How AI can help solve the sustainability talent gap

Sustainability is increasingly a priority for businesses, driven by both regulatory and client pressures. But as demand for sustainability professionals soars, there are simply not enough qualified workers to fill the required positions. 

According to last year’s LinkedIn Global Green Skills report, the demand for “green” talent has grown by roughly 8% annually over the past 6 years, yet the supply of professionals has only increased by around 6%. In the meantime, the so-called ESG talent gap keeps making headlines, including recent reports by the Financial Times and the World Economic Forum. 

And this is in spite of the fact that jobs in sustainability or ESG are increasingly popular among workers, with many seeking to develop new skills in this space as part of what LinkedIn termed “The Great Reshuffle”. 

The gap poses a challenge not only for individual businesses but for society’s broader efforts to address climate change. As Microsoft stresses in its report “Closing the Sustainability Skills Gap: Helping businesses move from pledges to progress”, if we want to have a fighting chance to meet global environmental goals, we will need to hire and upskill millions of workers focusing on climate and environmental issues over the course of this decade. 

Most guidance to support companies bridge the ESG gap focuses on improving organizational culture, encouraging internal mobility, providing in-house opportunities for ESG credentialing, and adopting better recruiting strategies. However, tech - and especially AI - will also play a vital role in addressing this issue. 

By streamlining sustainability data gathering and analysis, tech - and particularly AI - boosts the productivity of sustainability teams, and allows for a more efficient allocation of company resources. 

The different paths to a career in sustainability

Sustainability is broad and includes a number of different sub-specializations, all of which require a different skill set. Organizations have different needs, and the skills required to effectively manage a firm’s sustainability strategy vary widely depending on the sector, industry, and organization size. The skills required for regulatory ESG reporting are vastly different from those required to implement corporate decarbonization strategies. However, sustainability roles can be distilled into a limited number of core disciplines.

Here are some of them:

• Data Management and Analysis: Sustainability teams need to collect, store, and analyze large amounts of sustainability data. This requires proficiency in data management tools, including spreadsheets and databases, as well as an understanding of data analysis techniques and visualization tools. 
• Sustainability Reporting: ESG reports are used to communicate the company's sustainability performance to stakeholders and is increasingly becoming a matter of compliance thanks to a new wave of sustainability regulations. In the EU, mandatory disclosures - such as the EU Taxonomy, the CSRD, and the SFDR  - now touch most of the market and require reporting professionals to oversee the process. 
• Environmental Assessment and Modeling: This area requires knowledge of environmental impact assessment tools and methodologies, as well as the ability to use software tools to model and analyze data.
• Sustainable Supply Chain Management: These teams oversee a company's supply chain practices and find opportunities to improve sustainability performance. This requires knowledge of sourcing practices, supply chain management tools and methodologies, and the ability to evaluate the sustainability performance of suppliers and clients.
• Energy and Resource Management: This role requires a strong understanding of how energy and resources are used in the company's operations and how they can be managed more efficiently. Workers in this field require a knowledge of energy and resource management tools and methodologies and technologies.

While these job functions all demand  different skills, AI has a role to play throughout in reducing the time sustainability professionals spend on routine tasks. This enables organizations to devote more of their time and energy to communication, strategy development, and promotion of sustainability initiatives. 

Let’s have a closer look at some specific use cases. 

AI and NLP: A game-changer for sustainability teams

According to a survey conducted by Microsoft, management and collection of sustainability data is considered one of the most important skills for sustainability teams. On average, sustainability professionals spend approximately 11% of their time on these tasks, underscoring the opportunity to deploy technology. 

AI solutions can play a huge role in automating large parts of the data collection, preparation, and visualization process, and providing more detailed and precise modeling capabilities.

Most sustainability data is unstructured. It comes in charts, tables, large blocks of texts and other unstandardized formats that limit the capacity of existing technology solutions. This is where technology like Natural Language Processing (NLP) can be a game-changer: for instance, document analysis models can be used to identify, extract, and classify unstructured data that can be used for the firm’s sustainability analyses. 

NLP helps relieve analysts from the mind-numbing task of sifting through endless reports and bottomless spreadsheets, and it makes sustainability reporting measurably easier and faster. If you want to learn more about the numerous applications of NLP in sustainable finance and reporting, have a look at an article that our CTO has written on this topic. 

Training and upskilling of  ESG talent can also benefit from AI solutions. Question-answering technology - including the world sensation ChatGPT - will have a massive impact on research, learning, and knowledge-sharing. While generalist chatbots like ChatGPT still lack the necessary in-depth knowledge when it comes to highly technical topics, these technologies are evolving quickly and will likely be able to adapt to specialized fields in the near future. 

Utilizing NLP technology for training purposes can be an extremely cost-effective way to upskill a workforce and expand the pool of eligible candidates for sustainability roles.

As highlighted by this EY report zooming in on the phenomenon of the Great Resignation, learning and upskilling is a growing challenge for companies that hope to retain talent and optimize their internal resources for the ever-changing needs of the business world. 

Interestingly, the same report shows that over 10% of employees care deeply about their companies’ sustainability goals: in other words, there is no shortage of interest in these topics among the workforce. 

AI and sustainability teams: a match made in heaven?

AI will be a game-changer for businesses that seek to scale up their ESG and sustainability strategy, not only by increasing the productivity of existing teams but also by ramping up companies’ ability to train new workers at scale. 

With AI handling routine tasks, sustainability specialists can devote their time and energy to promoting impactful initiatives and developing effective sustainability strategies. 

Investing in machine learning software for sustainability could eventually provide businesses of all sizes with a scalable way to mitigate the current shortage in ESG talent, so that sustainability specialists can devote more of their time to driving change within their organization.

At Briink, we are on a mission to empower sustainability and sustainable finance teams to achieve their goals with AI-powered sustainability reporting and sustainability intelligence technology, with a focus on the EU regulatory framework. Learn more about our products and services, or get in touch with our team of specialists to learn more about how we can help your organization achieve its sustainability goals. 

Summing up: 

• Demand for "green skills" has grown by 8% annually in the past 6 years according to LinkedIn's Global Green Skills report, while the supply of professionals has grown by only 6%.
• The gap between demand and supply poses a challenge for businesses and society as a whole.
• Closing this skills gap can be approached through internal training programs, encouraging new graduates to pursue sustainability careers, and flexible hiring practices.
• However, AI - and in particular NLP - can also play a crucial role in mitigating the shortage of sustainability experts, by streamlining the sustainability analysis process and improving knowledge sharing and training of sustainability professionals.
• Early adopters of AI will not only be able to bridge the ESG talent gap, but will also lead the charge in the race to a net-zero economy.