Navigating the complex interdependence of sustainability and AI
Right now, many companies are muddling through the challenges of reaching two huge goals – moving full speed ahead on the digital transformation of artificial intelligence (AI) while making substantial progress on sustainability initiatives.
The problem? In their race to optimize AI, many organizations seem to be ignoring the environmental and social impacts of AI’s technological advancements that threaten the core principles of sustainable, equitable growth. Disregarding the interconnectedness between AI and sustainability limits how companies can move their businesses forward comprehensively and strategically.
To better understand the interdependence of AI and sustainability, here are some key issues, examples, and resources that can help you optimize and integrate them more effectively:
Pay attention to how AI affects ESG’s incremental progress
According to Open AI researchers, since 2012, the computing power required to train cutting-edge AI models has doubled every 3.4 months. By 2040, it is expected that the emissions from the Information and Communications Technology (ICT) industry will reach 14 percent of the global emissions, with the majority of those emissions coming from the ICT infrastructure, particularly data centers and communications networks.
AI also raises significant questions about equity, access, and economic mobility, all key factors in how companies approach social governance and corporate responsibility. In the Brookings Institution’s latest report on AI’s impact on income inequality in the US, Senior Fellow Sam Manning notes that in the U.S. about 50-70 percent of the increase in wage inequality has been attributed to the introduction of new automation technologies.
While AI has certainly made important strides in how different industries can more effectively preserve resources and reduce environmental impact – precision agriculture, for instance – by and large, to quote Andrew Winston in his insightful article on AI and sustainability, “it’s going to be a tough race with radical demand growth.” Understanding how AI shapes your specific industry and intersects with your company’s core ESG initiatives is essential.
Align AI practices with broader ESG goals
With the knowledge that AI and sustainability are inextricably linked, companies should assess their most critical sustainability efforts and determine how they might be affected by AI resources. The Responsible AI Institute recently released “AI’s Impact on Our Sustainable Future: A Guiding Framework for Responsible AI Integration Into ESG Paradigm,” which provides a methodology that can be adapted to evolving frameworks. It’s an invaluable resource for organizations who need a comprehensive roadmap to realize the value of integrating relevant AI initiatives with those in ESG.
Learn from examples of how AI innovation can support sustainability
As the EU’s Corporate Sustainability Reporting Directive (CSRD) comes into effect, transparency in reporting is more important than ever. To support these efforts, Accenture partnered with Microsoft to help businesses harness generative AI, including developing copilots—digital assistants powered by generative AI—that facilitate data collection from diverse sources and generate qualitative data that meets required reporting standards.
Salesforce is another trailblazer in the strategic applications of AI in meeting sustainability goals. To reduce AI model emissions, Salesforce trained its models in lower-carbon data centers, powered by electricity that emits 68.8 percent less carbon than global average electricity. They’ve also taken care to customize AI for their specific purposes in sustainability, including developing domain-specific models instead of bowing to the trend towards large, general-purpose models, resulting in high-performing models that are smaller and more sustainable, cost-effective, and easier to fine-tune, improving the user experience.
Realize AI is not a silver-bullet solution but a tool that requires human-centered strategy
With an ever-evolving regulatory landscape, it’s tempting for companies to want to harness the seemingly immediate efficiency and automation AI provides to gather data, analyze processes, and produce suggestions for improvements. But, as the World Bank notes, “New governance frameworks, protocols, and policy systems are needed for the new digital era to ensure all-inclusive and equitable benefits. Societies need regulatory approaches that are not only human-led and human-centered but also nature-led and nature-centered. Government policies need to balance public interests, such as human dignity and identity, trust, nature preservation and climate change, and private sector interests, such as business disruptiveness and profits.”
With the promises and perils of AI evolving at lightning speed, companies should commit to creating, monitoring, and assessing a strategic integration of their AI and ESG initiatives.
Have an example of a successful use of AI within sustainability? Share with me and readers in the comments on LinkedIn.
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