Submit a Manuscript to the Journal
Journal of Marketing Management
For a Special Issue on
Tackling AI and Sustainability: The good, the bad, and the ugly
10 February 2025
Tackling AI and Sustainability: The good, the bad, and the ugly
Sustainability is understood as a societal development where the fulfilment of the needs in the present does not come at the expense of future generations; it is a task that requires the solving of highly complex scenarios. In the face of the mounting environmental and social ‘grand challenges’ (i.e. United Nations Sustainable Development Goals) facing the world, sustainability has become a significant research domain spanning a broad range of disciplines, including development, marketing and consumption, strategy, business models, circular economy, blockchain, environmental studies, and well-being.
Artificial Intelligence (AI) has been defined as “machines that mimic human intelligence in tasks such as learning, planning, and problem-solving through higher-level, autonomous knowledge creation” (De Bruyn et al., 2020, p. 93). Much research has been developed in this area to examine broad applications of AI, as well as more focused types of AI technologies, across a variety of fields. Topics in this vein include Generative AI, OpenAI, Augmented Reality (AR), Virtual Reality (VR), chatbots, service robots and machine learning.
In practice, sustainability transitions and the growth of AI have unleashed unprecedented impact on societal ‘business as usual’, bringing with them major transformations across all walks of life. As such, the two phenomena figure as leading topics on the agendas of decision-makers globally. New business models have emerged to comply with the sustainability transition demands, such as the Sustainable Business Model by de Sousa Jabbour (2019), the Circular Business Model by De Angelis (2018) and Enacting Voluntary Simplicity by McGouran and Prothero (2016). There have also been seminal works in AI focusing on topics such as the use of service robots for service excellence (Wirtz et al., 2021), the role of AR in purchasing behaviour (Kowalczuk et al., 2021), and in-store VR usage (Han et al., 2020).
AI has developed considerably in the last few years, with three main types of AI being commonly used across sectors and in everyday life; these being (1) Artificial Narrow Intelligence (ANI), (2) Artificial General Intelligence (AGI), and (3) Artificial Super Intelligence (ASI). Accordingly, such developments may be seen as a constructive avenue through which to tackle the complexity of societal grand challenges. AI technologies, such as chatbots, service robots, Augmented Reality (AR) and Virtual Reality (VR) have already made significant inroads in revolutionising the retail and service sectors through providing additional consumer touchpoints and a wider range of consumer services. For example, within the retail sector, the IKEA app augments furniture into a room through the user’s camera screen, whilst the Dulux app augments paint colour options on a user’s wall, potentially reducing waste and energy in consumer access and no longer wanted purchases. Additionally, within the gaming sector, brands have entered collaborations whereby a gamer can buy “skins” (or outfits) for their Avatar (or character); for example, Gucci and North Face partnered with Pokémon Go whereby the characters could wear the latest e-fashion.
AI has even stretched to be more widespread, in the development of smart cities and in unleashing the power of blockchain. For example, AI has been implemented in speed camera technology from being able to identify vehicle type to identifying drivers using their phones while driving, demonstrating the practicality of AI in social sustainability. Likewise, the integration of AI in blockchain has been likened to ‘King Kong meets Godzilla’ in countering fake data and content in AI, whilst at the same time improving the efficiencies, security and introducing new features in blockchain. From a strategy perspective, this move extends unique opportunities to inform innovative business models development aligned with sustainability transitions (Darwish, 2023). Such widespread AI usage is even seen within social media through use of “filters” enabled by AR overlays of the camera image. TikTok is the second highest used social media app in the world and has seen many trending videos that are developed with either subtle or extreme AI filters, of which reports have found both positive and negative effects on user well-being.
Despite the exponential growth of research within both sustainability and AI, as well as their individual impact on societies worldwide, the two domains have tended to develop in parallel. The stark lack of ‘decussate’ (Binder & Wade, 2024) between the fields has resulted in an underdeveloped understanding of the intersect between sustainability and AI, and their combined societal implications.
At first instance, the above examples point to the potential multi-vector positive reach of AI in driving the transition towards sustainable practices, from buying digital apparel and being more cognisant in decision-making (Joerß et al., 2021), to transforming business models and innovation practices that help accelerate the transition towards sustainable/circular economic growth (Darwish, 2023). However, increasingly, scholars are beginning to raise “the complex and often alarming ways in which the use of IT affects organisational and social life” (Mikalef et al., 2022, p. 257). This points to an existence of a “dark side” of AI in its impact on societal sustainability, whether in the form of intentional misuses or emerging as an unintended negative consequence, that requires detailed scrutiny. For example, consumer research shows that the integration of AR is likely to drive purchase behaviours (Nikhashemi et al., 2021). AI may also inspire impulse buying (Bottger et al., 2017), such as where consumers using the IKEA app may use it as an idea generator and browsing tool which could increase spontaneous/unplanned purchases (Chen et al., 2022; Trivedi et al., 2022). Furthermore, the increasing use of “beauty filters” on social media can not only encourage purchasing of beauty products and treatments to attempt to recreate the augmented self in the real world but, and perhaps more importantly, the potential unintended effect resultant from the increased self-discrepancy gap signals considerable harm to emotional wellbeing in the longer term (Terán et al., 2020).
Accordingly, the long-awaited debates surrounding AI and its impact on environmental and social sustainability, such as excessive consumption and psychological wellbeing, has given rise to what we frame here as the “AI paradox”. We define AI-paradox as a seemingly illogical and/or contradictory outcome of the expected effect in the relationship between AI and sustainability. This paradox can be seen in several lights, including:
1. Positive impact on environment but negative impact on psychological wellbeing (e.g., purchasing skins for Avatars)
2. Positive effect on psychological wellbeing but negative impact on environment (e.g., online “retail therapy” based on algorithm recommendations)
3. Intended positive impact on environment but longer-term negative impact on environment (e.g., spontaneous purchasing caused by AR retailing apps)
4. Intended positive impact on wellbeing but longer-term negative impact on wellbeing (e.g., social media beauty filters)
5. Intended positive impact on wellbeing through automation of tasks and enjoyable experiences but negative impact on longer-term social sustainability (e.g., loss of employment, social isolation and loss of basic social skills).
From extant research in AI and sustainability fields, there appears to be an environmental sustainability vs. societal wellbeing debate. This special issue calls for papers investigating the notion of the AI-paradox across research disciplines and applications to gain understanding into the short- and long-term effects of AI on societal wellbeing, through the lens of environmental and social sustainability.
The full Call for Papers including suggested topics and references can be found at the JMM blog site: https://www.jmmnews.com/ai-and-sustainability/
Authors should submit manuscripts of between 8,000–10,000 words (excluding tables, references, captions, footnotes and endnotes). All submissions must strictly follow the guidelines for the Journal of Marketing Management. Please note the requirements to include a Summary Statement of Contribution, and to place figures and tables at their correct location within the text. Please also read the following guidelines prior to submitting your manuscript:
- Use of images: https://authorservices.taylorandfrancis.com/editorial-policies/images-and-figures/
- Use of third-party material: https://authorservices.taylorandfrancis.com/publishing-your-research/writing-your-paper/using-third-party-material/
- Ethical guidelines: https://authorservices.taylorandfrancis.com/editorial-policies/research-ethics-guidelines-for-arts-humanities-and-social-sciences-journals/
Manuscripts should be submitted online using the T&F Submission Portal. Authors should prepare and upload two versions of their manuscript (only use alpha-numeric characters or underscores in the filename). One should be a complete text, while in the second all document information identifying the author should be removed from the files to allow them to be sent anonymously to referees.
When uploading files authors will be able to define the non-anonymous version as “Manuscript - with author details”, and the anonymous version as “Manuscript - Anonymous”. To submit your manuscript to the Special Issue choose “Research Article” from the Manuscript Type list in the Submission Portal. On the next screen (Manuscript Details), answer ‘yes’ to the question ‘Are you submitting your paper for a specific special issue or article collection?’. A drop down menu will then appear and you should select the Special Issue Title from this list.