Significant role of AI in advancing environmental goals

Saudi Arabia has embarked on a journey of transformation that has seen the country make significant progress toward becoming one of the most advanced nations in the world, with Vision 2030 advancing economic and social reform.

As part of this journey, the Kingdom has placed an onus on driving sustainability across all aspects of business and society, launching programs and initiatives such as the National Environment Strategy: a framework for enhancing the effectiveness of the environmental sector and implementing environmental compliance across all industries.

Accordingly, environmental, social, and corporate governance has become a top priority for local leadership. This could be seen with the Saudi Exchange’s decision to issue ESG disclosure guidelines, engaging listed companies and encouraging them to report on their sustainable practices.

This is in keeping with the growing number of regulations being brought in around the globe that require businesses to report the environmental impact. There are several technologies already in place to help us respond to climate change and make progress toward sustainability goals. However, one area that holds powerful promise in helping companies assess value chain carbon footprint is artificial intelligence and generative AI. These tools can also help entities identify hotspots and opportunities to reduce their emissions across the value chain by infusing advanced data analytics into their environmental management program.

The potential of these types of AI models — referred to as foundation models — lies in the fact that they are trained on massive volumes of generic data to learn the patterns and structures of language, then fine-tuned on data from specific tasks or domains to generate output to more specific contexts or objectives. Foundation models are powerful, and versatile, and can be used to quickly perform tasks with minimal or no training or supervision. The recent open-sourced IBM and NASA geospatial AI datasets, for example, are intended to democratize access and application of AI to generate new innovations in climate and Earth science.

So, how can businesses use AI and Gen AI to help meet their environmental objectives?

Addressing challenges

Reporting emissions, including those from a value chain, is essential. The complexities associated with quantifying such emissions are making it intractable using traditional reporting practices. Manually sifting through data to calculate carbon emissions is not only error-prone, but unwieldy, time-consuming, expensive, and can result in an unreliable audit trail.

Companies require reporting mechanisms that are automated, scalable, and reliable. It is all well and good to make self-assured ESG commitments — the importance is in demonstrating how, exactly, you have met these targets. As a result, companies are increasingly exploring how Gen AI and large language models can streamline reporting, improve quality, and reduce cost.

In Saudi Arabia, AI-powered solutions are being leveraged to enable businesses and entities to problem-solve and overcome their challenges

Fahad Alanazi

Organizations have dedicated systems for a range of activities, such as HR management and financial accounting — environmental reporting should be no different. Implementing a specialized software platform — backed by AI — to capture data and calculate emissions, monitor sustainability initiatives, and assess supply chain feedback makes the process easier, more reliable, and transparent.

Leveraging AI

Today, AI promises a solution that can process vast volumes of data, interact using natural language, and extract pertinent insights specific to the needs of the user.

For instance, carbon capture and storage projects require a deep understanding of the earth’s subsurface and geological processes. Decades of oil and gas exploration and production at our client, Wintershall Dea, has created a vast subsurface knowledge base containing hundreds of thousands of documents. Traditionally, this valuable corpus of information was simply inaccessible to AI and advanced analytics. Today, however, Wintershall Dea and IBM Consulting have built a GPT-based knowledge extraction tool that allows users to ask specific questions of the provided subsurface knowledge base (tables and text) to evaluate whether certain areas can be used for CCS projects in terms of profitability, effectiveness, and safety. What’s more, the fusion of Gen AI capabilities with deep domain expertise from geologists and scientists can unlock new solutions and better ways of working.

In Saudi Arabia, AI-powered solutions are being leveraged to enable businesses and entities to problem-solve and overcome their challenges. More so than ever, AI is being utilized to put data to work with greater speed, accuracy, and efficiency.

Last year, IBM signed a strategic agreement with the Saudi Data and Artificial Intelligence Authority to promote the adoption of AI in the carbon capture and industrial domains.

As part of the deal, IBM, SDAIA, and the Ministry of Energy outlined plans to use AI to detect, map, and eventually reduce carbon emissions across the country.

IBM has also partnered with Saudi Aramco to build an innovation center in Riyadh: a state-of-the-art facility that will boost the development of a sustainable economy and explore how advanced technologies, such as AI, can be applied to overcome pressing sustainability challenges.

Notably, IBM was selected by the Water Transmissions and Technologies Co. — the largest water transmission company in the world — to automate over 175 of its business processes. In addition to accelerating the digital transformation of the company’s operations, IBM implemented the SAP Environment, Health, and Safety Module and governance, risk, and compliance module to equip WTTCO with the all-important tools to enhance its ESG efforts.

What we have seen is that AI-driven analytics can be used to monitor a company's energy consumption, discover areas for improvement, and create actionable frameworks to help organizations reduce their carbon footprint. This is advantageous as the momentum for more environmentally sustainable operations continues, and a company’s sustainability credentials become critical to economic success.

Reporting for a sustainable future

Responsible companies understand the need to anticipate, prepare for, and manage business risks, including those caused by climate change. Technology can help companies in this regard. IBM’s Environmental Intelligence Suite can help users monitor and plan for extreme weather and IBM Maximo can identify preventative maintenance actions that help users improve sustainability by maintaining optimal performance and efficiency of their assets.

Moreover, regulations on reporting the ESG aspects intersecting a company are increasing. Increasingly, companies are required to disclose environmental information alongside anti-corruption and bribery processes, corporate governance and diversity, equity, and inclusion.

Generative AI can be a key tool in the process, helping organizations prepare for regulatory compliance, bolster ESG reporting, harness efficiencies and streamline business processes.

Final words

To help with the selection of appropriate AI models and foundation models, businesses may consider partnering with technology providers with a proven track record of developing and implementing systems that deliver. The chosen partner must also have the capacity to adapt to changing market requirements — putting digital service in place is the start of a journey, not its destination.

What is clear is that the companies that fare best will be those that embrace AI to adapt to the changes and reveal opportunities during the transition to a sustainable economy.

• Fahad Alanazi is general manager of IBM KSA.