Join data, AI, and technology leaders for an evening dedicated to exploring how Responsible AI can be scaled across the enterprise.
This edition of Building with AI focuses on operationalizing governance, aligning AI initiatives with regulatory expectations, and creating accountability across data, models, and people.
What’s in it for you:
Learn how leading enterprises are embedding Responsible AI frameworks into their data and technology ecosystems
Understand the governance structures that drive ethical and compliant AI adoption
Hear from practitioners building scalable, auditable AI systems
Network with Hyderabad’s growing community of AI innovators, engineers, and architects
AI literacy - Content and Innovation Director, Johnson and Johnson
Executive Director – Data, AI & Cloud Engineering, DBS Bank
Chief Marketing Officer, Covasant Tecnologies
VP, Data & Analytics, Covasant Tecnologies
Gain a strategic overview of how enterprises can move from ethical intent to operational maturity defining measurable guardrails for trust, transparency, and compliance in AI initiatives.
Explore how large organizations embed Responsible AI practices through governance councils, AI literacy, and enterprise alignment. Learn how to foster a culture that balances innovation with accountability.
Understand how enterprise data platforms serve as the foundation for Responsible AI. Discover strategies to operationalize data governance, lineage, and compliance across complex environments.
Explore how strong data governance frameworks drive transparency, auditability, and compliance in enterprise AI. Understand how organizations can align their data foundations with ethical AI principles ensuring that trust, lineage, and control are embedded across every stage of the AI lifecycle.
Setting the Context: From Responsible AI Principles to Responsible AI Practice
By: Subhendu Pattnaik
Chief Marketing Officer, Covasant Technologies
Gain a strategic overview of how enterprises can move from ethical intent to operational maturity defining measurable guardrails for trust, transparency, and compliance in AI initiatives.
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Get a practical walkthrough of using MCP Toolbox for databases and ADK.
Important Note:
Professionals developing and deploying machine learning models and AI systems across various domains.
Innovators creating next-generation AI products using generative technologies like LLMs and diffusion models.
Individuals investigating autonomous AI agents and the responsible development and oversight of large language models.