


How to use artificial intelligence to solve industrial-scale decarbonization efforts
Our world has reached a point where society recognizes that the planet is under tremendous pressure. Businesses across a wide range of industries have announced plans to reduce their carbon footprint to "net zero" over the coming decades, with most aiming to achieve the target between 2030 and 2050. While strategies around net zero have been key to operational plans in some of the worst-affected sectors, such as energy and oil and gas, establishing sustainability goals has become the norm across most industries.
Environmental, social and government (ESG) issues have become an increasingly important topic of discussion. A recent McKinsey survey found that 83% of executives and investment professionals believe ESG programs will be delivering more value to shareholders in five years than they are today, suggesting they have potential short- and long-term value.
With carbon dioxide emissions expected to increase to approximately 43.08 billion metric tons by 2050, companies must adopt solutions to reduce or offset their carbon footprint. However, the difficulty and expense of measuring carbon emissions efforts and reducing or offsetting these challenges has forced many businesses to delay their efforts. However, cognitive AI solutions can play a key role in helping businesses and industries achieve net zero goals easily and at lower cost.
AI-Based Human Approach
Most artificial intelligence tools tend to operate in a black box, with human users unable to perceive how they arrive at conclusions, answers, and recommendations. These solutions often simply offer a remedy with no explainability, traceability or auditability – doing little to build user confidence. Increasing opportunities for artificial intelligence to enhance people’s talents and abilities requires their trust. Otherwise, the ability of both parties to work effectively together to address our most important sustainability issues will be severely limited.
Unlike traditional AI capabilities, cognitive AI solutions use human-like reasoning to identify opportunities for operational improvement and streamlining, which is an ideal choice for businesses looking to significantly reduce emissions while managing resources efficiently. key functions. This type of explainable AI works transparently, directly revealing the reasoning behind its recommendations and easily displaying the comprehensive data that supports its decision-making process with a clearly readable audit trail. Rather than using AI as a replacement for human input, cognitive AI serves as a tool for humans to make more confident decisions. The balance between knowledge-based cognitive and digital enables decision-makers to identify unexpected opportunities and take immediate action in critical situations – such as reaching net zero targets.
Prioritize AI Investments
With climate change at a critical inflection point, organizations should adopt cognitive AI technologies to help set realistic but ambitious net zero targets and more accurately Monitor progress.
Governments and private companies looking to fast-track AI investments and system deployments should prioritize the following areas:
- Start small to solve specific problems and scale with experience
- Leverage and mine large data sets from the growing number of installed sensors and measurements
- Identify specific use cases with clear return on investment
- Digitize domain expertise and enrich it with AI/ML
- Aligning stakeholders and their priorities with AI investments
While product cost is often the primary factor when considering investments in technologies like AI, executives and others Decision makers should consider the long-term return on investment of such solutions. Businesses must remember that costs will continue to fall due to technological developments in hardware and software, and the benefits will only become more widespread. In addition to helping companies set and achieve sustainability goals, AI technology can also help companies improve operational efficiency, ensure safety, increase customer trust and relationships, increase productivity, expand data processing capabilities, and more.
Coping with climate change impacts
Artificial intelligence can make a significant contribution to companies’ efforts to achieve net zero targets, while also helping to prepare for future climate change-related disruptions. For the electric power industry, a key goal is to accurately match demand and generation to continuously deliver the necessary amount of energy required by utility customers.
When demand exceeds grid capacity, it can cause uncontrolled shutdowns of generating equipment, leading to a catastrophic domino effect and grid outages. This potential scenario became a reality last year when extreme weather conditions caused demand to exceed supply, leading to ongoing power outages in California and Texas. With the effects of climate change expected to only continue to intensify weather conditions this summer, the North American Reliability Corporation's (NERC) 2022 Summer Reliability Review sounds the alarm that the U.S.'s outdated power grid faces a high risk of outages in the coming months .
The ability of generators and grid operators to accurately predict and manage power flows on physical grid infrastructure to match available generation to demand is a critical step in mitigating future climate change disruptions. Energy companies and grid operators therefore need AI to forecast and predict demand accurately and in a timely manner, allowing them to align generation with their inherent variability as set points change and variability due to the impact of cloud and wind on renewables delay to match. The biggest benefit that AI can bring to net-zero goals is allowing facility managers to use as much renewable energy as possible while taking into account all these parameters and variability. Artificial intelligence will play a key role in supporting the energy industry’s goals of a more efficient, connected and sustainable future.
Other examples of how AI initiatives are addressing climate issues include:
- Implementing artificial intelligence and machine learning to improve energy production in real time.
- Automation of downstream operations increases factory efficiency by 8% to 12%.
- Improve grid systems to improve predictability and performance, allowing for more thoughtful renewable energy strategies.
- Traffic and navigation optimization through AI and ML applications such as Google Maps and Waze, as well as other vehicle data collection solutions, reduce emissions and emissions by delivering relevant vehicle efficiency, traffic and other similar congestion data to consumers pollute.
- Use robotics equipped with artificial intelligence chips at the edge, by preventing catastrophic equipment failures and more by autonomously inspecting oil pipelines, refineries, or others.
Artificial Intelligence Now and Future
Working towards a low carbon future will require actions around operational efficiencies, improved production strategies and minimizing waste – all of which can Powered by cognitive AI solutions. The importance of global initiatives in achieving a more sustainable world cannot be overstated, but technology has a vital role to play: helping to identify and achieve bold and achievable goals. Artificial intelligence will become an even more critical practical tool in supporting businesses, industries and cities to achieve important net zero targets.
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