On 2 July 2026, the UN's Independent International Scientific Panel on Artificial Intelligence released its first preliminary report assessing AI's opportunities, risks, and governance challenges ahead of the inaugural Global Dialogue on AI Governance in Geneva on 6-7 July. The assessment provides an evidence-based foundation for international discussions, combining scientific research with a broad analysis of AI's impacts on sustainable development, human rights, and global prosperity.
Established by the UN General Assembly in August 2025 under the Global Digital Compact, the panel brings together 40 independent experts from academia, civil society, the private sector, and the technical community. It is the first permanent UN scientific body dedicated solely to assessing AI's development and societal implications. The report examines AI across four dimensions: scientific and technological developments, opportunities for sustainable development, emerging risks, and approaches to international governance.
Where AI is helping - and where it isn't
The report highlights AI's growing role in healthcare, education, agriculture, scientific research, and public administration. It describes AI as a general-purpose technology that can accelerate innovation and expand access to services. Demand for AI skills in research fields is climbing, and resources like AI for Science & Research help professionals deepen their expertise. Still, the panel finds these benefits remain unevenly distributed. Many developing countries lack computing infrastructure, technical expertise, and digital resources.
More than one billion people now use AI-powered services each week. Yet frontier AI capabilities-advanced models, specialised hardware, large datasets, and talent-are concentrated in a handful of companies and countries. The panel warns that without investment in local research ecosystems, digital skills, and multilingual AI, developing nations risk becoming primarily consumers rather than producers of the technology.
Emerging risks and sustainability pressures
The report identifies malicious uses of AI, including cyberattacks, fraud, disinformation, and election interference. It also points to risks from market concentration and limited transparency, noting that many governments cannot independently evaluate frontier AI models. Environmental sustainability adds another layer of concern. AI's growing computational demands require increasing amounts of electricity, water, and hardware, raising questions about resource efficiency and alignment with sustainable development goals.
The report itself states that "effective AI governance requires international cooperation," while acknowledging that governance approaches will continue to reflect different national circumstances and policy priorities.
The push for international cooperation
At the report's launch, UN Secretary-General António Guterres said that "the pace of AI development requires stronger international cooperation grounded in scientific evidence and inclusive dialogue." Panel co-chair Maria Ressa described the publication as "an independent scientific assessment designed to inform, rather than replace, intergovernmental decision-making." For those shaping AI policy, a structured resource like the AI Learning Path for Policy Makers can build critical understanding.
Future reports from the panel are expected to provide regular scientific assessments of AI capabilities and governance challenges as the technology evolves.
Why this matters for science and research professionals
The report underscores that AI's benefits and risks are not predetermined-they depend on how the global community governs the technology's development. For researchers, the findings highlight the urgent need to build equitable access to computing infrastructure, data, and AI literacy, especially in regions that risk falling behind. Scientists in both the public and private sectors are well-positioned to contribute to the evidence base that will shape future international standards. The panel's call for stronger scientific capabilities and locally relevant datasets directly affects how research communities collaborate and innovate in an AI-driven world.
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