The advantages and disadvantages of AI in cloud computing
Cloud computing offers businesses more flexibility, agility, and cost savings by hosting data and applications in the cloud. AI capabilities are now combining with cloud computing and helping companies manage their data, look for patterns and insights in information, deliver customer experiences, and optimise workflows.
We take a look at some of the benefits and drawbacks of AI in cloud computing.
The benefits of AI in cloud computing
A major 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 restrictive with AI projects, but with cloud enterprises you can access these tools for a monthly fee, making research and development related costs more manageable. AI tools can also gain insights from the data and analyse it without human intervention, reducing staff costs.
AI is able to identify patterns and trends in large data sets. Using historical data, AI compares it to the most recent data, which provides IT teams with well-informed, data-backed intelligence. AI tools can also 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.
Improved data management
AI enables extensive data management, and cloud computing maximises information security, making it possible to deal with massive amounts of data in a programmed manner to analyse them properly, allowing the business to leverage information that has been “mined” and filtered to meet each need. AI can also be used to transfer data between on-premises and cloud environments.
Businesses use AI-driven cloud computing to be more efficient and insight-driven. AI can automate repetitive tasks to boost productivity, and also 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.
With businesses deploying more applications in the cloud, security is crucial in order to keep data safe. IT teams can use different AI-powered network security tools which can track network traffic, they can flag issues, such as finding an anomaly.
The drawbacks of AI in cloud computing
Enterprises need to create privacy policies and secure all data when using AI in cloud computing. AI applications require a large amount of data, which can include consumer and vendor information. While some data can be anonymous and can't be tied to personally identifiable information, knowing who the data belongs to makes it more valuable. When sensitive information is used, data protection and compliance is a major concern.
IT teams use the internet to send raw data to the cloud service and recover processed data. Poor internet access can hinder the advantages of cloud-based machine learning algorithms, as cloud-based machine learning systems need consistent internet connectivity.
While processing data in the cloud is quicker than conventional computing, there is a time lag between transmitting data to the cloud and receiving responses. This is a significant issue when using machine learning algorithms for cloud servers, where prediction speed is one of the primary concerns.
ManageEngine Survey Finds Global AI Use Increase
ManageEngine, the enterprise IT management division of Zoho Corporation, has announced results from its recent market study, The 2021 Digital Readiness Survey, finding that 86% of organisations worldwide are using artificial intelligence (AI) more than they did two years ago. However, only 35% of the global respondents reported that their confidence in the technology has significantly increased.
The focus of the study was to understand technological changes in a post-COVID world, in areas such as remote work, security, business analytics, and AI. It was found that organisations worldwide mainly increased their use of AI to improve business analytics (63%), increase operational efficiency (62%) and enhance the customer experience (60%). While a majority of global respondents (94%) believe that AI will meet business expectations—and 65% stated AI had delivered measurable business results—some fears remain around the technology’s performance.
“The potential for AI to improve business efficiency and the customer experience was firmly on show through 2020, with AI handling everything from increased customer service volumes to oversight of self-service processes,” said Rajesh Ganesan, vice president at ManageEngine. “While AI is being handed more responsibility and is applied in more business-critical use cases, our research shows this is a double-edged sword and that more work is needed to embrace the technology and lift internal capability to ensure AI achieves its promise.”
Is business analytics the key to success?
The growing use of AI coincides with a broader trend of using analytics to improve the use of available data and the speed and accuracy of decision-making. In the post-pandemic era, profitability and competition are also driving organisations across the world to invest in business analytics platforms and capabilities.
Business analytics is an umbrella term for several types of analytics—descriptive, diagnostic, predictive and prescriptive.
The biggest user of business analytics by far is IT. An average of 63% of IT departments worldwide cited this in the survey. However, in North America, 67% of executives noted their use of business analytics, which was higher than their IT departments’ use (61%). Business areas such as marketing, sales, human resources, operations and R&D are also showing interest in business analytics but are well behind IT and executives on adoption and actual use.
Other key global findings of the survey
– A mighty 96% of organisations are planning to continue supporting remote workers for the next two years. Concerningly, the report also found that 84% of IT professionals believe that remote workers have increased their enterprise’s security risk.
– More than half (56%) of respondents stated that improving their security infrastructure is a key driver of adopting new technologies.
– 78% of organisations revealed that remote workers download software without obtaining approval from the IT department; this shadow IT mainly included mobile-specific applications (40%), online meeting tools (38%) and document sharing solutions (31%).
– 84% of respondents use more cloud services now than they did before the pandemic began. However, most respondents believe that improved security (56%), performance (52%) and reliability (51%) would increase their company’s confidence in cloud-based solutions.