Artificial Intelligence: A Potential Catalyst for Positive Social, Environmental, and Outcomes, According to a Report
Union Bancaire Privée (UBP), a leading Swiss private bank, has released a new impact report emphasising the potential of Artificial Intelligence (AI) in driving sustainable business models and generating measurable environmental and social benefits.
The report underscores UBP's focus on companies applying AI in ways that not only generate sustainable financial returns but also contribute positively to the environment and society. This approach is demonstrated in various sectors, from agriculture to healthcare, education, financial inclusion, and climate resilience.
In agriculture, AI-driven technologies like John Deere’s 'See & Spray' system are revolutionising farming practices. By using high-resolution cameras and AI to identify weeds, this technology enables targeted herbicide application, reducing chemical use by nearly 60%. This not only improves environmental outcomes by reducing chemical inputs but also promotes economic benefits through cost savings and product quality improvements.
In healthcare, AI is accelerating drug discovery and clinical trial design, enhancing treatment development efficiency and reducing costs. This contributes to better health outcomes and financial sustainability.
In education, AI is supporting equitable access to quality learning, fostering social equity and enabling sustainable economic growth.
For financial inclusion and impact investing, AI is improving screening and thematic mapping to identify companies aligning with impact goals. This helps investors integrate social and environmental impact with financial returns effectively.
In climate resilience, AI combined with geospatial data is enabling accurate assessments of nature-related risks. Companies like Nature Alpha are using AI to overlay geospatial data with corporate asset locations, helping investors and companies manage exposure to ecosystem degradation and extreme weather, thus driving environmental protection and risk mitigation.
However, the report also stresses the importance of transparency, explainability, and compliance with evolving regulatory standards in AI-driven decision making. The report states that AI is transforming equity investing and can be used for both good and bad depending on its application. The surging energy demands of AI could pose a threat to corporate net-zero commitments.
UBP held a roundtable in London to present its latest impact report, focusing on the duality of AI's potential for both emissions and sustainability solutions. Renewable energy firm Renalfa has secured €315M in funding from an EBRD-led investor group, while Trane Technologies is deploying AI-powered digital twins to optimise energy use across its asset base, reducing emissions at scale.
The Resonance housing initiative has welcomed tenants, and the related fund has since closed. AI is also being seen as a tool to support biodiversity preservation, such as through sustainable farming practices.
In conclusion, AI acts as an enabling technology that supports measurable environmental and social benefits embedded in practical applications while fostering sustainable business models. However, the technology's benefits must be balanced with rigorous governance and oversight to mitigate risks from biased data and ensure transparency and regulatory compliance.
- The Union Bancaire Privée (UBP) impact report highlights the potential of Artificial Intelligence (AI) in fostering business models that deliver tangible environmental and social benefits.
- In agriculture, AI is revolutionizing farming practices through technologies like John Deere’s 'See & Spray' system, reducing chemical use and promoting economic benefits.
- For financial inclusion and impact investing, AI is facilitating the identification of companies that align with impact goals, helping investors integrate social and environmental impact with financial returns.
- In climate resilience, AI combined with geospatial data is aiding accurate assessments of nature-related risks, helping companies manage exposure to ecosystem degradation and extreme weather.
- However, the report emphasizes the need for transparency, explainability, and compliance with evolving regulatory standards in AI-driven decision making to mitigate risks from biased data and ensure transparency and regulatory compliance.
