Special Issue for California Management Review 
Generative AI and acceleration of ESG Performance 
Guest Editors: 
Dr. Mark Esposito, Dr. Terence Tse, Dr. Yusaf Akbar, Dr. Alessandro Lanteri 
The call for papers for this special issue of the California Management Review (CMR) invites 
contributions that seek to comprehend the environmental, social, and governance (ESG) performance of 
firms in the age of generative artificial intelligence. This includes explorations of the challenges and 
opportunities for ESG performance, as well as the organizational characteristics and processes that 
establish high ESG performance. 
In recent years, the potential for generative AI to accelerate firms' ESG performance by allowing them to 
evaluate massive volumes of data and develop insights and solutions to complicated problems has been 
explored (Skaug Saetra et al., 2021) In this call for papers, the editors welcome research that seeks to 
understand how the application of generative AI--such as generative design (Alsakka et al., 2023), 
generative art (Liu et al., 2018) or generative texts (Pavlik, 2023)--in various aspects of business 
influences ESG performance. 
Some examples of business activities impacted by generative AI include, but are not limited to: 
1- Marketing: Many organizations are leaning toward adopting generative AI to create marketing
content such as images, videos, designs, text, and so on(Mayahi & Vidrih, 2022). In the fashion
sector, generative AI tools such as Khroma1 are used to generate images and designs. Studies also
have developed new algorithms and deep learning models such as PainNet to design generative 
fashion models for clothing (Lin et al., 2020). Data Grid, a Japanese technology firm, used the 
technology to create representative fashion models. Lastly, Spectrum uses generative AI to design 
its TV advertising2. Because the use of generative AI in marketing is still in its infancy, relatively 
little is known about how AI-generated marketing content affects ESG performance nor is there 
extensive research on the strategies and frameworks firms can use from a risk management 
perspective. 
2- Knowledge Management & Organizational Learning: The creation of educational text and
content at the organizational level is one of the primary functions of generative AI. Several firms
use knowledge management platforms and solutions to better manage their explicit and tacit 
knowledge and to increase knowledge levels throughout the organization. While AI-powered 
knowledge management systems, such as Lucy3, an AI-powered answer engine, are expected to 
alter enterprise knowledge management and organizational learning, there is scant understanding 
of how generative AI-enabled organizational learning (Baidoo-Anu & Owusu Ansah, 2023) and 
knowledge management affects ESG performance; and what business specifications are needed to 
maximize the effectiveness of such technology? 
3- Corporate Intelligence and Communication: Generative AI promises to change corporate
communication and the generation of organizational reports, as well as enhance corporate 
1 Khroma - The AI color tool for designers 
2 Spectrum Reach Introduces AI Ad Platform with Waymark | Charter 
3 Stronger Business Insights with AI-Powered Knowledge Management | Lucy

intelligence. Omdia4 generates AI-powered actionable insights for enterprises by analyzing and 
reporting on external occurrences. In this context, there is a lack of research relating ESG 
performance and the usage of AI-enabled market intelligence and communication tools. 
This special issue of CMR aims to provide meaningful managerial insights on how executives can 
develop successful environmental, societal, and governance mechanisms in the age of generative AI. 
Prior research has focused on the application of digital technologies and artificial intelligence as a catch-
all word for environmental sustainability (Bermejo & Juiz, 2023; Delgosha et al., 2021; Nishant et al., 
2020; Saheb et al., 2022; Skaug Saetra et al., 2021). In this special issue we welcome contributions 
focusing on any aspect of the ESG performance spectrum, including but not limited to: 
* identification of the ESG issues that are important to the business,
* consideration of ESG implications in strategic, financial, and operational decisions,
* engagement and collaboration with stakeholders,
* performance measurement and reporting
Earlier research has mainly focused on the environmental benefits of generative AI, such as the 
application of generative design for ecologically sustainable cities and urban growth (Dilibal et al., 2021; 
Toker & Pontikis, 2011). 
With the introduction of various and new forms of AI-generated content, more studies ought to be 
conducted to investigate especially the societal and governance performance of businesses. Further 
research is also needed to investigate the effects of generative AI in the form of texts, photos, and videos 
on ESG performance. 
Editor Biographies 
Mark Esposito is a Full Professor of Business and Economics at Hult International Business School, 
teaching across campuses in the area of Economics, Strategy, Foresights and Management of Technology, 
among some of his most common teaching areas. He is Co-Founder & Chief Learning Officer at Nexus 
FrontierTech, an AI scale-up venture. He was inducted in 2016 in the radar of Thinkers50 as one of the 30 
most prominent rising business thinkers in the world. Mark has held academic appointments for some of 
the world’s leading institutions such as Harvard University, University of Cambridge’s Judge Business 
School, and IE Business School. In his career he has written hundreds of op-eds and professional 
publications, over 150 articles, several book chapters, over 40 case studies and 13 books, including two 
bestsellers. 
Terence Tse is a Full Professor of Finance at Hult International Business School and an affiliate 
professor at ESCP Business School. Terence is also a co-founder and Executive Director of Nexus 
FrontierTech, an AI scale-up. He is a co-author of two international best sellers “The AI Republic: 
Building the Nexus Between Humans and Intelligent Automation” and “Understanding How the Future 
Unfolds: Using DRIVE to Harness the Power of Today's Megatrends.” His next book, “The Great 
Remobilization”, published by MIT Press, is to be released at the start of 2023. 
4 Home Page :: Omdia (informa.com)

Yusaf Akbar is a Full Professor of Management at Central European University in Vienna, Austria. His 
research interests are located at the intersection of business strategy, public policy, and business model 
innovation. Current research examines evolving sharing economy business models, non-market strategy 
and dynamic capabilities among others. He has published widely including around 100 articles, numerous 
book chapters and case studies as well as four books. His research has been published at the Journal of 
International Management, Journal of World Business, Harvard Business Review and International 
Business Review among others. 
Alessandro Lanteri is a Full Professor of Strategy and Innovation at ESCP Business School. His 
research has been published by leading international journals (Journal of Business Ethics, Philosophical 
Studies…) and publishers (Cambridge University Press, Palgrave Macmillan…), and has also appeared 
on leading practitioners outlets (Harvard Business Review and MIT Technology Review outlets, World 
Economic Forum Agenda and Forbes). His latest book “CLEVER. The Six Strategic Drivers for the 
Fourth Industrial Revolution” became a no.1 Amazon bestseller. He works with multinationals, 
governments, International Organizations, startups and family businesses across five continents. He also 
taught executive education programs for Saïd Business School University of Oxford and London 
Business School. He holds a Master in Economics from Bocconi University and a PhD in Philosophy and 
Economics from Erasmus University Rotterdam. 
Submission Information: 
-
Authors requesting advanced feedback on fit and feasibility of a contribution are welcome to
submit an extended abstract or full draft to the Guest Editors no later than September 1, 2023 
to: futureslab@hult.edu 
-
To be considered for publication in the special issue, authors must submit a full draft of their
papers no later than October 15, 2023 to the following email address:  futureslab@hult.edu 
-
The Guest Editors will then select the papers (approximately 12) that are most likely to result in a
first-rate, high-impact submission. Authors of these high-impact submissions will receive
feedback to help them revise and strengthen their papers as well as an official invitation to submit
through CMR’s online submission portal. 
-
The officially submitted manuscripts will then undergo a rigorous peer review process.
References: 
1.
Alsakka, F., Haddad, A., Ezzedine, F., Salami, G., Dabaghi, M., & Hamzeh, F. (2023).

Generative design for more economical and environmentally sustainable reinforced concrete 
structures. Journal of Cleaner Production, 387, 135829. 
https://doi.org/10.1016/J.JCLEPRO.2022.135829 
2.
Baidoo-Anu, D., & Owusu Ansah, L. (2023). Education in the Era of Generative Artificial
Intelligence (AI): Understanding the Potential Benefits of ChatGPT in Promoting Teaching and
Learning. SSRN Electronic Journal. https://doi.org/10.2139/SSRN.4337484
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https://doi.org/10.1016/j.jpdc.2023.02.006
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Owusu-Danquah, J. (2021). Data-Driven Generative Design Integrated with Hybrid Additive
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https://doi.org/10.1007/978-3-030-72139-8_10
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Lin, J., Song, X., Gan, T., Yao, Y., Liu, W., & Nie, L. (2020). PaintNet: A shape-constrained
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Liu, Y., Qin, Z., Wan, T., & Luo, Z. (2018). Auto-painter: Cartoon image generation from sketch
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https://doi.org/10.1016/J.NEUCOM.2018.05.045
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Mayahi, S., & Vidrih, M. (2022). The Impact of Generative AI on the Future of Visual Content
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Artificial Intelligence for Journalism and Media Education.
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