Rajasekhar Chitta

expert panel

​​The rapid expansion of artificial intelligence across government—from cybersecurity to citizen services—is reshaping national security itself. As AI moves into critical decision-making, companies building these systems are evolving from technology providers to strategic partners with real geopolitical influence. And adoption is accelerating fast. AI is moving from experimental pilots to mission-critical infrastructure, powering intelligence analysis, threat detection and operational decisions in real time. With this reliance comes high stakes: Errors carry strategic, legal and human consequences, making accountability, transparency and ethical boundaries essential. For AI companies, this creates a defining tension: how to support national security objectives while maintaining principled limits on technology use. Senior Executive AI Think Tank members—a curated group of leaders in AI governance, enterprise transformation and digital innovation—argue that firms establishing clear guardrails now will shape global standards, build trust and secure long-term advantage. Below, they explain how AI companies can balance national security partnerships with ethical guardrails—and what risks or opportunities they see in drawing firm lines on how this technology can be used.

expert panel

As artificial intelligence matures, one question looms large for executives: Where will durable revenue actually come from? Despite explosive adoption, many AI products still struggle to convert usage into sustainable profit. The shift from experimentation to enterprise value is now underway—and the stakes are high. Insights from the Senior Executive AI Think Tank—a curated group of leaders in machine learning, generative AI and enterprise systems—point to a clear trend: Profitability will not come from novelty, but from deeply embedded, outcome-driven applications. A recent Forbes report on AI ROI in the enterprise found that more than half of companies using AI are already seeing measurable revenue gains, with many reporting 6% to 10% growth, and some exceeding 10%. The findings reinforce a critical shift: Organizations are prioritizing AI solutions tied directly to business outcomes rather than experimental tools. What emerges from the Think Tank’s collective perspective is not a single dominant model, but a clear direction of travel. Enterprise copilots, verticalized AI systems, outcome-based pricing and workflow-native automation are converging into a new blueprint for profitability—one rooted in integration, accountability and measurable results. The following insights break down how these models are taking shape in practice, and what leaders must prioritize now to turn AI from a promising capability into a dependable revenue engine.

expert panel

Europe has spent the last decade establishing itself as the global leader in technology regulation. The General Data Protection Regulation (GDPR) reshaped how organizations handle personal data worldwide, and the European Union’s landmark AI Act aims to set guardrails for high-risk AI systems across industries. Yet policymakers now appear willing to recalibrate. European officials have begun discussing potential simplifications or delays to portions of the AI Act and related digital rules as they confront a widening innovation gap with the U.S. and China. The EU’s strict regulatory framework has slowed the pace of large-scale AI experimentation compared with other global tech hubs, putting them at a distinct disadvantage in the market. Members of the Senior Executive AI Think Tank—a curated network of leaders specializing in machine learning, generative AI and enterprise AI strategy—say the debate isn’t simply about regulation versus innovation. Instead, they argue that Europe’s regulatory approach has quietly limited several categories of AI development, from cross-border data platforms to real-time industrial automation. If policymakers move forward with regulatory adjustments, the ripple effects could be significant: Startups may gain the freedom to experiment faster, enterprises may finally scale AI deployments beyond pilot programs and the EU could evolve from global rule-setter into a more formidable technology competitor. Below, Think Tank members explain what Europe may have been holding back—and what could happen next.