Salim Gheewalla

expert panel

Artificial intelligence is often framed as a race: faster models, bigger investments, larger datasets and more powerful infrastructure. But beneath the headlines lies a more consequential question for business leaders, policymakers and investors alike: Who gets to compete?A growing share of the AI ecosystem is controlled by a relatively small number of organizations with access to the world's largest compute resources, proprietary datasets and distribution channels. This means the debate is no longer simply about what AI can do but about whether the next wave of innovation will emerge from an open marketplace of ideas or from a handful of dominant ecosystems.To explore that question, we asked members of the Senior Executive AI Think Tank—a curated community of leaders specializing in machine learning, generative AI, digital transformation and enterprise AI applications—what single rule they would change to improve AI competition.While their recommendations differ, a clear theme emerges: The future of AI should be shaped by innovation, trust and customer value rather than lock-in, opacity or concentrated control. The following insights offer a timely look at how technology and business leaders believe a more competitive—and in many cases safer—AI ecosystem can be built.

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 debut of GPT‑5 has sparked renewed debate among enterprise leaders about how generative AI will drive business innovation. As adoption accelerates—with Gartner estimating that over 80% of enterprises will deploy generative AI applications or APIs by 2026—the question isn’t just what AI can do but how organizations can deploy and orchestrate it effectively. Drawing on their industry experience, members of the Senior Executive AI Think Tank—a curated group of leaders in machine learning, generative AI and enterprise AI applications—offer their first impressions of GPT‑5, their vision for its strategic implications and actionable, strategic guidance for navigating this next wave of innovation.

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Demands on cybersecurity teams are growing faster than ever before. Members of the Senior Executive Cybersecurity Think Tank share how they’re transforming team culture, training strategies and internal collaboration to address both escalating attacks and shifting regulatory demands.

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From SEC incident disclosure rules to evolving data privacy laws, cybersecurity leaders facing increasing scrutiny must rethink how compliance fits into daily operations. Members of the Cybersecurity Think Tank share practical frameworks and mindset shifts for staying ahead.