expert panel

Internal AI assistants are quickly becoming the connective tissue of modern enterprises, answering employee questions, accelerating sales cycles and guiding operational decisions. Yet as adoption grows, a quiet risk is emerging: AI systems are only as reliable as the knowledge they consume. Members of the Senior Executive AI Think Tank—a curated group of leaders working at the forefront of enterprise AI—warn that many organizations are underestimating the complexity of managing proprietary knowledge at scale. While executives often focus on model selection or vendor strategy, accuracy failures more often stem from outdated documents, weak governance and unclear ownership of information. Research from MIT Sloan Management Review shows that generative AI tools often produce biased or inaccurate outputs because they rely on vast, unvetted datasets and that most responsible‑AI programs aren’t yet equipped to mitigate these risks—reinforcing the need for disciplined, enterprise level knowledge governance. As organizations move from experimentation to production, Think Tank members offer key strategies for rethinking how knowledge is curated, validated and secured—without institutionalizing misinformation at machine speed.

expert panel

The recent Disney–OpenAI partnership represents a turning point in the convergence of entertainment and artificial intelligence. By investing $1 billion in OpenAI and securing a three-year licensing deal for over 200 characters, Disney positions itself not only as a content powerhouse but as a first-mover in AI-driven storytelling, setting new competitive benchmarks for legacy media companies. This partnership also shines a light on the way generative AI is reshaping IP licensing, content production and audience engagement at scale. Jeff Katzenberg, former CEO of DreamWorks Animation, says AI could reduce the costs of creating an animated film by 90%, drastically changing the way creative works have historically been produced. So what does this mean for the future of storytelling in the media? And how can legacy media companies integrate frontier AI capabilities into content ecosystems without compromising IP, brand integrity or creative quality? Members of the Senior Executive AI Think Tank—a curated group of experts specializing in machine learning, generative AI and enterprise AI applications—see the Disney–OpenAI alliance as a strategic signal that AI is moving from a peripheral tool to a core creative and operational engine. Below, they provide expert analysis and actionable strategies to help leaders navigate this rapidly evolving landscape.

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.

expert panel

In July of 2025, YouTube announced significant updates to its monetization policies under the YouTube Partner Program (YPP), explicitly targeting “mass‑produced, repetitious or inauthentic” video content—much of which is enabled by generative AI tools (that even they themselves continue to roll out). The move is broadly seen in media and creator communities as a reaction both to advertiser pressure and to user frustration with what has been dubbed “AI slop”—videos that generate clicks but erode trust and engagement. The members of Senior Executive AI Think Tank—a curated group of specialists in generative AI, enterprise machine learning and content strategy—have studied the implications of this trend. With decades of applied experience across industries, members offer both caution and opportunity: While there is reason to believe YouTube’s action could be a turning point, much depends on how platforms, regulators and creators respond.

article

The FDA’s new generative AI tool, Elsa, could signal the start of AI-native government operations—streamlining scientific reviews, increasing public transparency, and reshaping how trust is earned in digital-era governance. But as Elsa ushers in new efficiencies, AI leaders warn: Success depends on human oversight, ethical frameworks, and explainable systems.