk and maintain continuity. Also define success metrics like clear KPIs such as cost reduction, system reliability, and uptime. And measure and guide progress and keep on doing that. So all these three steps keep on doing that regularly. These steps provide a foundation for scalable and efficient systems. We have to be on top of this. So make sure we are measuring and guiding progress and taking benefit of anything which is coming in future. Let's talk about the integration strategy like I was mentioning in the last slide. So scaling AI requires a dynamic part parameter adjustments, optimizing performance for workloads ranging from low to high demand, and then robust monitoring frameworks. Real time monitoring predictive analytics for proactive uses. And issue, proactive issue and resolution. So this is one, also one of the important factors to be considered. Let's talk about continuous improvement or continuous performance optimizations. Leveraging AI to fine tune systems for evolving requirements. So such strategies maximize the potential of any AI powered architectures. Looking ahead, we see exciting trends, looking ahead, we see exciting trends receiving the enterprise landscape. Quantum computing integration, which involves the quantum 8 ML models, will enhance computational capabilities, bringing up to 200 percent efficiency and gain. So the future is really bright. Let's talk about multi cloud orchestration. This is happening even now, but in the future it will be a seamless collaboration across platforms, which will improve operational efficiency even more by 95%, 94%. And the edge computing revolution. The real time data processing at the edge will boost reliability to 99. 99 percent enabling faster, And smarter decision making. These advancements will redefine how any enterprise operation in the years is to come. We are definitely looking forward and, as I said, the future is looking really great in this. And the trends are going to reshape how any enterprise operations is going to be in the many years to come. To summarize, AI powered cloud architectures deliver 40 45 percent improvements in operational efficiency, which is a huge. And then 35 50 percent is in cost reduction, 60 70 percent in system reliability enhancements. Like I said, this technology is the largest one in the world. Transformation. They are more about empowerment and driving business to innovate and grow at the same time. At Microsoft, we are committed to building this type of solutions and enable any enterprise to thrive in this rapidly evolving world. Now, thank you so much for your attention and I look forward to your questions. Please feel free to connect with me. I'm available on LinkedIn. And from this conference, you could also get my contact details. So looking forward for any questions you have and we'll be happy to help. Thank you so much.