Call for Papers: Industry Track

Distributed Artificial Intelligence has moved rapidly from theoretical foundations and laboratory prototypes into production environments that support decision-making, automation, coordination, optimization, and human-AI collaboration at scale. Modern AI systems are increasingly distributed by design: they involve multiple agents, heterogeneous models, decentralized data sources, edge-cloud infrastructures, human-in-the-loop workflows, and interactions across organizational, physical, and digital environments.

The Industry Track of DAI 2026 aims to provide a dedicated forum for researchers, practitioners, engineers, product teams, and industry leaders to share experiences, insights, systems, and lessons learned from developing and deploying Distributed AI, multi-agent systems, agentic AI, distributed learning, and large-scale AI applications in real-world settings.

We invite submissions that go beyond algorithmic novelty alone and highlight the practical realities of building, deploying, evaluating, and maintaining Distributed AI systems in non-trivial real-world environments.

Industry Track submissions should be up to 6 pages in length, excluding references and appendices. Papers must be written in English and submitted as PDFs through OpenReview.

Papers should follow the official DAI 2026 formatting guidelines. Authors should prepare manuscripts using the ACM LaTeX template. Two-column submissions using the ACM sigconf option are acceptable.

Accepted Industry Track papers will be included in the DAI 2026 conference proceedings.

Authors are encouraged to include an open-source or publicly accessible project link when applicable. Suitable links include:

• GitHub repository
• GitHub Pages project website
• Hugging Face model, dataset, Space, or organization page
• Public documentation page
• Demo system or video
• Benchmark, dataset, or leaderboard page
• Reproducibility package

The Industry Track will use single-blind peer review. Reviewers may know author and organization identities, but reviewer identities will not be disclosed to authors.

• Review period: 6 weeks
• Final decisions will be made by the program committee based on reviewer assessments, meta-reviews, and program-level deliberation.

Industry Track submissions will be evaluated according to criteria including practical significance, technical depth, relevance to DAI, clarity, quality of evidence, generalizability of lessons, artifact usefulness, reproducibility where applicable, and ethical and societal considerations.

Reviewers will be asked to consider whether the submission provides a meaningful contribution to the DAI community, even when the contribution is primarily practical, operational, or experiential rather than theoretical.

Submissions will be managed through OpenReview. Detailed author instructions and reviewer guidelines will be provided in the Author Guide and Reviewer Guide.

Accepted Industry Track papers will be included in the DAI 2026 proceedings, published through the ACM International Conference Proceedings Series (ICPS), and made available in the ACM Digital Library.

The ACM open access publishing model for ICPS applies. Authors based at institutions that are not part of the ACM Open program and who do not qualify for a waiver may be required to pay an article processing charge (APC) to publish their ICPS article in the ACM Digital Library.

Authors should consult ACM's ICPS author guidance, the ICPS publishing model FAQ, and the ACM Open program details for current publication and APC information. Questions about the ACM publishing model should be directed to [email protected].

Accepted papers will be presented at the conference as oral presentations, spotlight presentations, posters, demos, or other formats determined by the program committee. At least one author of each accepted paper must register for the conference and present the work.

• Submissions must present original work that has not appeared in, been accepted to, or be under review at another archival venue.
• Simultaneous submissions of substantially similar work to other archival conferences or journals are not allowed during the DAI 2026 review period.
• Submissions use single-blind review and do not need to be anonymized.
• Authors must disclose relevant conflicts of interest in the submission system.
• Authors are responsible for the correctness, originality, integrity, and disclosure permissions of all submitted content and artifacts.
• The use of generative AI tools must be disclosed when they materially contribute to writing, research design, code generation, data analysis, experiments, or other substantive parts of the work.
• Prompt injection, hidden instructions to reviewers or automated review tools, reviewer manipulation, plagiarism, fabricated results, and collusion are prohibited.
• Submissions should discuss ethical, legal, and societal considerations whenever they are relevant to the work, including implications for fairness, accountability, transparency, misuse, governance, labor, scientific practice, and the broader impacts of distributed or agentic AI systems.
• Submissions involving human subjects, sensitive or proprietary data, privacy or security risks, autonomous decision-making, multi-agent collusion or deception, scientific automation, safety-critical deployment, or high-impact domains must include an appropriate discussion of risks, safeguards, consent, approval processes, and legal or institutional compliance.

Industry Track Chairs
Weiwen Liu
[email protected]