Good morning everyone. I'm truly honored to be here at Conference for Thank you for giving me this platform to discuss a topic that is shaping not just our industries, but our societies, and ultimately our futures. My name is Vanil mpa, and I specialize in cloud technologies and ethical AI design. Today I invite you onto a journey where the story of cloud AI is not just about efficiency, gains and profitability, but with a lot of responsibility, ethics, and trust, because technology at it best serves the humanity. And it, at worst, it can divide, oppress, and even harm. Let's explore how we can ensure it, it all services better. The cloud AI revolution we are living through a once in a generation. Transformation organizations are embracing up to a 40% operational gains with with enhancing in the ai. Even a lightweight integrations create at least 25% of baseline efficiency, which is see which we're seeing as an improvement. And the cost structures have changed forever. Millions are saved through predictive analytics, optimization, and intelligent automation. Let's talk about some real-time examples. UPS saved 10 million gallons of fuel annually through through ai. Routing healthcare systems are cutting ICU vision times by 30% with using predictive staffing models. Amazon, which we use every day, generates about 35% of its revenue straight through AI driven recommendation engine. AI cloud is. Cloud AI is no longer optional. It's a foundation of modern and com to advantage, but with the speed of the innovation is breathtaking. The speed of ethical replication also lags behind. So what's the real time intelligence benefits? Three primary superpowers are unlocked through cloud ai, which is preventing the failures. Predictive AI detects vulnerabilities before cast failures occur. Example IBM Watson, which we heard recently, it's detecting the factory machines, breakdowns weeks in advance, accelerating the ratios, real time data empowers leaders to act immediately shifting the strategies with the agility that today's fast moving world demands. Example, American Airlines adjust its flight flight routes dynamically to avoid weather interactions. And we are talking about next personalized experiences from Spotify suggesting what would the next perfect song. And also and the hospitals tailoring the treatments to genetic profiles. Personal personalization is just about the convenience. It's about loyalty, outcome, and lives. But these benefits must deeper emerging risk if unchecked. So the ethical challenges which, which are emerging right now. Ethical concerns in AI have existed since its very beginning, dating back to early debates of over automated editions which happened in 1960s. Today, three themes dominate the landscape, which is a privacy. Everyone is scared of their own privacy. Data is collected and at unprecedented scale, yet transparency content consent mechanism often lagged behind. So algorithm bias, AI learns from historical data and the historical data is real with sorele biases, real time examples, the compass system. Used by us criminal screening systematically gave black defendants higher risk of sc of scorings and re reoffending Amazon internal AI hiring tool performed male candidates, a better over woman until it's what it was. Disman, the transparency black box system make decisions that even their creators often cannot explain. Ai at its core, AI ethics is about protecting dignity, the fairness and the agency, so the trust, the, there are a lot of rising concerns here, so trust is the most valuable currency in the ai if you lose it, and no, no amount of technical can compensate. Once the trust loss cannot be rebuilt, and especially in this era, what are the different key trends which we're talking about? Regulatory pressure is increasing. Is increasing. It might be in G-D-P-R-C-C-P-A-E-U-A Act. Canadas EID proposal investors are prioritizing environmental, social, and government standards, meaning ethical AI is just a compliance issue. It's a capital market issue. Consumers are becoming activism driven, boycotting companies, which are seeing analytical proof. The research shows that companies rank highly in ethical technology practice saw that the stocks raised 14% than their competitors doing the market. At Tmin Turbulences ethical AI isn't slowing you down it ins it's insulating you via loyalty. Let's talk about few case studies. Let's start with the financial services. Cancel the financial sector. The major global bank realized its loan application AI systematically penalized applicants from a lower income zip codes. This is ethically wrong. So what's, what are the character mechanisms they have taken deployed the, they deployed the advanced bias detection models, restructuring the data sets to ensure the balance representation, empowering a cross-functional human panel, human review panel, the, and the outcomes. They were amazing. Approving rates were harmonized across demographics. Within a 22% variance and the customer side and satisfaction it's sky, it's skyrocketed by 18%. And regulatory scrutiny, coff and the brand are so ethical. Correction just didn't compromise profitability. It's enhanced it. And the next case study, which we can talk about is healthcare. Healthcare amplifies the the stakes. The cloud AI now predicts the cardiac error, how was in advance, analyze the cardiac scans faster than the human radiology. And Tyler postop treatment plans based on the predictive models. And what are the safeguards in this? This healthcare AI needs to have end-to-end transcript encryption role-based access controls, graphic variance audits, because in healthcare bias isn't just analytical, it's lethal. And what is the future of ai? The future will demand even more maturity from us. Autonomous ai, the systems that independently adapt and self-correct, but always with the human governance boundaries. Edge, ai, moving intelligence to where the action happens. It might be in phones, factories, vehicles enhancing privacy and reducing latency. And the next is decentralizing infrastructure, distributor clouds, ecosystem, which are tamper proof, failure, resistance, and trust enhancing. The question is not will we have the system. It is, will they deserve our trust? Yes, they need to deserve trust. Deeper future risks, newer threats, loom. So there, there's, there, there's something called synthetic data bias training is on synthetic data data risks and embedding and amplifying unseen bias. So what's emotion there? There are a lot of emotional AI risks. AI systems detecting and manipulating human emotions raise alarming ethical dilemmas. What's deep? A deep fake profile as generative models become better at pro producing synthetic tests, images, and voice. The challenge of dis distinction, real versus fake is getting existential AI will increasingly act first, but must never act against us, but which is happening right now. So we need to balance this innovation with ethics. Balancing bold innovation with rigorous ethics requires systemization. It needs a proper framework for this. It's innovating fearlessly, evaluate impact, thoroughly implement ethical safeguards, and continuous monitor and adapt. And next we need to talk about ethical ethics by design principles, privacy by default, bias detection as part of standard qa expandability mandatory for all the critical systems, regular, independent, and external rx. Ethical AI is just not a destination. It's a dynamic journey. So not a single team or a dependent can can can shoulder this burden. So trust through a ethical AI requests executive leadership by, in the highest level, cross-functional product teams, which leverage the go product governance, multidisciplinary advisory councils, genuine community and stakeholder involvement. The best technical systems will just will be built just for the society, but for the society. So we need to, let's talk about some key takeaways here. So performance performance analytics can and must coexist. Ethical governance AC accelerates and hinders the innovation. Collaboration, diversity and transparency will define winners in the AI era. The systems we designed today will, outliers, let's ensure they carry forward with the best best values. Thank you. Thank you for your time, your dedication, and your vision. Innovation without ethics is empty. Innovation, grounded in ethics, that's how we change the world. Thank you everyone.