March 29, 2024
What are the key considerations for developing AI platforms? In this episode of the Product Leaders to Watch series with Cognizant Product Director Chenny Solaiyappan, Bank of America VP of AI/ML and Automation Platform Hira Dangol shares strategies for AI product development, highlighting the importance of diversity and leveraging AI, ML, and data insights to solve business challenges. The conversation also explores frameworks for building solutions that deliver total experience value and the pathways for community involvement, continuous learning, and responsible growth in AI.
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Show Notes
- Product development strategies should leverage insights from industry leaders.
- Diversity plays an important role in product development.
- AI, ML, and data can be applied to address business challenges.
- Frameworks can guide building solutions from data to insights to automation.
- Total experience value is key, including customer, user, employee, and developer experience.
- Compliance, security, performance, usability, agility, and speed are important considerations.
- Community involvement and ecosystem building are important pathways.
- Continuous learning and collaboration help drive industries forward.
- Leadership discussion forums and panels are impactful ways to contribute.
- Products should go beyond solved problems to deliver holistic value.
- Vision, mission, execution strategy are important for product managers.
- Organizational and ecosystem priorities should be considered.
- Customer obsession requires understanding pain points.
- Revenue and monetization are important for commercial products.
- Experiential aspects deliver delightful experiences.
- Scaling preserves initial vision while adapting to needs.
- Privacy, availability, and functionality are essential aspects.
- Responsible growth is important for any product.
- Diversity, equity, and inclusion build stronger organizations.
- Contributing to the community is as important as personal gain.