AI and Organizational Transformation: Navigating the Future

Najana, Madhavi; Bhattacharya, Saurav; Kewalramani, Chhaya; Pandiya, Dileep Kumar

doi:10.21428/e90189c8.03fab010

International Journal of Global Innovations and Solutions (IJGIS) 2024

DOI: 10.21428/e90189c8.03fab010

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AI and Organizational Transformation: Navigating the Future

Madhavi Najana,

Saurav Bhattacharya,

Chhaya Kewalramani

et al.

Abstract: The incorporation of intelligence (AI), into business practices worldwide signifies a change in how organizations operate. This study delves into the reaching effects of AI technology on aspects of organizational activities, such as operational effectiveness, employee involvement, customer satisfaction and creativity. By examining real life examples and analyzing data it explores how AI driven automation simplifies processes, improves decision making and encourages a culture of innovation in sectors like finan… Show more

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2024

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Cited by 3 publications

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Artificial Intelligence and its Applications in the Field of Internet of Things (Iot)

Jakkani

2024

IJRISE

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Artificial Intelligence (AI) and the Internet of Things (IoT), are innovative technologies that have revolutionized many fields independently. Altogether, this convergence offers a daunting possibility for innovation of a number of aspects of smartness in a range of domains on the one hand and the optimization of those aspects for sustainability on the other hand. Machine learning and deep learning help IoT devices and networks perform analytics on big data and achieve real-time decision making and automation. In smart cities AI based IoT helps in the self-organizing and self-optimizing of traffic management, and utilization of energy, and increases public safety by applying predictive analytics to the actual management of a city. The telemedicine receiving aid from AI IoT includes the detecting of sickness onset with a device that monitors patients and creates corresponding customized treatment regimens. The same way applied to IIoT where AI is implemented for predictive maintenance, quality assurance, inventory control and in turn, the achievement of alleviated downtime and improved production. Ethical issues related to bias in algorithms, and subsequent decision making via the use of Artificial Intelligence add another layer of concern in terms of deployment and utilization. Prospects for the future include such trends as edge computing, the AIoT is AI + IoT amalgamation, and the disruptive effect of quantum computing on AI applications for the IoT. The mitigation of these difficulties and the exploitation of these opportunities will open the path to proper optimizations of AI-based IoT systems as concerns effectiveness, security and/or ethics. This article stresses how AI is mandatory to the implementation of an ideal IoT system by exploring current uses, future developments, and problems that are vital for the advancement of IoT.

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Artificial Intelligence and its Applications in the Field of Internet of Things (Iot)

Jakkani

2024

IJRISE

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Real-Time Network Traffic Analysis and Anomaly Detection to Enhance Network Security and Performance: Machine Learning Approaches

Jakkani

2024

JECNAM

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There are numerous proceedings that take place within an actual computer network, and one of them is the monitoring of the network traffic in real-time with the added function of anomaly detection. This research focuses on the use of machine learning to improve these capabilities as stated in the following section. In the context of the current study, the emphasis is made of building powerful anomaly detection models that would be capable to work in real life by defining network and potential threats on their own due to their machine learning capabilities. Furthermore, the study gives a detailed analysis of the more complex methods like feature selection in addition to dimensionality reduction for enhancing the abilities of machine learning algorithms in the management of big data samples for world-wide network traffic. Furthermore, the presented research focuses on the application of definitions of edge computing paradigms to facilitate decentralized processes of the identification of anomalies, thereby enhancing the sensitivity and response time of essential networks. Thus, the research objectives are to address the aforelisted challenges and generate insights into constructing better network security frameworks to prevent and respond to future threats in a precise and effective mechanism.

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Enhancing Urban Sustainability through AI-Driven Energy Efficiency Strategies in Cloud-Enabled Smart Cities

Jakkani

2024

JEET

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Energy efficiency in the modern urban environment is fostered by high technologies like artificial intelligence (AI), cloud computing and others. Thus, this research aims at examining the adoption of AI solutions in the climate-smart cities using cloud technology to boost the achievement of the sustainable development goals. With data collected from the IoT sensors that are integrated within different structures of the city, the AI will be able to actively regulate the energy usage as needed in real time. Such algorithms not only predict energy requirements but also adapt the entire city’s functioning to decrease losses and harm the environment less. Cloud computing is instrumental by integrating large amounts of storage and processing that are required in tackling data accrued by the IoT devices. By way of cases and experiments, this research assesses how AI-based solutions can address problems of emerging city carbon footprint and sustainability under various urban conditions. The purpose of this research work is to highlight the importance of artificial intelligence and cloud computing to enhance the urban environment’s entity. They present these technologies showing their potential in shedding light on the rational use of energy in various facets of city functioning, and in this manner they make a positive impact on the drive for attaining sustainable development goals.

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AI and Organizational Transformation: Navigating the Future

Cited by 3 publications

References 9 publications

Artificial Intelligence and its Applications in the Field of Internet of Things (Iot)

Artificial Intelligence and its Applications in the Field of Internet of Things (Iot)

Real-Time Network Traffic Analysis and Anomaly Detection to Enhance Network Security and Performance: Machine Learning Approaches

Enhancing Urban Sustainability through AI-Driven Energy Efficiency Strategies in Cloud-Enabled Smart Cities

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