Justin Newell

expert panel

No longer confined to analytics dashboards and recommendation engines, AI systems are now initiating transactions, approving workflows, flagging anomalies and even orchestrating other software agents. With this sudden increase in autonomy, business leaders are left asking: Where should humans step back—and where must they stay firmly in control? According to a 2025 McKinsey survey on the state of AI, nearly nine out of 10 organizations now report using AI in at least one business function, yet most are still early in scaling these technologies and many lack robust governance and risk controls. As artificial intelligence advances from advisory tools to agentic systems capable of multi-step planning and execution, the leadership challenge shifts: defining not just what AI can do, but what it should do. Members of the Senior Executive AI Think Tank—a curated group of experts in machine learning, generative AI and enterprise-scale transformation—argue that the real issue isn’t capability but accountability. Across their industry expertise, they all converge on one theme: The boundary between human judgment and machine decision-making must be dynamic, evidence-based and anchored in responsibility. Here is how they recommend drawing—and redrawing—that line.

expert panel

The recent release of TIME’s 2025 TIME100 AI list underscores how much attention is focused on foundation models, generative agents and consumer‑facing AI tools. Yet a closer look suggests that many powerful AI applications are still flying under the radar.  That’s where the Senior Executive AI Think Tank comes in—a curated group of experts in machine learning, generative AI and enterprise AI applications who combine technical depth with executive perspective. In this article, they use real-world insight to examine which industries and use cases are underrepresented in lists like TIME’s and explore the biggest AI frontiers that deserve attention now.

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AI Think Tank members predict the future of business dashboards, where natural language, predictive analytics, and strategic recommendations replace static charts and siloed metrics.

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AI agents and memory-enabled models promise enterprise transformation—capturing institutional knowledge, automating workflows and making context-rich decisions. But without robust oversight, they pose security, privacy and accountability risks. Members of the Senior Executive AI Think Tank share insights on the risks and rewards of agentic AI in business.

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Artificial intelligence (AI) is revolutionizing cybersecurity, helping businesses detect threats, prevent attacks and respond to incidents faster than ever before. But what happens when cybercriminals start using AI for their own gain? As businesses embrace AI-driven security, experts warn of the risks AI itself introduces. Can organizations strike the right balance between automation and human oversight? AI Think Tank members weigh in on the promise and perils of AI-powered cybersecurity.

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As artificial intelligence (AI) disruptors like DeepSeek challenge industry giants, tech-enabled businesses must make strategic AI investments that balance innovation with stability. This article, featuring insights from the AI Think Tank, explores key considerations such as scalability, cost, ethical governance and partnerships to help businesses navigate the ever-changing AI industry.