There’s no doubt that AI is generating excitement across industries and is becoming integral to various aspects of our daily lives. In fact, investments in AI are expected to continue growing in the coming years.
While there is a lot of concern about regulating AI—rightfully so, it is equally important to consider and identify the ways AI can be used to drive sustainability goals. This is especially true for companies, as today’s investors prioritize responsible investments that address environmental and social sustainability issues arising from a company’s operations.
With all the buzz around AI’s potential, the question arises: How can AI help companies achieve their sustainability goals?
The AI-Sustainability Paradox
Interestingly, several companies have begun exploring the possibility of utilizing AI in their sustainability processes. A recent study by edX and Workplace Intelligence, which surveyed employees and C-suite leaders about their use of AI, revealed key insights.
The study’s most glaring finding is that 96% of C-suites at companies surveyed say that AI has improved their progress toward sustainable goals, and 75% believe that their company cannot achieve its sustainability goals without AI. However, despite this interest, 65% of executives are unsure how to use AI to improve sustainability.
Employees surveyed also reported that they aren’t being provided with adequate training on sustainability or AI or how to use AI to improve sustainability. Only 30% of employees surveyed say they have training on how AI can advance sustainability, while 55% expressed interest in such training opportunities.
Globally, the results show that nearly all employees in India use AI the most. In the UK and Canada, 77% of workers utilize AI, while France lags behind, with only 65% of employees utilizing AI.
Andy Morgan, head of edX For Business, suggests that India’s high engagement with AI can be attributed to “strong government support for AI initiatives, a heavy emphasis on STEM education, and India’s leadership in global IT services.” He further explains, “India has made significant investments in building AI skills across its workforce, ensuring that employees are well-positioned to use AI effectively.”
The United Nations Global Compact working in partnership with Accenture, has also issued an insightful report underscoring that not only should companies leverage generative AI, but that doing so is “critical” to drive progress on the Sustainable Development Goals.
According to the study, 97% of business leaders across industries identify generative AI as a key driver of reinvention in the next three to five years. This finding corroborates the edX and Workplace Intelligence study, emphasizing AI as a key tool for advancing sustainability efforts.
How AI is Being Used to Advance Sustainability Goals
Despite the challenges and risks that arise with the use of AI, AI has proven useful in addressing environmental and social sustainability issues across various sectors and areas. Here are a few examples:
- Enhancing inclusion: AI is being utilized to enhance assistive technologies for people with disabilities and to detect bias in recruitment, compensation, and workplace processes.
- Improving energy efficiency: AI can optimize energy consumption and minimize waste by analyzing usage patterns. It can predict peak times, adjust energy distribution in real time, and detect inefficiencies, leading to more sustainable energy management.
- Monitoring human rights violations: Generative AI can assist workers in agricultural supply chains by detecting high-risk areas for human rights violations and creating customized educational and training programs to address these issues.
- Workplace safety: AI can be employed to monitor occupational health and safety data in real-time, enabling the detection of potential hazards before they occur.
- Preserving Indigenous culture: UNESCO points out that many Indigenous communities are working to preserve their cultural heritage, and AI can be key in this effort. By digitizing Indigenous data, AI aids in recording, transmitting, and revitalizing knowledge, particularly for younger generations.
- ESG reporting: AI simplifies the creation of ESG reports, conserving time and resources while improving data accuracy. Tools like Salesforce’s Net Zero Cloud and Microsoft’s Sustainability Insights Copilot offer tailored insights and allow companies to benchmark progress.
However, it is also important to consider the potential downsides of AI. While AI has the potential to drive sustainability, its energy-intensive processes can actually hinder progress by increasing carbon emissions, especially when powered by non-renewable sources. Also, if built on biased datasets, AI can perpetuate and even entrench bias and discrimination.
As Hilda Kosorus, director of data and AI center of excellence for EMEA, Crayon, aptly notes in the UN Global Compact report, “it is not always about implementing the coolest algorithms but about generating value while factoring in ethical, security, and privacy considerations.”
The Disconnect: Why 65% of Executives Struggle
It is puzzling that executives believe that AI can make a difference, yet they struggle to leverage it effectively. This disconnect is attributable to factors relating to infrastructure, data management, and ethical concerns.
Andy Morgan, head of edX for Business, says, “One major factor is the sheer volume of data that needs to be processed and analyzed, which can be difficult without the right infrastructure in place.” He adds that navigating regulatory and ethical considerations regarding data privacy and compliance further complicates the issue.
To add to this, there aren’t any clear standards on AI and sustainability. “The lack of clear frameworks or industry standards on how AI can specifically be applied to sustainability efforts creates uncertainty, making it harder for executives to implement these solutions confidently,” says Morgan.
Training is a key factor in overcoming these challenges. Morgan emphasizes the importance of investing in technical skills. “To fully operationalize AI in these contexts, companies will need to invest in developing skills in data engineering, big data analysis, and cybersecurity to ensure compliance. Coding skills are also critical, as they form the foundation for any AI-driven solution,” he explains.
The goal, however, isn’t to become an AI expert, but for the workforce and executives to understand how AI can support sustainability goals while being mindful of the risks and challenges. As Brigid Evans, director of global policy at Pearson, puts it in the UN report: “Not everyone needs to be an AI expert, but everyone will be touched by AI. We therefore need to make sure that we invest in educating our workforce, so we can have a data literate workforce that is right for our strategy and needs.”
However, training isn’t without its hurdles, Morgan shares. Companies, especially small ones, may find it difficult to find the right expertise, align AI-driven sustainability initiatives with evolving laws and regulations, and manage the cost of adopting and implementing AI systems. Internal resistance to adopting new technologies, resulting from fears about AI taking over jobs, can also be a barrier.
To truly harness AI’s potential for sustainability, companies should consider investing in comprehensive AI training that empowers not just executives but employees at every level. This training should cover how AI can effectively address ESG challenges while also equipping employees with the skills to identify and mitigate potential risks. By encouraging teams to begin with small, measurable projects, companies can refine their approach and eventually scale AI-driven sustainability efforts across the organization.