AI Insights 2025 with the Product Awards Advisory Board

What can AI and data trends from the Q1 Product Awards tell us about where product innovation is heading in 2025? In this webinar hosted by Products That Count CEO Hoda Mehr, members of the Product Awards Advisory Board will unpack the most compelling AI insights they observed across hundreds of nominated products in the Q1 Product Awards.

Speakers include Capital One AI/ML Product Lead Priyanka Pande, Chalice AI Principal Product Lead Bharat Manglani, Google Cloud Product Marketing Lead Varun Krovvidi, Guide Point Senior Product Consultant Shany Mo, Guidewire Software Inc. Product Lead Keyuri Anand, Meta Platforms Inc. Head of Product Neha Bansal, and Walmart International Principal Product Lead Parul Jain.

Together, they’ll share practical insights on how AI is shaping product strategy, the new role of data in product-led organizations, and what the best-in-class teams are doing differently.

Join us for new conversations with leading product executives every week. Roll through the highlights of this week’s event below, then head on over to our Events page to see which product leaders will be joining us next week.

Show Notes:

1. AI is now a table stake for product development, with 90% of product award nominees using AI in some form.
2. Having AI in a product is not enough; solving core customer problems remains crucial.
3. The differentiation bar has shifted – AI capabilities are now an entry requirement, not a competitive advantage.
4. Strategic implementation of AI is more important than simply having AI features.
5. 5. Successful AI products focus on specific customer segments and deep insights.
6. Traditional moats based on proprietary technology are evolving in the AI era.
7. Vertical specialization and domain expertise are becoming key differentiators.
8. Building custom AI models provides a stronger competitive advantage than using off-the-shelf models.
9. Ecosystem integration and interoperability are critical for product success.
10. Distribution and changing customer behavior matter more than just technological capabilities.
11. AI is enabling new reasoning pathways beyond simple automation.
12. Evaluation and training of AI models are crucial for creating product differentiation.
13. Network effects and trust are becoming important in building product moats.
14. Companies are emerging in three categories: vertical specialists, generalist AI builders, and product-led platforms.
15. Regulatory compliance and understanding specific industry nuances are increasingly important.
16. AI is transforming how insights are shared across different business functions.
17. The most successful AI products solve complex, multi-layered problems.
18. Niche market targeting can be a powerful strategy for AI product development