The research enterprise is evolving with new roles, responsibilities, and strategic approaches. The purpose of this Joint Statement is to establish the responsible use of research analytics, research evaluation, and AI as essential features of a robust and responsible research ecosystem within higher education, research institutes, and other research organizations. Research analytics, evaluation, and AI can help institutions understand their strengths, gaps, and opportunities for advancement. Analytics and evaluation intelligence support the development of asset-based strategies critical to the future of a research enterprise that drives discovery, innovation, and economic development. Professionals with expertise in these critical and highly technical areas require dedicated units, professional development, professional networks, and practical guidance. Institutions will benefit their research enterprise by making thoughtful and strategic investments in personnel and technologies that develop responsible approaches to analytics, evaluation, and AI in the research ecosystem. The profession should invest in building capacity, momentum, and understanding.
Research management professionals face tighter budgets, complicated compliance requirements, and evolving research priorities. Some institutions have robust, dedicated analytics capacities, but other institutions may lack the resources to support these functions or understand the urgency of building capacity. As the gap widens, institutions not investing in these areas may fall behind. AI and data tools are becoming more widely available, but they are not always well understood or appropriately applied. Without proper context, training, and oversight, these tools can introduce bias, undermine trust, or lead to decisions that do not align with institutional values or meet the needs of local and regional communities. Building expertise in research analytics and evaluation requires substantive and normative expertise. Ethics should be built into the delivery of analytics, AI, and evaluation practices as an ongoing consideration.
Institutions will benefit from anticipating needs and investing strategically in the infrastructure, expertise, and ethical frameworks that make responsible use of AI, data analytics, and evaluation practices based on the needs of their institution.
Guiding Principles
Guided by these principles, we affirm the importance of:
- Establishing an institutional system of data governance policies and standards to guarantee that data are accurate, secure, and used responsibly to support informed decision-making, responsible evaluation, and maintain trust across the organization.
- Ensuring individuals across the institution have access to the data, tools, and training they need, when they need them, to support institutional operations, key decisions, and strategic investments.
- Investing in dedicated staffing and resources focused on research analytics, decision support, and evaluation expertise.
By investing in these areas through properly trained staff, providing technical resources, solutions, and training, the research enterprise will be equipped to not only meet current compliance and accountability demands—but will continue to be competitive throughout the research and development ecosystem.