Product Innovation Educators
DECEMBER 23, 2024
How product managers are transforming innovation with AI tools Watch on YouTube TLDR In this deep dive into AI’s impact on product innovation and management, former PayPal Senior Director of Innovation Mike Todasco shares insights on how AI tools are revolutionizing product development.
Product Innovation Educators
MARCH 3, 2025
How AI captures customer needs that human product managers miss Watch on YouTube TLDR In my recent conversation with Carmel Dibner from Applied Marketing Science, we explored how artificial intelligence is transforming Voice of the Customer (VOC) research for product teams. However, these early efforts faced significant limitations.
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Product Innovation Educators
DECEMBER 2, 2024
Using a custom ChatGPT model combined with collaborative team workshops, product teams can rapidly move from initial customer insights to validated prototypes while incorporating strategic foresight and market analysis. Instead of focusing solely on today’s customer problems, product teams need to look 2-5 years into the future.
Piyanka Jain
MARCH 12, 2025
And not because AI itself is broken, but because companies keep treating it like a science project instead of a tool that actually needs to solve problems. Some common AI failurestories: The Data Hoarders : Companies that think collecting more data will somehow lead to an AI breakthrough. Ready to see where data is headednext?
Advertiser: Data Robot
Banks have always relied on predictions to make their decisions. Today, banks realize that data science can significantly speed up these decisions with accurate and targeted predictive analytics. How today’s banks can handle the data science talent shortage. Brought to you by Data Robot.
Product Innovation Educators
DECEMBER 16, 2024
Drawing from his 20+ years of technology experience and extensive research, Nishant shared insights about how these activities vary across different organizational contexts – from startups to enterprises, B2B to B2C, and Agile to Waterfall environments.
Piyanka Jain
JUNE 25, 2025
When I built my first AI model back in 2002, as part of my master’s thesis, I couldn’t have imagined the GenAI-native world we live in today. Back then, artificial intelligence was mostly theoretical, and building even a simple agent required weeks of work and heaps of computing power. The insights were buried in dashboards.
Advertiser: Data Robot
As the disease tragically took more and more lives, policymakers were confronted with widely divergent predictions of how many more lives might be lost and the best ways to protect people. This whitepaper reviews lessons learned from applying AI to the pandemic’s response efforts, and insights to mitigating the next pandemic.
Advertiser: Data Robot
The game-changing potential of artificial intelligence (AI) and machine learning is well-documented. Download the report to gain insights including: How to watch for bias in AI. Any organization that is considering adopting AI at their organization must first be willing to trust in AI technology.
Advertiser: Data Robot
But we can take the right actions to prevent failure and ensure that AI systems perform to predictably high standards, meet business needs, unlock additional resources for financial sustainability, and reflect the real patterns observed in the outside world. We do not know what the future holds.
Advertiser: Data Robot
Many organizations are dipping their toes into machine learning and artificial intelligence (AI). Download this comprehensive guide to learn: What is MLOps? How can MLOps tools deliver trusted, scalable, and secure infrastructure for machine learning projects?
Advertiser: Data Robot
You know you want to invest in artificial intelligence (AI) and machine learning to take full advantage of the wealth of available data at your fingertips. This report explores why it is so challenging to choose an AI vendor and what you should consider as you seek a partner in AI.
Advertiser: Data Robot
As machine learning models are put into production and used to make critical business decisions, the primary challenge becomes operation and management of multiple models. Download the report to find out: How enterprises in various industries are using MLOps capabilities.
Advertiser: Data Robot
Democratization puts AI into the hands of non-data scientists and makes artificial intelligence accessible to every area of an organization. Brought to you by Data Robot. Aligning AI to your business objectives. Identifying good use cases. Building trust in AI.
Advertiser: Data Robot
More and more critical decisions are automated through machine learning models, determining the future of a business or making life-altering decisions for real people. But with the incredible pace of the modern world, AI systems continually face new data patterns, which make it challenging to return reliable predictions.
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