The Role of AI and Automation in Combating Climate Change

AI and Automation technologies are forecast to deliver up to 500% more impact than all developed world solar power investments combined; but how will we achieve this, what are the applications and what are the issues we face?

Synthesis:

Artificial Intelligence (AI) and Automation will have a major positive contribution to avoid emissions and reduce resource consumption globally.
AI and Automation drive clearer and more precise strategies, and accelerate their implementation, in a cost effective way with direct profit and climate impact.
Combined, these products have the opportunity to remove up to ~10 Gt CO2e by 2050, contributing up to 5x the impact of all planned solar power investment in developed countries
In parallel, the economic growth it creates will contribute +26% GDP growth by 2030 that will support broader financing of climate change prevention and adaptation
A clear commercial opportunity exists to build an Intelligent Automation “Innovation Partner of Choice” for global corporates that can address the confidence and talent gap that exists today.

An Introduction to Artificial Intelligence (AI) and Automation and its Application in Combating Climate Change:

As the world grapples with the urgent need to combat climate change, businesses are increasingly turning to Artificial Intelligence (AI) and Automation (together defined as "Intelligent Automation") as powerful allies in reducing their carbon impact. This article explores the profound positive impact of Intelligent Automation on how companies can embrace sustainability and drive higher profitability in a win-win outcome.

Intelligent Automation is reshaping how companies across all sectors assess and address their environmental impact. Intelligent Automation can be employed in five key ways: to gather and complete complex data sets; to strengthen planning and decision making; to optimize processes; to support collaborative ecosystems; and to encourage climate-positive behaviours. In these combined ways, it can help stakeholders— businesses and their investors—pursue a more informed and data-driven course, while offering them opportunities to create meaningful environmental change in this critical moment.

Importantly, Intelligence Automation can also help companies gathering and analysing their true ESG performance allowing the rethinking of systems to create higher and longer-term value for their stakeholders.

Companies around the world are now exploring innovative ways to reduce their environmental impact using technology, including Intelligent Automation, but are struggling to accelerate transformation. This talent and product gap creates a massive commercial opportunity for service providers and product companies globally.

Quantifying the direct economic and carbon impact of Intelligent Automation:

AI has a double contribution to preventing climate change. Firstly, its can provide the economic growth and cash flow required to accelerate investment by governments and corporates. The World Economic Forum has estimated that using AI for environmental applications could contribute up to $15.7 trillion USD to the global economy by 2030, a 26% increase relative to business as usual. Through productivity improvements, AI could create 38.2 million net new jobs across the global economy offering more skilled occupations as part of this transition.

In parallel, and very significantly, the application of AI levers could reduce worldwide greenhouse gas (GHG) emissions by 4% in 2030, an amount equivalent to 2.4 Gt CO2e – equivalent to the 2030 annual emissions of Australia, Canada and Japan combined. By 2050, these emissions reductions could contribute to between a 6.8 – 13.4% reduction in worldwide greenhouse gas (GHG) emissions; or equivalent to 4.9 – 9.7 Gt CO2e by mid-century. In context, the contribution of all solar energy in developed markets to decarbonisation is estimated to be only 2.1 Gt CO2e. Intelligent Automation therefore has the potential to contribute 2-5x the impact of the developed world’s solar market investment. This is without taking any incremental negative contribution of the cost of transition to renewables or its manufacturing footprint.

Additionally, the majority of these technology are borderless; with far simpler security concerns and can globalise faster. AI levers provide an accelerant for developed markets to support the accelerated transition of the Global South, where more than 3 billion people live in areas that are highly vulnerable to climate risk, such as the Small Island Developing States, South Asia, and much of Africa, according to the Intergovernmental Panel on Climate Change (IPCC).

How Intelligent Automation will be Applied by Companies to Fight Climate Change and Drive Profitabilty

Among the many tools at their disposal, Artificial Intelligence (AI), Robotic Process Automation (RPA), and Process Mining are key enablers for corporates globally.

Process Mining: Unearthing Efficiency and Sustainability: Process Mining, a data-driven approach to visualizing and optimizing business processes, has gained prominence as a tool for environmental sustainability. By providing a granular view of how operations function, it uncovers inefficiencies and bottlenecks that can lead to resource waste. Companies can then use these insights to streamline processes, optimize resource use, and reduce their environmental impact. For instance, Process Mining can reveal where excessive material usage occurs in manufacturing, leading to the development of more sustainable production methods.
AI: The Engine for Sustainable Transformation: Artificial Intelligence, with its data-processing capabilities and predictive analytics, plays a pivotal role in helping companies reduce their environmental impact. AI-driven insights enable businesses to optimize resource allocation, energy consumption, and supply chain logistics. For instance, AI-powered demand forecasting can lead to reduced overproduction and waste, cutting down on unnecessary resource consumption. Additionally, AI-driven predictive maintenance can extend the lifespan of equipment and machinery, reducing the need for replacements and their associated environmental costs.
RPA: Automating for Efficiency and Sustainability Robotic Process Automation (RPA) is another technological marvel that companies are adopting to streamline their operations while reducing their carbon footprint. RPA excels in automating repetitive, rule-based tasks, which not only increases operational efficiency but also minimizes errors and waste. In the context of environmental sustainability, RPA can be applied to optimize energy management systems, reducing energy consumption in offices and production facilities. Furthermore, it can enhance the efficiency of waste management processes, improving recycling rates and minimizing landfill waste.

Addressing the talent gap is critical to the successful delivery of these dual goals:

A BCG survey conducted in May 2022 found that 87% of global public- and private-sector leaders who are responsible for climate or AI topics believe that AI is a useful tool in the fight against climate change, however only 43% of these leaders say that their organizations are able to define how. 78% say that a lack of AI expertise is a clear obstacle to their organization’s efforts to use AI to combat climate change, 77% blame a lack of productised AI solutions, and 67% point to a lack of confidence in AI-related data and analysis.

For these technologies to be fully utilised there need to be sufficient skilled people in the market to design and implement readily accessible products that offer tangible benefits to the user.

There is a clear market opportunity to build a service provider who can be the “Intelligent Automation Innovation Partner of Choice” for corporates and the public sector as a critical component of an effectively applied solution.

Challenges and Ethical Considerations:

While AI, RPA, and Process Mining offer significant benefits in reducing environmental impact, they also raise important challenges and ethical considerations. These technologies can lead to workforce displacement, prompting questions about the social responsibility of companies as they automate tasks. Moreover, there are concerns about the ethical use of AI, particularly in the context of privacy and data security, which need to be addressed to ensure responsible implementation.

Conclusion:

In conclusion, the integration of AI, RPA, and Process Mining into business operations holds immense promise for reducing companies' environmental impact. These technologies are enabling organizations to optimize processes, enhance energy efficiency, and make data-driven decisions that lead to sustainability. However, their adoption should be guided by ethical considerations and a commitment to a more environmentally responsible future. As companies increasingly recognize the value of sustainability, Intelligent Automation will continue to play a central role in driving positive change for both businesses and the planet.

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