There are many different applications for generative AI when it comes to incorporating sustainability, especially when it comes to filling data gaps. The amount of data required to produce ESG and sustainability reports is enormous, and its complexity is considerable. Companies often don’t have that data or lack the proper protocols to align their data and sustainability strategies.
Most clients, regardless of the size of their company, have overstretched sustainability teams trying to manually locate data instead of focusing on what it reveals. Generative AI can unlock productivity potential by accelerating data collection and reconciliation of ingested data. For example, rather than sustainability teams manually collecting and reviewing paper fuel receipts, technology can help convert images of those receipts into the data needed to calculate fuel-related metrics. This allows teams to spend more time optimizing fuel consumption for decarbonization and analyzing data, rather than searching for it.
If you spend all your time reconciling invoices or collecting physical fuel receipts, how will you and others in your organization have time to understand the data and make changes that drive sustainability? If time is spent collecting data and reporting, there is little room to gain actionable insights from that data and make changes. Systems and processes must be established that allow organizations to improve their sustainability performance and meet ESG reporting requirements, without allocating all their resources and funds to data management that, in the long run, offers visibility, but not the ability to generate impact.
As mentioned in the study, generative AI can “transform data-driven sustainability by enabling organizations to turn trade-offs into mutual benefits, identify opportunities for improvement, and drive innovation quickly and at scale.” No wonder 73% of executives surveyed say they plan to increase their investment in generative AI for sustainability.
To fully harness the power of generative AI in the future, companies must first understand how ready their data capabilities are today. Then, we can prioritize how generative AI can enhance existing data to increase visibility and use that data to gain insights into performance.
Companies can identify immediate opportunities for generative AI to help them move faster, while ensuring they have the critical data collection and management processes necessary to meet current and future reporting needs. We want our clients to take advantage of ESG reporting to achieve a return on investment (ROI) both financially and in terms of sustainable impact. While external mandatory requirements will influence an organization’s budget allocation, companies can deliberately integrate sustainability into those initiatives to realize the full value of their transformation efforts.
Source: www.ibm.com
