Prashant Kondle

expert panel

As artificial intelligence advances at breakneck speed, the question of trust has become more urgent than ever. How do senior leaders ensure that innovation doesn’t outpace safety—and that every stakeholder, from customers to regulators and employees, retains confidence in rapidly evolving AI systems? Members of the Senior Executive AI Think Tank—a curated group of seasoned AI leaders and ethics experts—are confronting this challenge head-on. With backgrounds at Microsoft, Salesforce, Morgan Stanley and beyond, these executives are uniquely positioned to share practical, real-world strategies for building trust even in regulatory gray areas. And their insights come at a critical moment: A recent global study by KPMG found that only 46% of people worldwide are willing to trust AI systems, despite widespread adoption and optimism about AI’s benefits. That “trust gap” is more than just a perception issue—it’s a barrier to realizing AI’s full business potential. Against this backdrop, the Think Tank’s lessons are not theoretical, but actionable frameworks for leading organizations in a world where regulation lags, public concern mounts and the stakes for getting trust wrong have never been higher.

expert panel

AI‑native startups are scaling faster than ever—some hitting milestones that traditional SaaS firms took years to reach. But things are starting to move even faster. A recent analysis by Stripe suggests AI startups reach $1 million in revenue in about 11.5 months compared with 15 months for the earlier top SaaS models. That velocity comes not just from better algorithms but from a fundamentally different organizational posture. Meanwhile, many legacy firms are still navigating the early stages of adoption—pilots, governance debates, technical debt struggles—and too often fall short of meaningful impact. According to Boston Consulting Group, 74% of companies struggle to derive value from AI, with just 26% achieving scale beyond proof of concept. The Senior Executive AI Think Tank brings together leaders immersed in machine learning, generative AI and enterprise AI applications. Their collective wisdom reveals that competing with AI challengers demands more than tech upgrades—it requires deep structural and cultural shifts. In this article, they explore those shifts and offer actionable strategies for traditional organizations to close the gap.