Artificial intelligence (AI) plays an important role in facilitating most of the decision-making processes by resolving conflicts and facilitating human communications. AI based applications have impacted the general businesses to a great level but its role in environmental resource management in businesses to achieve sustainably remains limited. This is due to the underlying cognitive state and complexity of environmental issues in business processes, along with the diversity of stakeholders' perspectives when dealing with commercial issues. The objective of this chapter is to illustrate the main components of AI and provide a guideline for the selection of suitable methods in business management and achieving environmental sustainability. The results show that AI applications can aid the involvement of stakeholders in the expedition of a state of resolution in order to reach a reciprocally substantial compatibility and bestow to familiar selection in environmental resource management and meet business needs in a profitable manner.
TopIntroduction
Artificial Intelligence (AI) is one important tool in monitoring the management of natural resources and using it in a feasible manner for business processes management (BPM) (Naim et al. 2021).
AI can transform and monitor natural resources such as forests, water, air quality and others. (Fu et al. 2020).
This is made possible through the use of AI-powered remote sensing and monitoring systems that collect data on various environmental factors. (Khatri et al. 2023).
The growth of AI in natural resource management is a remarkable milestone as it not only monitors but also gives optimum solutions for resource management and options to replace the energy consuming inputs to more environmentally friendly inputs for BPM (Saini and Tarkar 2022).
The applications of AI are implemented in agriculture, forestry, mining, and water management. This transformation has not only led to more efficient and sustainable management practices but also opened novice ways and methods for innovative applications (Bhardwaj 2022).
One of the most significant breakthroughs in AI for natural resource management has been the development of advanced data analytics and machine learning algorithms (MLAM) (Saini and Tarkar 2022).
These tools have allowed researchers and practitioners to analyze vast amounts of data, identify patterns, and make informed decisions (Chowdhury et al. 2023). For instance, in agriculture, AI-powered analytics can help farmers optimize their use of water, fertilizers, and pesticides, leading to increased crop yields and reduced environmental impacts. Figure 1 shows the AI based resource management applications for the benefit of BPM.
Figure 1. AI based benefits to resource management
The features of AI facilitate the functioning of resource management. AI based applications help businesses to improve their efficiencies and increase the outcomes which also help in environmental sustainability (Vrontis et al. 2022). Figure 2 shows the features of AI applications which are prevalently applied by the businesses for managing their resources (Bhardwaj 2022).
Figure 2. Features of AI based applications for BPM in managing theirresources
There are many areas where AI has made a significant impact and remote sensing is one of them. The use of satellite imagery and aerial photography has been a staple in natural resource management for decades (Pillarisetty and Mishra, P 2022).
However, the advent of AI has revolutionized this field by enabling the automated analysis of these images. MLAM can now quickly and accurately identify features such as land cover, vegetation health, and water bodies, making it easier for managers to monitor and assess the state of their resources (Priya et al. 2023). AI benefits are witnessed at various levels in environmental sustainability, these levels include benefits in air quality, water preservation, biodiversity, etc. Some of the benefits are presented in figure 3.
Figure 3. Benefits of AI based applications in environmental sustainability and resource management