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Companies that adopt AI-driven decision systems channel more capital into green projects, and those investments raise both environmental metrics and firm financial returns; robust governance noticeably amplifies these benefits.

AI-Driven Decision Capability, Green Investment Intensity, and Sustainable Firm Performance: The Moderating Role of Governance Quality
Md Qamruzzaman · July 23, 2026 · Journal of Intelligent Decision Making and Information Science
openalex correlational medium evidence 8/10 relevance Summary only summary available; pdf_status=error DOI Source PDF

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Firms with stronger AI-driven decision capabilities allocate more to green investments, which in turn improve environmental sustainability and financial performance—effects that are amplified by higher governance quality.

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The role of artificial intelligence (AI) in project evaluation, capital allocation, and sustainability performance has gained attention, yet the firm-level channel through green investment remains underexplored. This study examines whether AI-driven decision capability increases green investment intensity and whether such investment improves environmental sustainability and financial performance under the moderating role of governance quality. The analysis uses panel data for 750 firms from 2015 to 2024 and applies descriptive statistics, panel regression, mediation and moderation tests, dynamic robustness checks, and machine learning models. The results show that AI-driven decision capability significantly increases green investment intensity. Green investment positively affects environmental sustainability and financial performance and mediates the link between AI capability and firm outcomes. Governance quality strengthens the effect of green investment on both outcomes. The findings indicate that AI creates sustainable value through strategic capital allocation, especially when firms maintain effective governance mechanisms.

Summary

Main Finding

AI-driven decision capability increases firms’ green investment intensity, and those green investments improve both environmental sustainability and financial performance. Green investment mediates the link between AI capability and firm outcomes, and the positive effects are stronger when firms have higher governance quality.

Key Points

  • Sample: panel of 750 firms observed from 2015–2024.
  • Core variables:
    • Predictor: AI-driven decision capability (firm-level).
    • Mediator: green investment intensity.
    • Outcomes: environmental sustainability and financial performance.
    • Moderator: governance quality.
  • Main statistical results:
    • AI capability → significant increase in green investment intensity.
    • Green investment → significant positive effects on environmental sustainability and financial performance.
    • Mediation: green investment substantially mediates the AI → outcome relationships.
    • Moderation: governance quality strengthens the positive effect of green investment on both outcomes.
  • Robustness: findings hold under dynamic robustness checks and when evaluated with machine learning models.

Data & Methods

  • Data: firm-level panel data covering 750 firms over 2015–2024.
  • Empirical strategy (as reported):
    • Descriptive statistics to summarize key variables and correlations.
    • Panel regression analyses to estimate relationships between AI capability, green investment, and outcomes.
    • Mediation tests to assess whether green investment transmits the effect of AI capability to environmental and financial outcomes.
    • Moderation tests to evaluate whether governance quality alters the strength of green investment’s effects.
    • Dynamic robustness checks to account for temporal dependence and potential dynamic endogeneity (e.g., inclusion of lagged variables / techniques appropriate for panel dynamics).
    • Machine learning models used as supplementary robustness/validation (to capture nonlinearities or improve predictive performance).
  • Variables and controls: study focuses on AI capability, green investment intensity, environmental sustainability, financial performance, and governance quality — standard firm controls are implied though not enumerated in the summary provided.

Implications for AI Economics

  • Capital allocation channel: AI capabilities can materially reallocate firm capital toward greener projects, making AI an important micro channel for sustainable investment.
  • Value creation: AI-driven green investment not only advances environmental performance but also yields financial benefits, implying complementarity between ESG and shareholder value when AI informs investment decisions.
  • Governance matters: Effective corporate governance amplifies the returns (environmental and financial) from green capital allocation enabled by AI — governance is a key moderating institutional factor.
  • Policy and management:
    • Policymakers and investors should consider promoting AI adoption alongside governance improvements to accelerate corporate green transitions.
    • Firms should invest in both AI decision systems and governance capacity to capture sustainable value from green investments.
  • Research directions:
    • Further work can unpack causal mechanisms (e.g., instrumenting AI adoption), heterogeneity across industries and firm sizes, and the long-run welfare implications of AI-driven green capital reallocation.

Assessment

Paper Typecorrelational Evidence Strengthmedium — The study leverages a reasonably large panel (750 firms over 2015–2024) and conducts multiple robustness exercises (dynamic checks, ML robustness, mediation/moderation), which increases credibility that relationships are systematic rather than spurious; however, absent clear exogenous variation, instruments, difference-in-differences, or other quasi-experimental identification, endogeneity (reverse causality, omitted variables, measurement error) remains a salient concern. Methods Rigormedium — The authors use an appropriate suite of empirical tools for observational panel data (fixed effects-style regressions, mediation and moderation analyses, dynamic robustness checks) and complement econometric work with machine-learning checks; but the description does not indicate use of formal endogeneity-correcting approaches (valid instruments, natural experiments, regression discontinuities) or detailed measurement validation for key constructs (AI-driven decision capability, green investment intensity), which limits claim strength. SamplePanel of 750 firms observed annually from 2015 to 2024 (firm-year panel; source and country/market coverage not specified), with firm-level measures of AI-driven decision capability, green investment intensity, environmental sustainability outcomes, financial performance, governance quality, and standard controls (likely size, industry, profitability, etc.). Themesadoption innovation governance org_design productivity IdentificationObservational panel analysis using firm-year panel regressions (likely with firm and year fixed effects), mediation and moderation tests, dynamic robustness checks (e.g., lagged dependent variables or system GMM unspecified), and machine-learning models used for robustness or prediction; no exogenous shock, instrument, or randomized variation reported to definitively isolate causation. GeneralizabilityUnknown country/market coverage — results may reflect institutional/regulatory context of the sampled market(s), Likely biased toward larger or publicly listed firms if drawn from disclosure-based data, limiting applicability to SMEs, Measures of AI capability and green investment may rely on firm disclosures or proxies that vary in accuracy across sectors, Findings may not generalize to sectors with very different capital intensity or environmental regulations, Temporal generalizability: 2015–2024 captures early-to-mid AI adoption but results may shift as AI diffuses further, Causal generalizability limited by observational design and potential unobserved confounders

Claims (8)

ClaimDirectionOutcomeConfidence & EvidenceDetails
AI-driven decision capability significantly increases green investment intensity. Adoption Rate positive green investment intensity
Reading fidelity high
Study strength medium
n=750
0.3
Green investment positively affects environmental sustainability. Consumer Welfare positive environmental sustainability
Reading fidelity high
Study strength medium
n=750
0.3
Green investment positively affects financial performance. Firm Revenue positive financial performance
Reading fidelity high
Study strength medium
n=750
0.3
Green investment mediates the link between AI capability and environmental sustainability. Consumer Welfare positive environmental sustainability (mediated effect)
Reading fidelity high
Study strength medium
n=750
0.3
Green investment mediates the link between AI capability and financial performance. Firm Revenue positive financial performance (mediated effect)
Reading fidelity high
Study strength medium
n=750
0.3
Governance quality strengthens the effect of green investment on environmental sustainability. Consumer Welfare positive environmental sustainability (moderated effect)
Reading fidelity high
Study strength medium
n=750
0.3
Governance quality strengthens the effect of green investment on financial performance. Firm Revenue positive financial performance (moderated effect)
Reading fidelity high
Study strength medium
n=750
0.3
AI creates sustainable value through strategic capital allocation, especially when firms maintain effective governance mechanisms. Firm Productivity positive combined sustainable value (sustainability and financial outcomes)
Reading fidelity high
Study strength medium
n=750
0.3

Notes