Digital Darwinism: Evolving Business Strategies for Climate Resilience

Jana Majerova (), Minh Cong Nguyen () and Subhankar Das ()
Additional contact information
Jana Majerova: Ambis University
Minh Cong Nguyen: Graduate School, Duy Tan University
Subhankar Das: Duy Tan University

A chapter in Generative AI for a Net-Zero Economy, 2025, pp 233-248 from Springer

Abstract: Abstract This chapter discusses Digital Darwinism, the fusion between AI and corporate strategies for climate resilience. It shows how AI improves climate risk assessment, supply chain design, and scenario planning by synthesising climate science, organisational theory, and technological innovation. With case examples, such as Shell’s renewable energy transition and Patagonia’s circular systems, the analysis shows how AI can empower organisations to create dynamic capabilities that optimise resource utilisation and enable climate future simulations. However, the double-edged nature of AI algorithmic bias, unequal access, and ethical dangers requires strong governance frameworks. The chapter explains that for companies to undergo a future-proof business transformation that enables them to excel within a net-zero economy, they must discard incremental ESG initiatives and create AI-driven embedded agility in their DNA. This requires multi-industry collaborations, equitable innovation, and ethical foresight, such that climate resilience is also a route to business continuity and custodianship of the planet.

Keywords: Digital Darwinism; Climate action; AI; Digital strategy; Supply chain; Ethics; Governance; Sustainable economy; Human capital; Agility (search for similar items in EconPapers)
Date: 2025
References: Add references at CitEc
Citations:

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-981-96-8015-3_14

Ordering information: This item can be ordered from
http://www.springer.com/9789819680153

DOI: 10.1007/978-981-96-8015-3_14

Access Statistics for this chapter

More chapters in Springer Books from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().