AI-Based Sustainability Reporting Visualization Towards the 2035 Horizon

Abstract

The present study aimed to visualize the future of AI-based sustainability reporting toward the 2035 horizon by identifying key drivers, analyzing strategic uncertainties, and developing plausible future scenarios in Iran. This study employed a mixed-methods (qualitative–quantitative) futures studies approach. In the qualitative phase, fuzzy Delphi technique, expert interviews, content analysis, and cross-impact analysis were utilized to identify and evaluate the key drivers affecting the future of AI-based sustainability reporting. The participants consisted of experts in sustainability reporting, accounting, artificial intelligence, and policy-making who were selected purposively. Subsequently, cross-impact matrices and expert questionnaires were used to assess the interactions among variables and determine their influence and dependence levels. In the quantitative phase, the Scenario Wizard software was applied to extract and analyze compatible future scenarios. Scenario analysis was conducted based on the consistency of assumptions, interaction among drivers, and evaluation of strategic uncertainties shaping the future of sustainability reporting. The findings revealed that seven key drivers, including algorithmic advancements, predictive and analytical reporting, data transparency and traceability, evolution of sustainability reporting standards, binding national and international regulations, the role of professional and supervisory institutions, and organizational readiness and resistance, exerted the greatest influence on the future of AI-based sustainability reporting. Scenario analysis identified four highly compatible scenarios: “Smart Leap Toward an Integrated Sustainability Reporting Ecosystem,” “Cautious Transition to the Era of Data-Driven Reporting,” “Slow Movement Toward Minimal Transformation,” and “Continuation of the Traditional Status Quo Amid Institutional Resistance and Passivity.” The results indicated that the most desirable future would emerge when AI algorithm development, reporting standards maturity, regulatory coherence, data transparency, and organizational readiness are strengthened simultaneously. Conversely, institutional weakness, organizational resistance, and fragmented regulations may result in the persistence of traditional reporting practices and widening information gaps. The study concluded that the future of sustainability reporting in Iran is not solely dependent on technological advancement but is shaped through the simultaneous interaction of technological, institutional, regulatory, and cultural factors. Developing an intelligent sustainability reporting ecosystem requires strengthening data-driven infrastructures, coherent regulations, mature reporting standards, and organizational readiness for digital transformation. Smart policy-making and active involvement of professional institutions can facilitate the transition toward predictive and intelligent sustainability reporting and enhance transparency, accountability, and sustainable decision-making at national and international levels.