The Three Priorities
Draft strategic objectives — open for community comment
The ASA Board of Directors identified three priority domains for concentrated investment and action. Each domain has a draft measurable objective developed during the spring 2026 strategic planning session. These objectives are open for community comment through July 15, 2026.
Priority 1: Stakeholder Engagement & Advocacy
Why this priority
The statistics profession’s unique contributions to responsible AI development are not well understood by policymakers, industry, or the broader public. The distinctive value statisticians bring, principled uncertainty quantification, bias assessment, causal inference, reproducibility, data provenance, is precisely what responsible AI development most needs, and what the public least understands.
The ASA has existing assets: its 2023 Statement on the Role of Statistics in Data Science and AI, and its Statement on Ethical AI Principles for Statistical Practitioners. The challenge is translating these into active, sustained presence in the institutions shaping AI’s future. This priority positions the ASA as an active, visible advocate for carrying the message that AI cannot be developed or deployed responsibly without statistical expertise into the rooms where those decisions are being made.
Draft objective
By December 31, 2026, the ASA will identify priority stakeholders across policy, industry, funding, and the scientific community and launch targeted engagement and advocacy campaigns, anchored in the message that AI cannot be developed or deployed responsibly without statistical expertise, as measured by the number of stakeholder engagements, media placements and impressions, formal partnerships or coalitions established, and ASA presence in AI governance and standards conversations.
Draft — open for comment Action steps and progress tracking will be added after JSM ratification.
Priority 2: Next-Generation Talent & Education
Why this priority
Statistics training has not kept pace with where graduates are going or what the field needs. The recent closure of a statistics department at a major research university is a concrete signal that programs face institutional risk.
Machine learning must be taught through a statistical lens by asking when performance generalizes, how to quantify uncertainty, and what assumptions justify a prediction. Teaching ML purely as a set of computational techniques, without that lens surrenders statistics’ comparative advantage. Well educated students will bring counterfactual reasoning and sensitivity to measurement that AI alone cannot replicate.
Draft objective
By JSM 2027, the ASA will develop and disseminate a white paper on statistics curriculum for the AI era, offering concrete recommendations for preparing undergraduate and graduate students for leadership roles in the ethical advancement and use of AI across academe, industry, and government, and will launch an accompanying outreach effort to encourage curriculum modifications consistent with its recommendations, as measured by dissemination reach, the number of departments reporting curriculum modifications consistent with the recommendations, and integration into ASA education and professional development programs.
Draft — open for comment Action steps and progress tracking will be added after JSM ratification.
Priority 3: Culture & Practices of Statistics
Why this priority
Professional development matters. Statisticians need new skills and fluency to engage confidently at the AI frontier. But culture is deeper than skills. It is about what the profession signals it values: in its publications, in its awards, in the language used to describe excellent work, and in how the ASA supports early-career members navigating genuine uncertainty about their professional futures.
The 2024 JSM town hall documented a shift in what the field needs — from narrowly scoped methodological contributions toward end-to-end, system-level problem solving. The ASA plays a central role in shaping professional norms, incentives, and the public face of the discipline.
Draft objective
By JSM 2027, the ASA will take deliberate steps to shape the culture and practice of the statistics profession in the AI era, including how the ASA recognizes valuable contributions, communicates the profession’s identity, and supports members’ confidence and sense of purpose, while expanding professional development offerings developed in collaboration with statistical leaders in AI, as measured by the breadth and participation in new professional development offerings, member surveys on professional confidence and identity, and observable changes in ASA publications, awards, and public communications that reflect the profession’s evolving identity in the AI era.
Draft — open for comment Action steps and progress tracking will be added after JSM ratification.
How the five domains connect
All five domains, three strategic priorities
The Board's planning session explored five domains. The themes of Data Work and Infrastructure and Engaging with AI/ML Innovations are integrated into the three priorities in the curriculum recommendations that address how students engage with AI/ML methods, in the advocacy campaign that positions statisticians as essential contributors to AI development, and in the professional development and culture work that equips members to engage at the technical frontier. The three priorities are not a narrowing of the conversation. They are an integration of it.
Respond to the draft objectives
Comments are open through July 15, 2026. The Board welcomes feedback on the objectives, the rationale, and any gaps you see.