Climate change is the defining crisis of our time and a rapidly escalating issue that has left many with a sense of hopelessness and helplessness. Thankfully, new initiatives and developments are taking shape, giving public sector authorities and certain industry segments some power to take action to reduce emissions. Collective efforts are instrumental to combatting this crisis, and companies that commit to reaching their net-zero targets will become the most significant agents of change for our future.
Net-zero 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? I believe they are, however, meeting them will require substantial change and determination.
Following the World Economic Forum Annual Meeting in Davos this year, it was confirmed that digital technologies, such as artificial intelligence, machine learning and automation – scaled across industries – have the power to accelerate decarbonization efforts and reduce emissions by up to 20%. While it is understandable why people are losing faith in the future and being impacted by eco-anxiety, these findings give us hope by uncovering how digital solutions could pave the way for achieving sustainable outcomes that align with net-zero targets. In fact, if scaled, 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.
The predictive and productive power of digital solutions
With the support of digital solutions, the energy sector can reduce carbon-intensive operations and, subsequently, emissions by 8%, 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 so that they can make better use of resources – including systems, staff and partners – and fill any gaps with renewables. One such method is machine learning (ML), which can anticipate energy outputs and demands through its data analysis. We’re finding that these forecasts can then help industries effectively implement climate change strategies while reducing inefficiencies and carbon emissions.
The benefits of these 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.
Intelligent automation (IA) solutions can also improve sustainability in vital industries, such as manufacturing, infrastructure and data centers. We’re seeing organizations 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, we think 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, directly and immediately contributing to the fight against climate change.
AI-powered waste reduction
Artificial intelligence (AI) has the power to support climate action by reducing waste in all forms (financial, temporal and material). The problem is that even amongst the many firms that utilize a high level of automation, a fragmented approach to AI is often adopted. This stifles transformation, wastes valuable time and staff resources and generates “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 one 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
The future ahead may be rife with daunting uncertainty, but there are still limitless opportunities to generate innovative technologies that drive forward climate goals. Only five years ago, a company’s intelligent automation objectives often outstripped the capabilities of available technology. The market hype around advanced technologies didn’t deliver the promised business results. Since then, automation technology has progressed significantly, as billions of dollars have been invested in research and development. The prioritization of generating digital solutions in this sector, including the use of process analysis and predictive maintenance to reduce energy waste, has done much to accelerate the journey to reaching net-zero.
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. In an example of the potential of digital solutions, the revolutionary 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, which collects data intelligence from monitored colonies around the world. Monitoring sensors capture and combine data points, such as hive temperature, humidity, pollinator decline and deficiencies. These data points support the creation of solutions that maintain a healthy and sustainable ecosystem.
Digital solutions that are currently available present an actionable step towards net-zero and can help to prevent unnecessary damage from the climate crisis. Organizations that have committed to such targets will not only be able to reach their goals by continuing to employ digital solutions, but will also do so faster as they implement intelligent automation to simplify work processes, reduce waste and contribute to a sustainable and brighter future.