The cloud has emerged as more than a means of computing power. Cloud storage and platforms also help companies modernize their work practices by driving more efficient work practices, saving time and money, and driving innovation.
Cloud-based artificial intelligence (AI) technologies, including machine learning, are helping companies add value as the amount of data they collect continues to grow.
From logistics companies that analyze the efficiency of transportation networks to e-commerce brands that test website performance in real time, AI algorithms enable companies to gather new insights from their data and improve their way of working.
Companies that don’t have the budget or talent to build their own AI infrastructure (many companies don’t) can take advantage of the AI infrastructure by running the cloud service provider’s system.
Automation is an important driver of cloud adoption, especially when it comes to improving the efficiency of business operations.
By centralizing data and systems in the cloud, enterprises can automate many of their internal processes, such as integrating data from different locations and creating business intelligence dashboards.
Today, many organizations are trying to strengthen the connectivity between different software with the goal of better managing their growing cloud footprint and ensuring that solutions from different vendors work together seamlessly.
As more vendors launch solutions that can be hosted on external servers, some companies will choose to outsource some of their IT operations to third parties.
Instead of hiring a dedicated team to build, manage, and maintain the system, companies can reduce operational costs and focus on their core products or services.
However, sensitive data and technology must be considered when deciding which operations to outsource so as not to compromise governance or compliance practices.