AI and CSR

AI at the service of Corporate Social Responsibility: a winning duo?

Artificial intelligence (AI) is without doubt one of the most revolutionary technologies of our time. But behind its potential lie crucial questions about its environmental impact. How is AI becoming a major asset for strengthening CSR initiatives? Can it be both a threat to the environment and a lever for sustainable development and Corporate Social Responsibility (CSR)?

AI at the service of CSR: promising advances

Optimized ESG data collection and analysis

AI is revolutionizing the collection and analysis of ESG data, enabling real-time monitoring and continuous assessment of companies’ environmental, social and governance performance. Companies like Avisia have developed tools to automate data collection and pre-fill sustainability reports, making the process more efficient and accurate. Using AI, companies can analyze massive datasets to identify trends, patterns and opportunities for improvement in their CSR practices, including carbon footprint analysis, supply chain monitoring and assessment of the social impact of operations.

Supply chain optimization

For companies with complex supply chains, AI can be used to optimize the supply chain with the aim of reducing waste, improving efficiency and ensuring CSR compliance. Machine learning algorithms are used to forecast demand, optimize logistics routes and identify inefficiencies in the supply chain. For example, companies like Walmart are using AI systems to optimize fresh produce storage, reducing losses and minimizing the environmental impact associated with overproduction and food waste.*

Reducing GHG emissions

AI has become a key pillar of the global effort to reduce greenhouse gas emissions and promote environmental sustainability. AI systems are being integrated in a variety of fields, such as intelligent energy management, sustainable transport and natural resource management. For example, companies like Tesla use AI algorithms to optimize battery management and improve the energy efficiency of their electric vehicles. According to a McKinsey study, these improvements could reduce the automotive industry’s CO2 emissions by 15% by 2030.

The challenges of AI in CSR

An AI carbon footprint not to be overlooked

Despite its advantages, AI is energy-hungry. A query on an AI model, such as ChatGPT, can consume up to ten times more energy than a Google search. The use phase of AI models often consumes more energy than their drive phase, posing significant environmental challenges. What’s more, building and running the data centers needed to host these AI models also contributes to a significant carbon footprint. According to a study by Huawei analyst Anders Andrae**, data centers could consume up to 8% of the world’s electricity by 2030, largely due to the growing demand for AI and digital services. However, companies like Microsoft are committed to using data centers powered by renewable energies. In 2020, Microsoft announced its goal of becoming “carbon negative” by 2030, and eliminating by 2050 all the carbon footprint the company has emitted directly or through the use of electricity since it was founded in 1975.

Rebound effects: towards responsible use of AI

Efficiency gains achieved through AI can sometimes be offset by an increase in production or utilization, a phenomenon known as the rebound effect. To maximize environmental benefits, it is crucial to transform not only practices, but also business models. Take Ekimetrics, a European leader in data science and AI solutions. In 2023, Ekimetrics affirmed its commitment to using AI to promote sustainable and responsible practices by becoming a mission-driven company. This commitment led to the modification of the company’s articles of association to include its raison d’être: “To make Data Science and Artificial Intelligence the gas pedal of sustainable organizational transformation”.

For the use of AI to be truly responsible, it is also essential to train and raise awareness among users and employees of its environmental and ethical implications. For example, internal training programs can be set up to educate teams on optimizing processes via AI while reducing potential negative impacts.

In conclusion, AI offers considerable opportunities to strengthen corporate CSR initiatives. For AI to make an effective contribution to CSR, its use needs to be well thought-out and well supervised. This implies transparent and democratic data governance, oriented towards the common good. By focusing on specific, useful uses, such as waste reduction, eco-design and predictive maintenance, AI can support a more inclusive ecological and social transition. “The AI revolution is opening up exciting new prospects,” says Audrey Azoulay, Director-General of UNESCO. “But we must ensure that it is used for the benefit of our societies and their sustainable development “***.

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