Workshop: Quantum-Enhanced AI for Financial Decision-Making
ACM ICAIF 2026 Workshop
Intro: QAI4Fin 2026
QAI4Fin 2026 aims to bring together researchers and practitioners working at the intersection of artificial intelligence, financial services, and quantum-enhanced computation.
The workshop focuses on hybrid quantum-classical and quantum-inspired AI methods for financial prediction, risk modeling, trading, portfolio optimization, fraud detection, scenario generation, and financial decision-making. A central objective is to move the field beyond isolated proof-of-concept results toward reproducible benchmarks, rigorous comparisons with classical baselines, and financial-grade model validation.
The workshop welcomes contributions from AI, machine learning, finance, quantum computing, quantum machine learning, optimization, model risk, and financial technology communities.
Call for Papers
We invite submissions to QAI4Fin 2026, an ICAIF 2026 workshop on Quantum-Enhanced AI for Financial Decision-Making: Benchmarks, Hybrid Models, and Risk Governance.
The workshop seeks novel research papers, position papers, benchmark reports, reproducibility studies, positive and negative results, and industry perspectives that address the intersection of AI and Finance, with a particular focus on quantum-enhanced, hybrid quantum-classical, and quantum-inspired methods.
Topics
Topics of interest include, but are not limited to:
Hybrid quantum-classical machine learning for financial data
Quantum-enhanced financial time-series modeling and forecasting
Quantum and quantum-inspired reinforcement learning for trading, execution, hedging, and portfolio control
Quantum kernels, variational quantum circuits, quantum neural networks, and quantum feature maps for financial applications
Quantum-inspired optimization, sampling, tensor-network methods, and annealing-inspired methods for finance
Quantum-enhanced AI agents and sequential decision-making in financial services
Benchmarks, datasets, evaluation protocols, and reproducibility for quantum-enhanced financial AI
Classical baselines, ablation studies, noise analysis, and hardware-vs-simulator comparisons
Explainability, uncertainty quantification, robustness, validation, and calibration of quantum-enhanced financial AI models
Model risk, governance, responsible AI, and regulatory considerations for emerging AI and quantum-AI systems in finance
Submission Types
• Full workshop papers: up to 8 pages, including references
• Extended abstracts / position papers: up to 4 pages, including references
• Benchmark, reproducibility, and negative-result reports: up to 4 pages, including references
All submissions should use the ACM sigconf format. Reviews will be double-blind. At least one author of each accepted paper must attend the workshop in person and present the work. [ACM templates]
Accepted workshop papers are non-archival and will not appear in the ACM ICAIF proceedings. The workshop organizers may list accepted papers on the workshop website.