The TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence) AI for Enterprise Decisioning at Scale with Rob Walker - #573
May 16, 2022
Rob Walker, VP at Pegasystems, returns to share his expertise in AI and machine learning for customer engagement. He tackles the 'next best' decision-making dilemma and distinguishes it from recommender systems. The conversation dives into machine learning's coexistence with heuristic methods and tackles challenges around responsible AI practices. Rob also discusses the significance of feature stores and the balance between traditional models and deep learning, all while gearing up for the upcoming PegaWorld conference.
AI Snips
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Transcript
Episode notes
Pandemic Travel
- Rob Walker mentions flying during the pandemic on nearly empty planes between Europe and the US.
- He expresses relief about returning to more normal travel patterns.
Next Best Action vs. Recommenders
- Next-best-action recommendations differ from standard recommender systems by considering broader factors beyond product recommendations.
- These factors include affordability, customer context (like existing product ownership), and addressing pressing customer needs.
Outcome-Driven AI
- Start with desired business outcomes when designing AI/ML solutions for customer engagement.
- Define business goals before considering algorithms and then determine the necessary scaffolding for the 'next best action' metric.