Human–AI Collaboration in Strategic Decision-Making: Cognitive Insights for Innovation, Governance & Risk Management

Abstract

This study examines the benefits of human-AI collaboration in strategic decisions, particularly innovation, governance and risk management. With the combination of human cognitive abilities and AI capabilities, the research analyzes the way of collaborative intelligence improving decision quality and company performance. Data on 1,200 strategic decision cases were tested on four algorithms (Random Forest, Support Vector Machine (SVM), Gradient Boosting, and Neural Network). Results of the experiment showed that Neural Networks were invariably the most successful in terms of predicting the human-AI decision alignment, the R 2 of the innovation outcome was 0.85, the mean score of the governance compliance indicated 87, and the risk mitigation effectiveness value was 0.71. Gradient Boosting and Random Forest were also very strong in predicting and SVM showed relatively poor results. The comparison with the previous studies [1526] validated that the consideration of cognitive variables of human beings has highly contributed to predictive power and to strategic intelligence. According to the findings, human-AI collaboration does not only maximise the outcomes in the field of innovation and risk but it also enhances governance and ethical decisions. The study highlights the need to develop collaborative decision-making systems that utilize both human judgment and AI intelligence, which provides practically grounded directions to establish resilient, responsible, and creative ideas to the organization.