Andrei Danescu

expert panel

AI progress is often reduced to a leaderboard: a model scores higher on reasoning, coding or multimodal benchmarks, and the industry moves on to the next release. But benchmarks are snapshots of what a model can demonstrate under controlled conditions. They do not always capture what happens when increasingly capable models are connected to an organization’s data, software, physical environments and decision-making processes.The 2026 AI Index from Stanford HAI reports that frontier AI capabilities are advancing faster than many established benchmarks can measure, with some evaluations reaching saturation within months.Members of the Senior Executive AI Think Tank see a similar pattern from the front lines of enterprise AI, machine learning, robotics, cybersecurity, cloud technology and digital product development. They point to a broader question for business leaders: What are today’s most capable AI models beginning to do that could matter far more than benchmark gains suggest? Here, they explore the emerging capabilities they believe deserve closer attention—and what those developments could mean for the way organizations build products, make decisions and operate in the years ahead.