
AI in Cloud Computing: Key Benefits and Drawbacks
AI and cloud computing work together to improve many processes; however, the cost of combining these technologies is high.
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CIO Applications Europe | Wednesday, August 11, 2021

AI and cloud computing work together to improve many processes; however, the cost of combining these technologies is high.
FREMONT, CA: Artificial intelligence (AI) aids in automating typical IT infrastructure processes, resulting in increased productivity. When AI and cloud computing gets coupled, the result is a massive network that can store enormous quantities of data while learning and improving.
Because of tools from well-known public cloud providers, advanced AI and machine learning techniques are more readily available to businesses.
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Advantages of AI in cloud computing
Lower costs
Cloud computing provides the benefit of removing the expenditures of on-site data centers, like hardware and maintenance. These upfront costs can get prohibitive for AI initiatives, but in the cloud, enterprises can instantly use these technologies for a monthly subscription, lowering R&D costs.
Intelligent automation
AI-driven cloud computing allows businesses to be more efficient, strategic, and insight-driven. To increase efficiency, AI can automate complex and repetitive operations and execute data analysis without the need for human participation. IT teams can also use AI to oversee and monitor essential workflows. Thus, while AI handles tedious duties, IT personnel can concentrate on strategic operations.
Improved data management
In the processing, structuring of data, and management, artificial intelligence (AI) plays an important role. With more reliable real-time data, AI can significantly improve marketing, customer service, and supply chain data management. In addition, AI tools make it easier to acquire, modify, and manage data.
Increased security
Intelligent data protection is becoming increasingly important as businesses deploy more cloud-based apps. To watch and analyze network traffic, IT teams might employ AI-powered network security tools. When AI-powered systems detect an anomaly, they can raise a red flag. Such proactive technique aids in the prevention of data loss.
Disadvantages of AI in cloud computing
Connectivity concerns
Consistent internet access is necessary for cloud-based machine learning systems. IT departments utilize the internet to send raw data to the cloud and get processed data. Unfortunately, the benefits of cloud-based machine learning algorithms can get hampered by poor internet access.
Data privacy
AI applications need a large amount of data, which can include customer and vendor information. Though some data is anonymous and can also be linked to personally identifiable information, knowing who owns the data adds value. When sensitive data is valid, data privacy and compliance are critical issues. Therefore, businesses must develop privacy policies and secure all data when utilizing AI in cloud computing.
See Also: Top Cloud Solution Companies
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