Learn more about the 10 types of innovation developed by Doblin, which fit in three categories: Configuration, Offering and Experience.
Artificial intelligence (AI) focuses on building machines that can replicate human intelligence. The goal of AI is to help speed up processes, make work more efficient, and assist humans in performing repetitive tasks.
When talking about AI, it is not just about building robots that can think and act like humans. AI can be used in performing basic tasks such as data collection and organization. It can also be used for more advanced applications of machine learning and deep learning.
Artificial intelligence has changed the technological landscape. Individuals, businesses, and governments have all benefitted from AI applications. Most people interact with AI applications regularly. It can be integrated into virtual chatbots, virtual assistants like Siri, self-driving vehicles, and more. Today, AI also plays a significant role in improving corporate sustainability.
As mentioned, artificial intelligence is present in a lot of things that people use daily. Search engines, social media algorithms, subscription platforms… All these things use some form of artificial intelligence.
Artificial intelligence has two main applications today, referred to as weak and strong AI.
Weak AI is also called narrow AI. It consists of simple functions that try to imitate human intelligence. But these applications are limited and cannot think and act on their own. Some examples of weak or narrow AI include search engines, facial recognition software, and self-driving cars.
These applications are already a huge advancement in technology. Who would have thought that cars could drive themselves in the 21st century? However, these applications are still a long way from mimicking human intelligence. They perform specific functions that are determined by algorithms and human input.
Machine learning is responsible for most applications of narrow AI. In machine learning, a computer programmer inputs specific data into a computer. The computer then analyzes the data to learn it. Once it has learned the task, the computer can then work on improving its performance. This process reduces the need to write code from scratch.
More advanced machine learning applications make use of unlabeled data sets. This is called unsupervised learning. This means that the computer can analyze unorganized data and create algorithms from it. While supervised learning uses labeled data sets to create algorithms.
Deep learning is another application of narrow AI. It is a subcategory of machine learning. In deep learning, computers learn data through an architecture that imitates the human neural system. This means that the data goes through several layers for it to be processed. Through each layer, the machine learns the data and extracts valuable insights from it.
Strong AI is also called artificial general intelligence or AGI. AGI is the more advanced form of artificial intelligence. This type of AI is often depicted in movies as robots that can think and act for themselves.
AGI is the end goal of most artificial intelligence researchers. However, the current state of technology is not enough to fully create a human-like machine. More knowledge and research are needed to discover ways how to replicate human intelligence in computers. Experts in the tech field agree that AGI is still an idea that has yet to be actualized.
The good news is that humans won’t have to worry about robots taking over the world anytime soon. But something that humans do have to worry about is global warming and climate change. These are actionable things that artificial intelligence plays a significant role in.
So, how can artificial intelligence help corporate sustainability management? As discussed above, artificial intelligence can perform specific tasks and functions. The field can create algorithms based on datasets to help predict outcomes and recommend solutions.
The following are the applications of AI to improve corporate sustainability management.
The main goal of corporate sustainability is to slow down global warming. Machine learning can identify areas of a business that uses excess energy. Businesses can then address these areas by finding alternative energy sources. AI can also use advanced sensors to collect and organize data. Computers analyze this data to come up with solutions to reduce a company’s carbon footprint.
Aside from dealing with energy sources, AI also contributes to improving transportation routes. By predicting optimal routes, businesses can save on costs and reach their customers faster. All these while reducing their overall carbon emissions.
Artificial intelligence makes use of advanced sensors to predict the weather. Machine learning applications can create algorithms to make these predictions more accurate. This capability of AI helps businesses predict economic flows that are affected by the weather. This includes shipment and production information.
Weather predictions also help businesses build a business continuity plan (BCP). They can prepare for disasters and calamities with the use of AI. A business that has a BCP in place is more resilient than its competitors. It improves consumer confidence as businesses can still deliver their products and services to consumers despite extreme weather conditions.
Limited resources are available on the planet today. Due to the widescale production, economies must create policies that aim to protect and conserve these resources. These policies affect businesses. Thus, corporate sustainability measures must also focus on how to manage resources. Proper management will help global efforts while keeping consumers satisfied.
AI can detect mismanagement of resources. After which, it can recommend solutions to improve in this area. It can also detect changes in land, vegetation, and ocean health. Businesses can also use machine learning applications to develop resource management protocols. These protocols can counteract risks associated with depleting resources.
World economies are set on reducing carbon emissions to meet the net-zero carbon target by 2050. AI can help speed up this process. Corporate sustainability has become a priority for businesses of all sizes. It can help determine the business’ growth, market value, and consumer confidence.
Want to become a master innovator? Read our other articles on innovation:
Dou you want to boost your sales by applying innovation in your company? Book a FREE Call and let’s talk about how we can help you.
Learn more about the 10 types of innovation developed by Doblin, which fit in three categories: Configuration, Offering and Experience.
Learn more about the 10 types of innovation developed by Doblin, which fit in three categories: Configuration, Offering and Experience.
Learn more about the 10 types of innovation developed by Doblin, which fit in three categories: Configuration, Offering and Experience.