Position Paper: The Opportunity for Visual Analytics in the Age of Generative AI

AI is rapidly transforming knowledge work, raising epistemic questions about the future role of many established research areas. For the Visual Analytics (VA) community, these developments raise the same question: how do advances in AI affect the role and direction of the field? In this position paper, we argue that VA is particularly well positioned to respond this. First, we examine the implications of AI for system-oriented VA research. Recent advances in code generation by AI reduce the cost of software implementation, shifting attention toward problem formulation and evaluation. Rather than undermining the role of systems in VA research, this shift highlights that VA systems often serve to instantiate conceptual ideas or to support the evaluation of analytical methods. As implementation becomes easier, greater emphasis is placed on identifying meaningful analytical problems and evaluating whether proposed systems support human tasks. Second, we revisit the broader VA research agenda and show that understanding analytical problems and assessing how computational tools support human reasoning have always been central concerns of the field. Additionally, while the integration of AI introduces new opportunities and challenges, it remains aligned with VA's core objective of supporting humans. We conclude that, rather than disrupting VA, advances in AI reinforce the field's human-centered foundations and align the broader landscape of software development with the challenges VA has long studied.