The role of artificial intelligence in achieving environmental goals
By Horacio Morell
President IBM Spain, Portugal, Greece and Israel
The Corporate Sustainability Reporting Directive (CSRD), which came into force in June, will require some 50,000 companies operating in the European Union (EU) to report on the carbon footprint of their value chains, among other obligations.
However, the CSRD is just one of a growing number of regulations being introduced around the world that require companies to report on their environmental impact. There are already a number of technologies that are helping us to respond to climate change and move towards sustainability goals. Chief among these are artificial intelligence (AI) and, specifically, generative AI. These technologies can also help responsible entities identify hotspots and opportunities to reduce their emissions across the value chain by including advanced data analytics in their environmental management program.
The potential of this type of AI models - called foundational models - lies in the fact that they are trained with massive volumes of generic data to learn language patterns and structures, and then tuned with task-specific data to generate results to more specific contexts or targets. Foundational models are extremely powerful, versatile, and can be used to quickly perform tasks with minimal or no training or supervision, giving us scalability and productivity.
So how can companies use AI and generative AI to help meet their environmental goals?
Need vs. capacity for action
Leading companies have already embraced sustainability: 95% of executives stated in a recent IBM Institute of Business Value survey entitled "The ESG Data Conundrum" that their company has developed a value proposition around environmental and social goals. Seventy-two percent even believe that sustainability is a key driver of revenue generation. However, despite these objectives, the same survey revealed that only 10% have made significant progress.
To close the gap, we need to address the data challenge, and this is where generative AI comes in. CEOs face pressure to embrace generative AI while weighing data management needs for AI to succeed. Our recent study "The Power of AI: Sustainability" indicates that 77% of CEOs pursuing transformative sustainability expect work processes across their organization to be digitized and leverage AI automation by 2025. Another 46% of executives see AI as important in driving their company's sustainability efforts.
The magnitude of this challenge was highlighted in a recent United Nations report which revealed that current corporate targets will only reduce emissions by 5-10% by 2030. To reach the "Zero Net Emissions" target by 2050, a 45% reduction in emissions will be required. It is therefore reasonable to expect stricter environmental standards in the not too distant future.
Given the magnitude and complexity of information and improving their sustainability goals, companies should already be considering the use of AI to evaluate scenarios and model decisions to improve performance. Failure to act now will leave the company at a disadvantage with potentially detrimental results.
Leveraging AI to identify opportunities
If applied properly, AI is not limited to collecting and analyzing data for daily reporting, but can also provide deeper insights that can be applied for additional benefits. For example, it can be used to identify and eliminate unnecessary process steps, saving time and money and potentially helping to reduce emissions.
For example, AI-based analytics can be used to monitor a company's energy consumption and detect areas for improvement, enabling companies to take proactive steps to reduce their carbon footprint. This is highly advantageous, as the drive towards more environmentally sustainable operations is growing.
The potential of generative AI lies in its ability to process large volumes of data, extract its context, and enable querying and interacting with it using natural language. It can also help decipher unstructured or opaque data, categorize the requirements of complex regulations and internal policies, and identify and analyze the causes that may affect progress toward sustainability goals.
Addressing the challenges associated with environmental reporting
Reporting of emissions, including supply chain emissions, is a requirement of the CSR Directive. The complexity associated with quantifying such emissions makes it impossible to use traditional reporting practices. Manually examining data to calculate carbon emissions is not only error-prone, it is unwieldy, time-consuming, expensive and can lead to unreliable audit results.
Companies need information management mechanisms that are automated, scalable and reliable. It's all very well to make environmental, social and corporate governance commitments, but the important thing is to demonstrate exactly how those goals have been met. That's why companies are increasingly exploring how generative AI and large linguistic models can streamline reporting, improve quality and reduce costs.
Organizations already have specific systems in place for a range of activities, such as human resource management and financial accounting. It seems natural that the time has now come to implement a specialized software platform - supported by AI - to capture data and calculate emissions, monitor sustainability initiatives and evaluate feedback from the supply chain to make the process easier, more reliable and transparent.
Socially and environmentally responsible companies understand the need to anticipate, prepare for and manage business risks, including those caused by climate change. Technology can help businesses in this regard. IBM's Environmental Intelligence Suite can help users monitor and plan for extreme weather conditions and IBM Maximo can identify preventive maintenance actions that help users improve sustainability while maintaining optimal asset performance and efficiency.
Moreover, regulations on the reporting of environmental, social and governance issues affecting a company are becoming increasingly stringent. The CSRD requires companies to disclose environmental information along with anti-corruption and bribery processes, corporate governance and diversity, equity and inclusion (DEI).
Generative AI can be a key tool in the process, helping organizations prepare for compliance, strengthen ESG reporting, leverage efficiencies and streamline business processes, with platforms such as IBM Envizi helping to accelerate adoption and automate the capture of sustainability-related data.
Preparing for the future
The climate crisis is not going away. Organizations must adopt new tools and technology solutions that enable them to make more informed decisions. Deploying generative AI capabilities can help organizations better understand their operations and identify opportunities to improve their environmental performance, including reducing greenhouse gas (GHG) emissions.
There is no doubt that focusing on meeting environmental targets can be difficult. However, for responsible companies it is not optional. Moreover, the CSRD, for example, will not only create new and detailed sustainability reporting requirements. Mandatory reporting requirements will go beyond environmental reporting to include social and governance measures, such as respect for human rights, anti-corruption and anti-bribery, corporate governance and diversity, equity and inclusion (DEI).
Using AI to meet these requirements will not only help ensure compliance, but can also strengthen ESG reporting and streamline business processes, which can lead to savings and productivity gains. What is clear is that the best performing companies will be those that embrace AI to adapt to change and reveal opportunities during the transition to a sustainable economy, the route to long-term value creation.
To ensure the use of effective, scalable and reliable AI models, it is essential that companies work with technology partners with a proven track record of developing and deploying systems that deliver results. It is also important to ensure that the chosen company has the ability to adapt to changing market requirements: implementing a digital service is the beginning of the journey, not the destination.
Horacio Morell, President IBM Spain, Portugal, Greece and Israel.
Horacio Morell has extensive experience in the IT sector and a deep knowledge of the Spanish and European market. He has been Vice President of Industry Solutions and Business Development at IBM Europe, where he has developed strategic cloud transformation and artificial intelligence projects for clients across Europe.
In addition, in his more than 20-year career at IBM, Horacio Morell has held multiple leadership responsibilities in the Spain, Portugal, Greece and Israel region, such as Vice President of Sales, between 2015 and 2019, and Director of Infrastructure Services, between 2012 and 2015. He also led client relationships in the financial sector in Spain.
Horacio Morell holds a degree in Economics and Business Administration from the Universidad San Pablo CEU and a Master's degree from the Instituto de Estudios Bursátiles de Madrid.
