How Intelligent Automation Can Pave the Road to Net-Zero

America is putting its money where its good intentions are when it comes to fighting the climate crisis. With the Inflation Reduction Act, the U.S. makes the single largest climate investment in the nation’s history. The legislation is expected to create hundreds of thousands of jobs in the clean technology sector. California has pledged tens of billions of dollars in budget money for climate proposals as well. Collective efforts are instrumental to combatting this crisis, and businesses that commit to climate-change fighting strategies will become the most significant agents of change for the planet’s future. Utilized to its fullest potential, intelligent automation (IA) could make all the difference.

Net-zero emissions is considered critical to insulating the world against the worst effects of climate change. If achieved, it means that human CO2 emissions will no longer exceed the amount of CO2 we remove from the earth’s atmosphere. Its importance has led to governments and corporations around the world pledging to meet such targets by 2050. But are net-zero emissions possible by 2050? Meeting this goal is not just a pipe dream, but it requires substantial change, determination and the right technology 

Digital solutions such as artificial intelligence (AI) and machine learning (ML) have the potential to accelerate decarbonization efforts and reduce emissions by up to 20 percent. If scaled across industries, digital solutions could be most effective at reducing emissions in the three highest emitting sectors – energy, materials and mobility. 

But to make this possibility a reality, high-emitting industry sectors must rethink their strategies to leverage efficiency, circularity and sustainability.

Predictions and production 

Digital solutions can enable the energy sector to reduce carbon-intensive operations and, subsequently, emissions by 8 percent, according to estimates from the World Economic Forum (WEF). To successfully transition to more renewable energy sources, utilities suppliers need to develop better methods for estimating how much energy is required, allowing them to make better use of resources and fill any gaps with renewables. Machine learning can anticipate energy outputs and demands through its data analysis. These forecasts can then help industries effectively implement climate change strategies while reducing inefficiencies and carbon emissions. 

Researchers from the Department of Energy (DOE) are relying on ML as a tool to search for materials that can be used as solar absorbers. They’re studying a class of material called halide perovskites which has shown promising results in converting sunlight to electricity.  According to a DOE report, solar energy could power 40 percent of the nation’s electricity by 2035.

The benefits of ML algorithms extend beyond the utilities sector and can be used in any business, across industry verticals. As a result, more accurate supply and demand forecasting contributes to drastic cuts in manufacturing and transportation waste through improved understanding of what’s needed, and when. Targeted suggestions for low-carbon items can also drive ecologically responsible purchases by helping to optimize power usage and avoid unnecessary storage and waste.

Enhance the algorithm

Intelligent automation solutions can also improve sustainability in vital industries, such as manufacturing, infrastructure and data centers. Organizations can reduce emissions by employing data automation and modeling to digitize and analyze processes, and develop predictive maintenance and monitoring capabilities. 

Although IA algorithms that anticipate energy consumption already exist, there is room for improvement to ensure they can keep up with the multiple sources of energy production today and the need to meet new and evolving regulatory and measurement requirements. Complex algorithmic features also need fine-tuning to be able to react to changing trends or behaviors, and to expand beyond the industrial level to cater to family and individual demands. 

One-stop digital solutions such as IA not only boost efficiency and production, but they also enable the development of new procedures that reduce power consumption and harmful emissions. 

AI-powered waste reduction

Artificial intelligence has the power to support climate action by reducing waste. The problem is that even among the many firms that utilize a high level of automation, a fragmented approach to AI is often adopted. This is inefficient, stifles transformation, wastes valuable time and racks up “technical debt” (referring to the costs that arise from organizational reworks needed due to sub-optimal solutions being originally chosen for fast, short-term results). 

Organizations need to reimagine their existing strategies and use varied yet complementary technologies that work together, rather than in isolation, to maximize efficiency and reduce waste. AI-managed energy systems can then identify the appropriate amount of energy consumption needed at any given time. These insights support the fight against climate change by minimizing energy waste, simplifying processes and maximizing productivity by creating efficient and unified workflows.

Innovation driven climate action

AI-enhanced digital solutions can assist with the development of tools that will help individuals and businesses understand their carbon footprint and outline steps to decrease it. For example, the World Bee Project harnesses the power of technology and science to enhance the wellbeing of bees and other pollinators. The collective effort has created the world's first global bee database. Monitoring sensors capture and combine data points, such as hive temperature, humidity, pollinator decline and deficiencies. This data supports the creation of solutions that maintain a healthy and sustainable ecosystem.

Automation technology has progressed significantly in the last five years with billions of dollars being invested in research and development. The prioritization of generating digital solutions has done much to accelerate the journey to reaching net-zero. Businesses and organizations that have committed to such targets will continue to move toward their goals by committing to digital solutions. Implementing intelligent automation may be the turbo boost they need on the road to simplifying work processes, reducing waste, and contributing to a sustainable and brighter future.

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