Eshaan Jain
AI & Enterprise Risk Leader | Driving Secure, Scalable AI Adoption in Regulated Environments
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Eshaan Jain is a technology leader specializing in AI-driven enterprise platforms, risk management, and scalable product architecture. With over a decade of experience building and leading complex enterprise solutions, he focuses on integrating AI into business-critical systems while ensuring security, compliance, and governance.
Eshaan has led initiatives across AI adoption, enterprise SaaS platforms, and digital transformation, with a strong emphasis on aligning innovation with risk management frameworks. His work bridges the gap between cutting-edge AI capabilities and real-world enterprise constraints, enabling organizations to scale AI responsibly.
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When AI Goes Wrong: A Practical Framework for Ethical Decision-Making in Rogue and Failing AI System
As AI systems move into high-stakes enterprise and societal decisions, failures are no longer hypothetical—they are inevitable. Yet most organizations are unprepared to respond when AI systems behave unpredictably, produce harmful outputs, or operate outside intended constraints.
This session introduces a novel, practitioner-driven framework for managing AI failures and “rogue AI” scenarios through structured ethical decision-making. Rather than focusing on abstract principles, we present a real-world operational model that helps organizations detect, assess, and respond to AI failures in real time.
At the core of this session is the “Ethical Failure Response Model (EFRM),” a decision framework that integrates risk severity, stakeholder impact, reversibility, and system autonomy into a clear response strategy. Attendees will learn how to classify AI failure modes—including hallucinations, adversarial manipulation, emergent behaviors, and model drift—and apply appropriate containment and remediation actions.
We will also explore the emerging concept of “ethical blast radius,” helping leaders quantify the downstream impact of AI failures across customers, employees, and regulatory exposure. Through realistic scenarios, we will demonstrate how organizations can balance speed, accountability, and transparency when responding to AI incidents.
Key takeaways:
* A structured taxonomy of AI failure and rogue behavior patterns
* The Ethical Failure Response Model (EFRM) for real-time decision-making
* A practical method to quantify ethical and reputational impact (“blast radius”)
* Governance patterns for incident response, escalation, and auditability
This session is designed for CISOs, risk leaders, AI engineers, and product executives who need actionable strategies to manage AI failures responsibly—before they become organizational crises.
From Experimentation to Governance: A Practical AI Integration Roadmap for Enterprise Risk Leaders
Most enterprises are rapidly adopting AI but few have a structured roadmap to integrate it into their risk management frameworks. This session introduces a practical, end-to-end AI integration roadmap tailored for enterprise risk leaders, bridging the gap between experimentation and governed deployment.
We will move beyond high-level principles and present a step-by-step model that aligns AI adoption with enterprise risk management (ERM), cybersecurity strategy, and regulatory compliance. Attendees will learn how to systematically identify AI use cases, classify associated risks (model, data, operational, and reputational), and implement governance controls without slowing innovation.
The session introduces a novel “Dual-Speed AI Risk Framework,” enabling organizations to balance rapid AI experimentation with structured oversight. Real-world scenarios will illustrate how organizations can proactively mitigate risks such as data leakage, model drift, adversarial attacks, and unintended bias—while still accelerating business value.
Key takeaways include:
* A 5-stage AI integration roadmap aligned with ERM principles
* A risk classification model for generative and predictive AI systems
* Governance patterns for secure and compliant AI deployment
* Metrics to measure AI risk exposure and organizational readiness
This session is designed for CISOs, risk leaders, and product executives seeking actionable strategies to operationalize AI safely at scale.
Eshaan Jain
AI & Enterprise Risk Leader | Driving Secure, Scalable AI Adoption in Regulated Environments
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