In this episode of the AI Monetisation Podcast, Anita Luthra, Global Technology Director of AI and Cloud Labs at HCLTech, joins Co-founder Binny Mathews to explore one of the most overlooked challenges in enterprise AI: systemic bias and its multi-billion dollar impact.

Guest Background: A veteran in AI architecture, Anita has led major transformations at JPMorgan Chase, IBM, and now HCLTech. She pioneered the first Watson solution integration at IBM and is a recognized speaker on hallucination and bias in AI, recently featured at the Worldwide AI Summit.

What’s Inside?

1. The trillion-dollar blindspot: How bias infiltrates AI training data and algorithms
2. Real-world implications: Personalization failures and reduced efficacy for diverse users
3. Practical strategies: Detecting and mitigating bias through data, model tuning, and governance
4. Governance in AI: Why accountability lies with every member of the development lifecycle
5. Contrarian AI thinking: Why small models might hold the key to scalable, equitable solutions

Key Takeaways:

1. AI models reflect the societal and demographic imbalances present in their training data

2. Personalization without representation can lead to massive financial and brand risks

3. Bias correction must start early at data selection, architecture, and prompt engineering levels

4. Responsibility for bias mitigation cannot lie with a single team or function

5. Enterprises must rethink traditional hiring and development mindsets to stay relevant in the AI era

This episode is essential listening for enterprise leaders, AI engineers, and product owners looking to build fair, inclusive, and commercially successful AI systems in the real world.

For full show notes, visit- https://bit.ly/44d07Qh

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