ESG & AI: Streamlining Sustainable Growth
Environmental, Social, and Governance (ESG) principles were introduced with a noble ambition—to protect our planet and foster a fairer society. Over the past decade, the concept of ESG has evolved significantly, rapidly gaining popularity and largely supplanting Corporate Social Responsibility strategies, thus influencing how organisations are perceived by the world, their competitors, and potential talent. However, due to a lack of standardised regulations and measurement systems, ESG’s rise led to a surge in greenwashing. Companies sought recognition for their contributions to social and environmental causes, often exaggerating their impact. This, in turn, prompted a significant increase in regulatory measures, defining the current landscape in which we find ourselves.
”Many find themselves overwhelmed and wishing to disengage”
TOO MUCH RED TAPE?
ESG initiatives are transforming traditional business models in real estate, introducing new regulations and changing how information systems are managed. With a 155% increase in mandatory reporting requirements for ESG actions in Europe between 2011 and 2022 according to the World Business Council for Sustainable Development, businesses find it challenging to “keep up”. The rapid growth of consultants and specialists in the ESG domain over the past years is notable amid the challenges in discerning their credibility and trustworthiness. Companies experience “ESG fatigue”—not only do they now have to bear the high costs and complex implementation of ESG initiatives, they also need to engage with external consultants to report on their positive actions, bringing additional costs, consuming time away from the core business, and ultimately undermining the purpose of benefitting the planet and society in the first place. Many find themselves overwhelmed and wishing to disengage from ESG activities altogether.
While the recent Omnibus package introduced by the European Commission at the end of February proposes to postpone the implementation of the Corporate Sustainability Reporting Directive by two years and scale back ESG-related disclosures relating to value-chain impacts, it is clear that ESG is here to stay. Companies must develop broad-based strategies not only to meet ESG requirements and targets, but to mitigate ESG-related risks. Is there a method to streamline the adoption, implementation, and reporting of ESG standards to make the process less burdensome?
USING AI TO SOLVE ESG
The increasing affordability and accessibility of AI offer potential solutions to alleviate these challenges, both in the implementation and reporting of ESG initiatives. As AI is becoming globally available, its adoption offers improvements across industries when integrated into daily operations and aligned with ESG goals. The synergy between AI and ESG extends beyond just a technological advancement. It is a key strategic element that can redefine market leadership and sustainability in a changing global landscape. Mastering this synergy is critical for companies to maintain competitiveness and fulfil corporate responsibilities. The rapid deployment of AI technologies brings new and significant risks—from job losses to over-dependencyon technology. Risk management and organisational structures must be re-evaluated to integrate AI into one’s business. The potential impacts of AI on fairness, privacy, and transparency have become key issues in business ethics.
AI-DRIVEN RESULTS
The latest discussion paper from Ernst & Young on the interplay between AI and ESG elevates AI and sustainability to top priorities on corporate agendas. EY’s report (2024) notes that 38% of CEOs prioritise sustainability in capital decisions and 88% invest in AI-driven products.
According to EY, businesses are responding to heightened de-mands from investors, regulators, and society for increased transparency in ESG practices. This trend highlights a growing alignment of business strategies with broader societal and environmental goals. McKinsey Global Institute (2023) projected generative AI to generate an economic impact of $110 billion to $180 billion in real estate in the following years. This projection reflects the potential value creation from generative AI across various aspects of the real estate industry, from design and construction to operational efficiency and customer engagement globally, highlighting the immediate potential of generative AI to transform the sector.
SMART GRIDS AND DIGITAL TWINS
AI enhances operations with improved automation, usability, and various applications. The case studies below demonstrate examples of innovative technology and AI integration to reduce emissions; monitor and manage buildings through BMS and digital twins; use smart retrofitting tools to shift brown stock to green with clarity for investor returns; reduce material waste by employing AI in manufacturing and fabrication; and improve energy management through AI smart-grid integration.
WHAT THE HECK IS A DIGITAL TWIN?
A digital twin is a digital model of an object or system directly connected to the physical thing that it monitors and mirrors. Using real-time data from the physical target, digital twins help make improvements to efficiency and operations, prevent misuse, and anticipate necessary maintenance. They can also model theoretical scenarios and run simulations, using AI to analyse multiple processes and factors simultaneously, which offers significant potential to improve products and processes.
GET AI READY
The rapid advancement of AI, particularly in roles traditionally filled by younger, less experienced employees, poses significant challenges for workforce management and business strategy. While AI can efficiently handle routine tasks, its deployment necessitates stringent oversight by more experienced staff, potentially increasing pressure on senior personnel. Over-reliance on AI could expose businesses to risks, such as technological disruptions or a lack of skilled human oversight. This shift could also hinder the development of future leaders, who gain essential skills through hands-on experience and mentorship, hampering organisations’ succession planning. Thus, effective governance should embrace AI and leverage it to enhance and train a skilled future workforce. This approach should prioritise data interpretation, visionary leadership, and continuous improvement of AI outcomes, preparing a new generation to work alongside AI rather than being overshadowed by it.
A NEW FRONTIER
AI and ESG are setting new standards for innovation in real estate and manufacturing. Successful integration of these technologies enhances operational efficiency, sustainability, company reputation, and stakeholder returns. Navigating the associated risks through strategic planning and proactive governance is crucial for realising these benefits. This discussion draws on emerging research and trends that may change as new technologies and regulations develop. The pace of technology adoption and the consistency of ESG standards vary widely, potentially affecting the applicability of these findings. Moreover, the long-term effects of AI on job markets and corporate structures are still uncertain and require continuous study and adaptation.
