How Responsible AI Is Being Built Inside Real Companies
Responsible AI is no longer just a theory—it's a necessity.
In this episode of The Founder's Foyer, we sit down with Aishwarya Srinivasan to explore how organisations tackle ethical AI in real-world environments.
This discussion covers deep and practical insights into data privacy, copyright, enterprise integrations, and the future of agent-based systems. If you're building with AI or implementing LLMS in your org,
This episode is a must-watch.
Learn how AI adoption, compliance, and governance must go hand-in-hand to shape innovation responsibly.
Timestamps:
00:00 – Introduction: Why Responsible AI Matters
02:42 – Data-Centric AI vs. Theory: Applying Ethics in Practice
07:35 – Copyright & Model Training Dilemmas
11:40 – Post-Training, Filters & What Data Should Be Used
16:10 – Role-Based Access & AI in Enterprise Workflows
22:25 – Productivity Tools & Data Privacy Risks
29:20 – Agent vs Automation: What’s the Difference?
35:10 – Human-in-the-Loop: Where It Matters Most
41:00 – Real AI Use Cases: Sales, GTM, and Non-Tech Teams
48:00 – The Need for Cross-Functional AI Literacy
52:45 – The Challenge of Data Silos and Integration
58:10 – Final Thoughts: Building Trustworthy AI Systems
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YouTube: @aishwaryasrinivasan
X (Twitter): @Aishwarya_Sri0
Medium: aishwarya-srinivasan.medium.com
Speaker Profile: Machine Learning Week Europe
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