Expectations on businesses to combat climate change have intensified. Dave O’Shaughnessy outlines how organisations can use artificial intelligence to reach sustainability goals

Last month, the World Economic Forum reiterated the need for urgent action on climate change, which was also the core message from COP28.

With the world poised at this make-or-break moment, societal and stakeholder expectations of the role of business in reducing the effects of climate change are at an all-time high.

In a US Pew Research Centre Survey published last October, 52 percent of respondents said they believe large businesses and corporations can do "a lot" to reduce the effects of climate change.

This suggests that the expectation has moved beyond businesses simply fulfilling their environmental, social and governance (ESG) responsibilities to the view that they should be focused on even greater change.

This change – termed “regeneration” – calls for a reinvention of systems across an organisation, from business models to supply chains, to help drive a positive impact rather than simply avoiding a negative one.

While this is certainly an important objective, many organisations are currently facing external and internal pressures, long-term planning challenges and reporting requirements that have grown in scope and complexity to even reach a stage of compliance and organisation, let alone regeneration.

It’s here that artificial intelligence (AI) is a game-changer.

By harnessing data and driving efficiency, it can help your organisation meet your most immediate sustainability goals: achieving carbon neutrality, reduction of water use, and meet Science Based Targets initiative (STBi) targets as well as the UN Sustainable Development goals (UNSDGs). At the same time, AI also frees up your people to consider the bigger, long-term regeneration opportunities that can change your organisation’s environmental impact.

There are three ways AI can assist with and organisations sustainability goals, which are outlined below.

One: Guidance on sustainability reporting standards

New directives such as the Corporate Sustainability Reporting Directive (CSRD) and Corporate Sustainability Due Diligence (CSDD) mean companies face increasing reporting requirements. The high volume of reporting points and the interrelationships between regulatory reports and voluntary frameworks (Global Reporting Initiative (GRI), the Carbon Disclosure Project (CDP), and the Sustainability Accounting Standards Board) adds to the complexity of the task and requires organisations to be able to interpret complex policy documents in a short space of time.

Unsurprisingly, many organisations are struggling with where to begin, unsure of how they fare compared to expectations and are confused by the multitude of requirements. As a result, they are unable to forge an action plan or identify potential problems.

Generative AI can alleviate this concern. Its ability to analyse large volumes of documents (in this case, the reporting requirements and frameworks) in real-time and then to provide easy-to-understand explanations gives companies a clear starting point.

It also cuts down on complicated, manual research time and ensures consistency in understanding and actions among staff.

A chatbot is one means of achieving this. It can ingest all the legislation, directives, frameworks, and facts relevant to your company’s sustainability needs and then act as a “personal assistant” for any user questions.

By combining knowledge from a vast number of resources, your organisation-specific chatbot can provide enhanced understanding on complex topics at speed, support decision-making, and even provide references so users can review the sources or answers for fact checking and traceability.

Two: Actionable insights

With the objective to halve emissions by 2030, companies must have a comprehensive and integrated net zero approach involving all aspects of their operations and value chain.

But while this integrated approach is key to meeting targets, extracting information from multiple sources and the analysis of that information (crucial if opportunities and hot spots are to be identified quickly and adjustments made) means considerable work for teams.

AI has the ability to monitor and analyse multiple data points, often combined with outputs from machine learning or other algorithms, quickly and efficiently (e.g. forecasting total emissions or identification of raw materials that have the highest impact on CO2 reduction).

It can also enhance the quality of insights generated by this analysis by providing explainable and clear “next best actions”.

Three: Sentiment analysis

Public sentiment can significantly impact a business's reputation and performance. Social media, in particular – a key source of sentiment information with many people sharing their views and experiences – can often prove difficult for companies to monitor and manage quickly.

Sentiment analysis can assist with this. A form of natural language processing (NLP) that uses AI to evaluate and classify sentiments expressed in textual data can provide consolidated insights to businesses.

Until recently, sentiment analysis required extensive training data, making the process time-consuming and expensive. The process has been revolutionised with the emergence of Large Language Models (LLM).

LLMs perform very well when it comes to classifying text and analysing sentiment without the need for prior training, thus streamlining the sentiment analysis process. This innovation makes the collection and interpretation of public sentiment more seamless, helping businesses get a quicker and more accurate understanding of how they are perceived by the public.

New opportunities

Organisations that leverage AI will find it easier to meet their immediate sustainability goals and be better prepared to address future challenges.

Quicker collation of information and analysis enables workforces to take greater initiative.

By being able to make faster, more insightful decisions, people will have the time to identify new opportunities for greater environmental impact.

Dave O’Shaughnessy is Partner and Sustainability Reporting – Technology Lead at EY