Skip to main navigation menu Skip to main content Skip to site footer

The synergy of digital innovation and green economy: A systematic review of mechanisms, challenges, and adaptive strategies in the post-Al era

Abstract

Digital transformation and the green transition increasingly co-evolve through shared infrastructures (data, energy, and institutions), yet their interaction is not automatically synergistic. This review synthesizes peer-reviewed research and authoritative institutional reports to clarify how digital technologies—especially AI, analytics, and platform infrastructures—shape green economic outcomes, and how environmental constraints and governance feedback reshape digital diffusion. We organize evidence around four domains: (i) labor-market restructuring under AI and digitalization, with attention to wage polarization, rents, and institutional mediators; (ii) skills mismatch and SME adoption constraints as a binding bottleneck for inclusive digital-green upgrading; (iii) the convergence of green finance and computing, where automated ESG assessment expands monitoring capacity but also amplifies measurement divergence and greenwashing risks; and (iv) sustainable infrastructure and energy transition, focusing on hydrogen value chains and the energy footprint of digital systems (data centers and AI workloads). A sectoral case—digital tourism—illustrates both substitution potential (virtual experiences, demand management) and rebound risks. Evidence converges on a conditional-synergy thesis: digital tools can accelerate green innovation and emissions reductions when coupled with credible standards, auditability, clean power, and workforce capability building; absent these complements, digitalization may increase electricity demand, widen inequality, and incentivize strategic disclosure. The review identifies three research gaps that limit policy inference: long-horizon causal evidence on non-linear coupling between digitalization and decarbonization, joint modeling of distributional outcomes and environmental performance, and integrated evaluation of AI-enabled sustainable finance under heterogeneous disclosure regimes. We propose a future agenda that prioritizes enforceable AI governance, life-cycle carbon accounting across hydrogen supply chains, and targeted SME capability policies.

Keywords

digital transformation, artificial intelligence, green finance, greenwashing, hydrogen, rebound effect, SMEs, sustainable tourism, built environment

PDF

References

  1. Acemoglu, D., & Restrepo, P. (2022). Tasks, automation, and the rise in U.S. wage inequality. Econometrica, 90(5), 1973–2016. https://doi.org/10.3982/ECTA19815
  2. Autor, D. H., Levy, F., & Murnane, R. J. (2003). The skill content of recent technological change: An empirical exploration. The Quarterly Journal of Economics, 118(4), 1279–1333. https://doi.org/10.1162/003355303322552801
  3. Berg, F., Kölbel, J. F., & Rigobon, R. (2022). Aggregate confusion: The divergence of ESG ratings. Review of Finance, 26(6), 1315–1344. https://doi.org/10.1093/rof/rfac033
  4. Equator Principles Association. (2020). The Equator Principles EP4. https://equator-principles.com/app/uploads/The-Equator-Principles_EP4_July2020.pdf
  5. Gössling, S., Balas, M., Mayer, M., & Sun, Y.-Y. (2023). A review of tourism and climate change mitigation: The scales, scopes, stakeholders and strategies of carbon management. Tourism Management, 95, Article 104681. https://doi.org/10.1016/j.tourman.2022.104681
  6. Gorovaia, N., & Makrominas, M. (2025). Identifying greenwashing in corporate-social responsibility reports using natural-language processing. European Financial Management. Advance online publication. https://doi.org/10.1111/eufm.12509
  7. Gu, Y., & Kharytonova, V. A. (2025). The built environment and economic context: Impacts on enterprise operations, mechanisms, and adaptive strategies. Journal of Sustainable Built Environment, 2(6). https://doi.org/10.70731/a6pdh022
  8. Gu, Y., & Lukin, S. (2025). Employment effects of digital economy: The role of SMEs in bridging skill mismatch. International Journal of Multidisciplinary Research, 1(2), 112–118. https://doi.org/10.65231/ijmr.v1i2.61
  9. Gu, Y., & Wang, Y. (2025). The impact of artificial intelligence on labor market income inequality. International Journal of Advanced Science, 1(2), 8–13. https://doi.org/10.70731/28ahd093
  10. Gu, Y., Feng, G., & Li, Y. (2025). Research on the impact mechanism of environmental economics on study tour education: Transnational cases and student capacity building. Journal of Global Trends in Social Science, 2(8), 46–52. https://doi.org/10.70731/hyc94503
  11. Gu, Y., Lin, H., Zhao, W., Li, M., & Wang, X. (2025). The ethical balance reconstruction of green finance empowered by computer technology. International Journal of Accounting and Economics Studies, 12(6), 580–586. https://doi.org/10.14419/ca6cas51
  12. Gu, Y., Pan, D., Yang, N., & Wang, X. (2025). Research on storage and transportation cost control and technological breakthroughs from the perspective of global hydrogen energy development. Journal of Sustainable Built Environment, 2(5), 33–38. https://doi.org/10.70731/9ygthr89
  13. Gu, Y., Wang, Y., Wang, X., & Wang, Z. (2025). Research on the development mechanism and practical path of digital tourism economy under environmental constraints. Journal of Global Trends in Social Science, 2(10). https://doi.org/10.70731/bbwczm87
  14. International Energy Agency. (2024). Global hydrogen review 2024. https://www.iea.org/reports/global-hydrogen-review-2024
  15. International Energy Agency. (2025a). Energy and AI: Executive summary. https://www.iea.org/reports/energy-and-ai/executive-summary
  16. International Energy Agency. (2025b). Energy demand from AI. https://www.iea.org/reports/energy-and-ai/energy-demand-from-ai
  17. Lagasio, V. (2024). ESG-washing detection in corporate sustainability reports. International Review of Financial Analysis, 96, Article 103742. https://doi.org/10.1016/j.irfa.2024.103742
  18. Lange, S., Pohl, J., & Santarius, T. (2020). Digitalization and energy consumption. Does ICT reduce energy demand? Ecological Economics, 176, Article 106760. https://doi.org/10.1016/j.ecolecon.2020.106760
  19. Lenzen, M., Sun, Y.-Y., Faturay, F., Ting, Y.-P., Geschke, A., & Malik, A. (2018). The carbon footprint of global tourism. Nature Climate Change, 8, 522–528. https://doi.org/10.1038/s41558-018-0141-x
  20. Li, H., Liu, Z., & Hachard, V. (2024). Digital transformation driving green innovation: Evidence from Chinese A-share firms. International Review of Economics & Finance. Advance online publication. https://doi.org/10.1016/j.iref.2024.103487
  21. Liu, X., et al. (2025). Green finance, carbon emission intensity, and digital economy: Nonlinear effects and mechanisms. Cleaner Environmental Systems. https://doi.org/10.1016/j.cesys.2025.100XXX
  22. Meerow, S., Newell, J. P., & Stults, M. (2016). Defining urban resilience: A review. Landscape and Urban Planning, 147, 38–49. https://doi.org/10.1016/j.landurbplan.2015.11.011
  23. Nipper, M., Ostermaier, A., & Theis, J. (2025). Mandatory disclosure of standardized sustainability metrics: The case of the EU Taxonomy Regulation. Corporate Social Responsibility and Environmental Management, 32(2), 2171–2190. https://doi.org/10.1002/csr.3046
  24. OECD. (2023a). OECD employment outlook 2023: Artificial intelligence and the labour market. OECD Publishing. https://doi.org/10.1787/08785bba-en
  25. OECD. (2023b). OECD skills outlook 2023: Skills for a resilient green and digital transition. OECD Publishing. https://doi.org/10.1787/27452f29-en
  26. Page, M. J., McKenzie, J. E., Bossuyt, P. M., et al. (2021). The PRISMA 2020 statement: An updated guideline for reporting systematic reviews. BMJ, 372, Article n71. https://doi.org/10.1136/bmj.n71
  27. Peng, H. R., & Qin, X. (2024). Digitalization as a trigger for a rebound effect of electricity use. Energy, 300, Article 131585. https://doi.org/10.1016/j.energy.2024.131585
  28. Rockall, E. J., Tavares, M. M., & Pizzinelli, C. (2025). AI adoption and inequality (IMF Working Paper No. 2025/068). International Monetary Fund. https://doi.org/10.5089/9798229006828.001
  29. Talwar, S., Kaur, P., Escobar, O., & Lan, S. (2022). Virtual reality tourism to satisfy wanderlust without wandering: An unconventional innovation to promote sustainability. Journal of Business Research, 152, 128–143. https://doi.org/10.1016/j.jbusres.2022.07.032
  30. UNESCO. (2020). Education for sustainable development: A roadmap. https://doi.org/10.54675/YFRE1448
  31. Xie, M., Liao, X., & Yaguchi, T. (2025). The policy spatial footprint: Causal identification of land value capitalization using network-time exposure. Land, 14(11), 2240. https://doi.org/10.3390/land14112240
  32. Yu, Y., Zhang, J. Z., Cao, Y., & Kazancoglu, Y. (2021). Intelligent transformation of the manufacturing industry for Industry 4.0: Seizing financial benefits from supply chain relationship capital through enterprise green management. Technological Forecasting and Social Change, 172, Article 120999. https://doi.org/10.1016/j.techfore.2021.120999
  33. Wang, J., et al. (2023). Digital transformation empowers ESG performance in the manufacturing sector. SAGE Open. https://doi.org/10.1177/21582440231204158