Sathish Anumula

expert panel

AI didn’t just make industry headlines in 2025; it got embedded into everyday knowledge-heavy work, from research and content creation to recruiting and analytics. McKinsey & Company’s November 2025 report on the state of AI noted that 88% of respondents now regularly use AI to handle at least one business function, representing a significant year-over-year jump. AI is changing how value is created, how decisions get made, and what “good work” looks like when speed and automation are always on the table. The AI revolution isn’t limited to business and industry; broader cultural shifts hint that artificial intelligence is moving from a novelty to a norm among consumers as well. With 61% of multinational survey respondents saying they’ve used a generative AI engine, it’s clear that AI is forging ahead as a personal tool for research, education, shopping and even entertainment.  Looking ahead into 2026, AI’s growing reach across industries and culture has big implications not just for technology teams, but for anyone whose work depends on interpretation, decision-making or trust. Drawing on their real-world expertise, members of the Senior Executive AI Think Tank share their perspectives on how AI is likely to shape business and culture in 2026, why those changes matter and which roles, tasks and industries may be hit by the next wave of disruption first.

expert panel

AI agents are no longer experimental tools tucked inside innovation labs. They are drafting contracts, recommending prices, screening candidates and reshaping how decisions are made across companies. As adoption accelerates, however, many organizations are discovering a sobering truth: Knowing how to use AI is not the same as knowing when not to. Members of the Senior Executive AI Think Tank—a curated group of technologists, executives and strategists shaping the future of applied AI—agree that the next frontier of AI maturity is literacy rooted in judgment. Training programs must now prepare employees not just to operate AI agents, but to question them, override them and escalate concerns when outputs conflict with human values, domain expertise or organizational risk. That concern is well founded: Organizations relying on unchecked automation face higher reputational and compliance risk, even when systems appear highly accurate. Similarly, confident but incorrect AI outputs—often called “hallucinations”—are becoming one of the biggest enterprise risks as generative AI scales. Against that backdrop, Senior Executive AI Think Tank members outline what effective AI literacy training must look like in practice—and why leaders must act now.

expert panel

The launch of the White House’s Genesis Mission represents a bold federal effort to leverage artificial intelligence for scientific discovery, national competitiveness and economic growth. Announced in November 2025 via executive order, the Genesis Mission aims to create an integrated experimentation platform by linking federal datasets, high-performance computing and public-private partnerships to accelerate AI-driven breakthroughs across biotechnology, energy, semiconductors and more. As this national initiative unfolds, questions about equitable access, anti-competitive risk and inclusive governance have emerged from both industry and policy communities. Ensuring that smaller players—startups, academic labs and emerging innovators—have a fair seat at the table is not just an ethical imperative but a strategic one if the United States wants sustained innovation and economic vibrancy. Members of the Senior Executive AI Think Tank—experts in machine learning, enterprise AI and AI strategy—offer frameworks and strategies that federal leaders can adopt to prevent the Genesis Mission from becoming a vehicle that reinforces incumbent dominance rather than broad-based innovation.

expert panel

The launch of Google’s new AI shopping tools—including conversational search, agentic checkout and the ability for an AI to call stores for you—marks a turning point. These innovations raise a fundamental question for retailers and brands: What happens when the “customer” is no longer a human browsing or clicking, but an algorithm executing on behalf of a human?  Google expects this new model to simplify shopping at scale, using its Shopping Graph—with more than 50 billion product listings—and its Gemini AI models to power agentic checkout and store-calling. Yet the transition toward “agentic commerce” is fraught with risk and opportunity. Drawing on their expertise in machine learning, generative AI and enterprise AI applications, the members of Senior Executive AI Think Tank explore this new form of commerce, how this shift could upend traditional consumer relationships and what merchants must do now to stay visible—and profitable.