Benefits and drawbacks of AI in cloud computing
Lower costs
A big advantage of cloud computing is that it eliminates costs related to on-site data centers, such as hardware and maintenance. Those upfront costs can be prohibitive with AI projects, but in the cloud enterprises can instantly access these tools for a monthly fee, making research- and development-related costs more manageable. Additionally, AI tools can gain insights from the data and analyze it without human intervention.
Intelligent automation
Enterprises use the power of AI-driven cloud computing to be more efficient, strategic and insight-driven. AI can automate complex and repetitive tasks to boost productivity, as well as perform data analysis without any human intervention. IT teams can also use AI to manage and monitor core workflows. IT teams can focus more on strategic operations while AI performs the mundane tasks. For example, IBM Cloud Pak for Automation provides prebuilt workflows for AI-powered automation.
Deeper insights
AI can identify patterns and trends in vast data sets. It uses historical data and compares it to the most recent data, which provides IT teams with well-informed, data-backed intelligence. On top of that, AI tools can perform data analysis fast so enterprises can rapidly and efficiently address customer queries and issues. The observations and valuable advice gained from AI capabilities result in quicker and more accurate results. For example, an app developer can use Amazon Personalize to give customers real-time personalized recommendations.
Improved data management
AI plays a significant role in processing, managing and structuring data. AI can significantly boost marketing, customer care and supply chain data management with more reliable real-time data. AI tools streamline how data is ingested, modified and managed. For example, IT teams can imbed AI tools into Google Cloud Stream analytics to get real-time personalization, detect anomalies and predict maintenance scenarios.
Increased security
As enterprises deploy more applications in the cloud, intelligent data security is crucial to keep data safe. IT teams can use AI-powered network security tools to track and evaluate network traffic. AI-powered systems can raise a flag as soon as they find an anomaly. This proactive approach helps prevent any damage to critical data. For example, Amazon GuardDuty is an intelligent threat detection tool that uses AI and machine learning to find potential risks.
