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AAAI-26 welcomes submissions reporting research that advances artificial intelligence, broadly conceived. The conference scope includes machine learning, natural language processing, computer vision, data mining, multiagent systems, knowledge representation, human-in-the-loop AI, search, planning, reasoning, robotics and perception, and ethics. In addition to fundamental work focused on any one of these areas, we expressly encourage work that cuts across technical areas of AI (e.g., machine learning and computer vision; robotics and multiagent systems, computer vision and natural language processing; or machine learning and planning), bridges between AI and a related research area (e.g., neuroscience; cognitive science), or develops AI techniques in the context of important application domains, such as healthcare, sustainability, transportation, and commerce.

The set of AAAI-26 keywords is available on the AAAI-26 keywords page. The author’s guide for choosing the best keywords describes important considerations in selecting keywords for a paper.

Most papers in AAAI-26 are expected to be part of the main track. All main track papers will be reviewed according to the same criteria and via the same process. This conference has two special tracks, which focus on AI for Social Impact, and AI Alignment. Papers in the special tracks will be reviewed according to a different evaluation rubric than papers in the main track. The same reviewing schedule will be followed for all papers.

Special Track on AI for Social Impact

As in past years, AAAI-26 will include a special track on AI for Social Impact (AISI). Submissions to this track will be reviewed according to a rubric that emphasizes the fit between the techniques used and a problem of social importance, rather than simply rewarding technical novelty. In particular, reviewers will assess the significance of the addressed problem; the paper’s engagement with previous literature on the application problem (whether in the AI literature or elsewhere); both novelty of and justification for the proposed AI-based approach; quality of evaluation; facilitation of follow-up work; and overall scope and promise for social impact. Further details are available at the AISI page.

Special Track on AI Alignment

The 2026 AI Alignment track seeks research on scalable oversight, mechanistic interpretability, empirical robustness evaluation, red-teaming, human cognitive and psychological factors, and safe-by-design engineering—including formal safety cases. We welcome work on transparent governance frameworks, economic incentives, institutional accountability, human-centered modeling and evaluation, and pluralistic coordination methods that enable AI systems to manage conflicting human values and foster international cooperation through shared evaluation standards. Submissions must state their contributions and relevance to the track clearly; papers that release open datasets, reproducible code, or practical evaluation tools are especially encouraged. Reviewing will emphasize technical correctness, appropriate coverage of related work, and relevance to the track. Further details are available at the AIA page.