Adopsi Artificial Intellegence, Pengungkapan ESG, dan Kinerja ESG pada Perusahaan Publik Indonesia
DOI:
https://doi.org/10.55606/jumia.v4i3.4467Keywords:
Artificial Intelligence Adoption, ESG Disclosure, ESG Performance, Moderated Regression Analysis, Refinitiv ESGAbstract
This study examines the effect of ESG disclosure on ESG performance and investigates the moderating role of Artificial Intelligence (AI) adoption in this relationship. The population comprises companies listed on the Indonesia Stock Exchange (IDX) during 2022–2024. Using purposive sampling, 20 companies with 60 firm-year observations were selected based on the availability of annual reports, GRI 2021-based sustainability reports, and Refinitiv (LSEG) ESG scores. A quantitative approach was applied using secondary data from annual reports, sustainability reports, corporate websites, and the IDX. ESG disclosure was measured using the GRI Disclosure Index, ESG performance using Refinitiv ESG scores, and AI adoption through a text-based analysis of AI-related keywords in corporate reports. The novelty lies in integrating text-based AI adoption measures with ESG disclosure and Refinitiv ESG performance data in an emerging market context. Hypotheses were tested using Moderated Regression Analysis (MRA) with SPSS 27 after classical assumption tests. Results show that ESG disclosure and AI adoption do not significantly affect ESG performance, and AI adoption does not moderate their relationship. Thus, AI adoption alone is insufficient to transform ESG disclosure into measurable ESG performance.
References
Akbarighatar, P. (2025). Operationalizing responsible AI principles through responsible AI capabilities. AI and Ethics, 5(2), 1787–1801. https://doi.org/10.1007/s43681-024-00524-4
Amarna, K., Garde Sánchez, R., López-Pérez, M. V., & Marzouk, M. (2024). The effect of environmental, social, and governance disclosure and real earning management on the cost of financing. Corporate Social Responsibility and Environmental Management, 31(4), 3181–3193. https://doi.org/10.1002/csr.2740
Appelbaum, D., Kogan, A., & Vasarhelyi, M. A. (2017). Big data and analytics in the modern audit engagement: Research needs. Auditing: A Journal of Practice & Theory, 36(4), 1–27. https://doi.org/10.2308/ajpt-51684
Aragón-Correa, J. A., & Sharma, S. (2003). A contingent resource-based view of proactive corporate environmental strategy. Academy of Management Review, 28(1), 71–88. https://doi.org/10.5465/amr.2003.8925233
Bang, Y.-Y., Lee, D. S., & Lim, S.-R. (2019). Analysis of corporate CO2 and energy cost efficiency: The role of performance indicators and effective environmental reporting. Energy Policy, 133, 110897. https://doi.org/10.1016/j.enpol.2019.110897
Benvenuto, M., Aufiero, C., & Viola, C. (2023). A systematic literature review on the determinants of sustainability reporting systems. Heliyon, 9(4), e14893. https://doi.org/10.1016/j.heliyon.2023.e14893
Chang, Y., Du, X., & Zeng, Q. (2021). Does environmental information disclosure mitigate corporate risk? Evidence from China. Journal of Contemporary Accounting & Economics, 17(1), 100239. https://doi.org/10.1016/j.jcae.2020.100239
Chen, X., & Ge, L. (2025). Artificial intelligence and corporate ESG performance: Evidence from China. Applied Economics Letters, 1–7. https://doi.org/10.1080/13504851.2025.2606145
Davenport, T. H., Ronanki, R., & others. (2018). Artificial intelligence for the real world. HBR’s 10 Must, 67.
De Silva Lokuwaduge, C. S., & De Silva, K. M. (2022). ESG risk disclosure and the risk of green washing. Australasian Business, Accounting and Finance Journal, 16(1), 146–159. https://doi.org/10.14453/aabfj.v16i1.10
Del Gesso, C., & Lodhi, R. N. (2025). Theories underlying environmental, social and governance (ESG) disclosure: A systematic review of accounting studies. Journal of Accounting Literature, 47(2), 433–461. https://doi.org/10.1108/JAL-08-2023-0143
Dienes, D., Sassen, R., & Fischer, J. (2016). What are the drivers of sustainability reporting? A systematic review. Sustainability Accounting, Management and Policy Journal, 7(2), 154–189. https://doi.org/10.1108/SAMPJ-08-2014-0050
Donaldson, T., & Preston, L. E. (1995). The stakeholder theory of the corporation: Concepts, evidence, and implications. Academy of Management Review, 20(1), 65–91.
Eccles, R. G., Ioannou, I., & Serafeim, G. (2014). The impact of corporate sustainability on organizational processes and performance. Management Science, 60(11), 2835–2857. https://doi.org/10.1287/mnsc.2014.1984
Farisyi, S., Musadieq, M. A., Utami, H. N., & Damayanti, C. R. (2022). A systematic literature review: Determinants of sustainability reporting in developing countries. Sustainability, 14(16), 10222. https://doi.org/10.3390/su141610222
Feng, B., Chen, X., & Tang, H. (2026). AI-driven green governance: Assessing the impact of artificial intelligence on corporate sustainability performance. Journal of Innovation & Knowledge, 11, 100869. https://doi.org/10.1016/j.jik.2025.100869
Freeman, R. E. (2010). Strategic management: A stakeholder approach. Cambridge University Press. https://doi.org/10.1017/CBO9781139192675
Friede, G., Busch, T., & Bassen, A. (2015). ESG and financial performance: Aggregated evidence from more than 2000 empirical studies. Journal of Sustainable Finance & Investment, 5(4), 210–233. https://doi.org/10.1080/20430795.2015.1118917
Ghozali, I. (2021). Aplikasi analisis multivariat (Edisi ke-10). Badan Penerbit Universitas Diponegoro.
Giese, G., Lee, L.-E., Melas, D., Nagy, Z., & Nishikawa, L. (2019). Foundations of ESG investing: How ESG affects equity valuation, risk, and performance. The Journal of Portfolio Management, 45(5), 69–83. https://doi.org/10.3905/jpm.2019.45.5.069
Handajani, L., Sokarina, A., & Hamdani Husnan, L. (2026). Signaling sustainability: The impact of ESG risk and sustainability awards on the performance of ESG-leader firms. Cogent Business & Management, 13(1), 2627674. https://doi.org/10.1080/23311975.2026.2627674
Hart, S. L. (1995). A natural-resource-based view of the firm. Academy of Management Review, 20(4), 986–1014. https://doi.org/10.2307/258963
Hart, S. L., & Dowell, G. (2011). Invited editorial: A natural-resource-based view of the firm: Fifteen years after. Journal of Management, 37(5), 1464–1479. https://doi.org/10.1177/0149206310390219
Li, Y., Gong, M., Zhang, X.-Y., & Koh, L. (2018). The impact of environmental, social, and governance disclosure on firm value: The role of CEO power. The British Accounting Review, 50(1), 60–75. https://doi.org/10.1016/j.bar.2017.09.007
Liu, X., Cifuentes-Faura, J., Zhao, S., Wang, L., & Yao, J. (2025). Impact of artificial intelligence technology applications on corporate energy consumption intensity. Gondwana Research, 138, 89–103. https://doi.org/10.1016/j.gr.2024.09.003
Mikalef, P., & Gupta, M. (2021). Artificial intelligence capability: Conceptualization, measurement calibration, and empirical study on its impact on organizational creativity and firm performance. Information & Management, 58(3), 103434. https://doi.org/10.1016/j.im.2021.103434
Mulyana, D., Widyaningsih, A., Rozali, R. D. Y., & others. (2025). Advancing sustainability through artificial intelligence: Implications for firm value in Indonesia. Jurnal Akuntansi, 29(1), 148–170. https://doi.org/10.24912/ja.v29i1.2774
Naveed, K., Farooq, M. B., Zahir-Ul-Hassan, M. K., & Rauf, F. (2025). AI adoption, ESG disclosure quality and sustainability committee heterogeneity: Evidence from Chinese companies. Meditari Accountancy Research, 33(2), 708–732. https://doi.org/10.1108/MEDAR-02-2024-2374v
Raimo, N., Caragnano, A., Zito, M., Vitolla, F., & Mariani, M. (2021). Extending the benefits of ESG disclosure: The effect on the cost of debt financing. Corporate Social Responsibility and Environmental Management, 28(4), 1412–1421. https://doi.org/10.1002/csr.2134
Russell, S. J., & Norvig, P. (2016). Artificial intelligence: A modern approach. Pearson.
Saha, R., & Maji, S. G. (2025). Does environmental, social, and governance (ESG) disclosure matter for carbon intensity? Evidence from S&P 500 firms. Journal of Environmental Management, 387, 125809. https://doi.org/10.1016/j.jenvman.2025.125809
Seow, R. Y. C. (2024). Determinants of environmental, social, and governance disclosure: A systematic literature review. Business Strategy and the Environment, 33(3), 2314–2330. https://doi.org/10.1002/bse.3604
Siddique, M. A., Karim, S., Haque, M. R., & Mia, P. (2026). The truth behind sustainability claims: Examining carbon risk, ESG disclosures, and greenwashing. International Review of Financial Analysis, 109, 104735. https://doi.org/10.1016/j.irfa.2025.104735
Sun, Y. (2024). The real effect of innovation in environmental, social, and governance (ESG) disclosures on ESG performance: An integrated reporting perspective. Journal of Cleaner Production, 460, 142592. https://doi.org/10.1016/j.jclepro.2024.142592
Tao, C., Zheng, M., & Huang, R. (2025). AI implementation and corporate ESG performance: Evidence from SMPP adoption. Asia-Pacific Journal of Accounting & Economics, 1–30. https://doi.org/10.1080/16081625.2025.2473334
Tsang, A., Frost, T., & Cao, H. (2023). Environmental, social, and governance (ESG) disclosure: A literature review. The British Accounting Review, 55(1), 101149. https://doi.org/10.1016/j.bar.2022.101149
Vial, G. (2019). Understanding digital transformation: A review and a research agenda. The Journal of Strategic Information Systems, 28(2), 118–144. https://doi.org/10.1016/j.jsis.2019.01.003
Warner, K. S. R., & Wäger, M. (2019). Building dynamic capabilities for digital transformation: An ongoing process of strategic renewal. Long Range Planning, 52(3), 326–349. https://doi.org/10.1016/j.lrp.2018.12.001
Zhang, C., & Yang, J. (2024). Artificial intelligence and corporate ESG performance. International Review of Economics & Finance, 96, 103713. https://doi.org/10.1016/j.iref.2024.103713v
Zhao, P., Gao, Y., Wu, M., & Sun, X. (2024). How artificial intelligence affects carbon intensity: Heterogeneous and mediating analyses. Environment, Development and Sustainability, 28(1), 2301–2325. https://doi.org/10.1007/s10668-024-05085-4
Zhou, Y., & Bu, W. (2026). Artificial intelligence adoption, energy management, and corporate energy transition: Evidence from energy consumption, energy intensity, and carbon emission intensity. Energies, 19(3), 821. https://doi.org/10.3390/en19030821
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