AI Loves Data Podcast

We explore what it takes to turn powerful AI capabilities into products customers actually use and trust, from conversational intelligence and context management to human-AI collaboration, product metrics, and moving beyond AI pilot purgatory.
Key Highlights:
What separates an AI feature or assistant from a truly agentic product capable of taking action.
How product teams should think about context, permissions, user control, reliability, and human oversight.
Turning calls, messages, and customer interactions into actionable insights and intelligent workflows.
Why promising AI pilots often struggle in production and what product teams can do differently.
Why task completion isn't enough and how teams should think about quality, customer experience, trust, and business outcomes.
🎧 Tune in to Episode 67 to hear Tanvi Kopardekar’s perspective on designing the next generation of AI-first products and what changes when software stops simply answering questions and starts taking action.
Be sure to mark your calendars for the annual ALD SF on Nov 5. Join us for the Enterprise Builder’s conference to hear from experts on how AI is shaping the enterprise AI. Apply to attend for FREE:https://ailovesdata.com/san-francisco/



Writer and Host: Anna Anisin
Produced, edited, and mixed by the Formulatedby Team

With more than 25 years of experience across real-time machine learning, distributed computing, high-availability systems, and enterprise AI, Ravi brings a deeply technical perspective to one of the biggest questions facing organizations today: How do we move AI agents from impressive demos to systems businesses can actually trust to do work?
We explore how enterprises can operationalize AI agents, why industrial systems of record are critical to agentic applications, and what organizations need to consider around context, security, evaluation, governance, and human oversight.
Key Highlights:
Agentic AI: Hype vs. Reality: Where enterprise AI agents are delivering value today — and where vendor promises are still ahead of what's realistically achievable.
From Copilots to AI Workers: What separates a conversational AI assistant from an agent capable of reasoning, taking action, and participating in real enterprise workflows.
Agents + Systems of Record: Why integrating AI agents with ERP and other operational systems is essential for reliable, context-aware decision-making.
Engineering for Reliability: Lessons from distributed computing, real-time analytics, and high-availability systems that today's agentic AI teams can't afford to ignore.
Security, Evaluation & Guardrails: How enterprises should approach permissions, observability, failure detection, governance, and human oversight as AI systems become increasingly autonomous.
🎧 Tune in to Episode 66 to hear Ravi Bulusu's perspective on moving beyond the agentic AI hype and building AI systems that are reliable, secure, and ready for the complexity of the real enterprise. Check out: https://theloops.io/
Be sure to mark your calendars for the annual ALD SF on Nov 5. Join us for the Enterprise Builder’s conference to hear from experts on how AI is shaping the enterprise AI. Apply to attend for FREE: https://ailovesdata.com/san-francisco/

Writer and Host: Anna Anisin
Produced, edited, and mixed by the Formulatedby Team

James Robson works with charities, research institutions, and public-impact teams to help them navigate complex challenges around privacy, accountability, and ethical data use, ensuring that data is not only compliant but genuinely trusted.

We explore how organizations can move beyond “compliance theatre” to build systems that balance privacy, usefulness, and public value — especially when working with sensitive data in high-stakes environments.

Key Highlights:

Responsible Data in Practice: What ethical and lawful data use actually looks like inside organizations.

Beyond Compliance Theatre: Why checkbox compliance fails — and what to do instead.

Data Sharing & Trust: How to safely enable collaboration while protecting sensitive information.

AI & Accountability: How AI is changing the landscape of governance, risk, and decision-making.

Leadership & Decision-Making: Communicating risk and building trust across technical and non-technical teams.

🎧 Tune in to Episode 65 to learn how to build trustworthy data systems and responsible AI practices that stand up in the real world.

Be sure to mark your calendars for the annual ALD NYC on Dec 11, where we will focus on THE FUTURE OF APPLIED AI IN Finance and Banking. Join us to hear from experts on how AI is shaping the future of finance, banking and insurance: https://ailovesdata.com/newyork/ Use code ALDPODCASTNYC to get 25% off your registration. 

Writer and Host: Anna Anisin
Produced, edited, and mixed by the Formulatedby Team

Joyjit Roy shares his experience leading large-scale initiatives across insurance and eCommerce, including multi-year modernization programs that integrate AI into core enterprise systems.

We explore what it takes to move from legacy platforms to intelligent, scalable systems that can support real-time decisioning, MLOps, and next-generation automation.

Key Highlights:

Enterprise AI Modernization: How to integrate AI/ML into legacy systems while maintaining execution speed, governance, and business alignment.

Cloud-Native Transformation: Lessons from building scalable, event-driven architectures that improve agility, observability, and resilience.

MLOps in Practice: Insights into feature engineering, inference workflows, and operationalizing AI for real-world enterprise use cases.

Agentic AI in the Enterprise: Joyjit’s perspective on how agentic systems can enable adaptive decisioning, contextual workflows, and more intelligent automation at scale.

Leading at Scale: Strategies for aligning large, cross-functional teams across product, architecture, engineering, and business stakeholders.

🎧 Tune in to Episode 65 to hear Joyjit Roy’s insights on bridging strategy, delivery, and AI innovation to drive measurable enterprise impact.

Be sure to mark your calendars for the annual ALD NYC on May 13, where we will focus on THE FUTURE OF APPLIED AI IN Finance and Banking. Join us to hear from experts on how AI is shaping the future of finance, banking and insurance: https://ailovesdata.com/newyork/

Use code ALDPODCASTNYC to get 25% off your registration

Writer and Host: Anna Anisin
Produced, edited, and mixed by the Formulatedby Team

Key Highlights:

Production-Scale LLMs: Deploying and scaling recommender systems powered by large language models.

AI Infrastructure Challenges: Building reliable, high-performance search and ML platforms at global scale.

MLOps & Model Optimization: Lessons learned from optimizing and monitoring complex AI pipelines.

Future of AI at Scale: Trends in GenAI, multimodal AI, and recommender systems that will shape the industry.

🎧 Tune in to Episode 63 to hear Rahul Raja’s insights on creating scalable, reliable, and cutting-edge AI infrastructure for production-grade systems.

Be sure to mark your calendars for the annual ALD NYC on May 13, where we will focus on THE FUTURE OF APPLIED AI IN Finance and Banking. Join us to hear from experts on how AI is shaping the future of finance, banking and insurance: https://ailovesdata.com/newyork/ 

Writer and Host: Anna Anisin
Produced, edited, and mixed by the Formulatedby Team