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Powering the Future of E-Government with AI-driven Technologies
AI has become increasingly persuasive with its numerous innovative aspects implemented in both private and government sector. This implementation helps government sectors to face the challenges that arise due to fraud and improper payments, enhancing safety measures of public as well as national security, and delivering better healthcare solutions. During this process, the entities will generate, collect, and store the diverse amount of data used to solve these problems. However, the traditional means to obtain insight from historical data are found to suffer from limitations such as volume, variety, and velocity—a pre-requisite for the modern government. This limitation can be overcome through advanced AI techniques with multistage data processing techniques.
The significant changes observed by employing advanced AI and machine learning algorithms in government entities are high efficiency along with reduced costs, and freeing up of resources benefiting the public sectors. There is a possibility that integrating AI can free-up over 30 percent of the government workforce’s time within the least span of time. The saved time and funds can be spent efficiently on benefits and services rather than maintaining the physical breaches.
Apart from the services and revenues ahead, the economic implications by deploying AI are widespread, and its effects will resonate across numerous government sectors. Through AI, certain vital insights can be extracted which will automate complex tasks and unlock the hidden aspects across the spectrum of government data.
Automatic fraud detection and improper payments monitoring can be achieved by employing the capabilities of machine learning along with deep learning techniques. The genuine data from the authorized users will be captured through the training process, and distinct features will be extracted and processed to classify the fraud data from the original data. It also ensures secure payment and fund release in government sectors.
Text analytics and natural language processing have the power to assist child welfare programs to identify children-at-risk and provide information to the authorities who can intervene to prevent children abuse. Furthermore, by processing the data in a multifold machine learning platform provides high precisive insights, which are free from frauds, are authentic, and enhance the government program in an efficient and effective manner.
Predictive methods deployed in government sector ensure readiness in safety, response agility to support national defense militarily and intelligent sector. Furthermore, with government approaches towards smart cities, because of IoT and sensors, the data captured are increasing, and there is a requirement of efficient machine learning techniques and cognitive computing approaches to enable government organizations to provide better needs and practical solutions to address the issues efficiently.