Artificial intelligence and cloud computing are the two most emerging technologies of the present era. Combined, they can create a revolution and improve the lives of individuals. But do cloud computing and artificial intelligence depend on each other? How do they facilitate each other? Or what are the drawbacks of applying AI in the cloud? Working AI in cloud computing makes organizations more efficient, strategic, and insight-driven on a larger scale. As cloud computing offers businesses more flexibility, agility, and cost-effectiveness, the combination of AI and cloud computing is a favorable solution. But like other prospering technologies, AI in cloud computing is not an exception of pros and cons. Let’s look at what they are and how they affect the functionalities.

Related post – Why AI in edge computing is the next possibility?

What is AI in Cloud computing

AI in cloud computing is the combination of artificial intelligence with cloud-based computing environments. The most recent initiative we see in this field is AI in edge computing, an advanced form of cloud computing. Thus, we can say it is a paradigm shift in cloud space, as well. Before Edge computing came into the picture, Machine learning and Artificial intelligence depended on the cloud. Now, with Edge computing edge AI has gained potential benefits. Now it is all about processing real-time data and the ability to respond fast in IoT-related activities. Besides, it serves better security features.

Not to mention, Edge computing has overcome the issue of agility, which is good in cloud computing but not enough. When IoT and cloud computing came into the market at the initial level, they dealt with dumb machines. Now, as intelligence is amalgamating with it, AI-enabled edge devices will create a new landscape. 

As per one statistic, the generations of AI edge devices will increase from 161.4 million to 2.6 billion units within 2018 – 2025. Furthermore, the categories will range in all sectors from daily use smart devices to health sensors or building sensors, and many more.

Edge Computing at the present scenario delivers three critical capabilities from the data point of view, whether it is AI-related or IoT –

• Faster decision making
• Transferring filtered data
• Local data processing

Benefits of AI in Cloud Computing

Without a strong, agile improvement process on the cloud, enterprises are more likely to fail in translating their ideas despite a strong cloud strategy. This can be rectified using AI. So, the usage of AI in cloud computing will become inevitable to reflect on the benefits. Here are top benefits of using AI in cloud computing are: 

Reshaping IT Infrastructure

One of the top benefits of AI in cloud computing refers to the reshaping of IT infrastructure. Nowadays, we see an increased competition that needs an inevitable need for sustaining. Therefore, the usage of AI-optimized application infrastructure is essential.

Data Mining Applications

To identify helpful information, the usage of AI in cloud computing is unconditional. The need for responsive cloud environments is evident with the increase in the incoming data each year. AI can help to achieve it. AI can help in managing the considerably massive volumes of information of the data. This also increases the responsiveness of the cloud environment. 

Analytical Advantages

Implementing AI in the cloud is a promising area for analytics. Evaluation of statistics for analytics can take the efforts of multiple teams to find relevant and meaningful insights. So, implementing AI in the cloud can help take off the burden of human effort, eventually becoming an economic benefit. On an overall basis, with AI, you could achieve better outcomes and at considerably lower prices than analysts.

Reduction of Costs

The combination of artificial intelligence and cloud computing aims at reducing costs as for on-premise data centers, there is no requirement of expenses. This is another terns is a great way of cost savings in research and development processes. Enterprise or a company can access the cloud to gain research insights without additional costs. Overall, the company can save a lot of money from both sides by using AI and the cloud.

Cloud Security Automation

Cloud Security is a burning area and one of the primary concerns in the present time. Usage of AI in cloud computing can help in cloud security. Implementation of AI in the cloud could process the information on cloud infrastructure and detect inconsistencies immediately. As a result, the AI can prompt caution for a human or respond through other alternatives. 

Furthermore, AI could detect any anomalies and block them. It can help human security teams to prioritize their work and address their tasks effectively. 

Better Decision Making

Decision-making is an important aspect of every organization. A combination of AI in the cloud can bring out the best result in making out decisions. AI helps identify patterns and trends in different datasets by learning from historical data and comparing current patterns in the data. Also, AI is responsible for faster data analysis that can help businesses resolve customer requirements easily with high accuracy. So, the working of AI and cloud together can generate positive outcomes.

Disadvantages of AI in cloud computing

As AI in cloud computing has numerous benefits, yet they have drawbacks as well.

 The following are the other disadvantage of using AI in cloud computing environments:

Connectivity concerns

Consistent connectivity is a need for AI in cloud computing. Poor internet access can hinder the advantages of cloud-based AI resources. 

Processing data in the cloud is quicker than conventional computing, but there is a latency issue in the cloud which creates a time lag in receiving responses. We might face this issue when using machine learning algorithms for the cloud servers, where prediction speed is one of the primary concerns.

Data privacy

AI applications are data-based; hence, they require a large amount of data, including customer and vendor information. Enterprises use a lot of sensitive information that can be targeted for data breaches by hackers. Hence, enterprises need to create privacy policies and secure all data when using AI in cloud computing.

Integration

Integration challenge is always there whenever two technologies come together. An enterprise or an organization needs to completely move its applications and technologies to the cloud before adding the AI layer. This itself is a massive challenge for many enterprises. Only after that, an enterprise can work on concreting the digital transformation of their infrastructure.