The ever-changing business conditions encourage enterprises to transform and become more flexible and intelligent. Cloud migration is a natural step for many companies on their journey to digital transformation, so they invest vast resources in cloud platforms, with Azure and AWS ahead of the curve.
Thanks to cloud implementations and the emergence of technologies such as AI and IoT, companies are evolving, and cloud solutions are getting more intelligent as well. This article will reveal what makes cloud solutions intelligent and provide some applications of the intelligent cloud.
What Makes Cloud Solutions Intelligent
The intelligent cloud is often understood as a combination of typical cloud capabilities with some AI-powered features, but this view doesn’t reflect the whole picture. Indeed, the development of AI has made a significant contribution to the emergence of intelligent cloud products; still, the intelligent cloud is broader, and it’s not just about increasing computing powers or data storing capabilities.
With the increase in computing power, the amount of data being continuously collected from various devices has increased drastically. This gave impetus to the convergence of technologies such as the cloud, AI, and the internet of things, which led to the emergence of multi-device cloud functionality. Thanks to this capability, companies can now collect data from many devices and synchronize it with the cloud at all times.
Consequently, the increasing amounts of collected data raise the need for effective and smart data management, and here the combination of AI and big data comes into play. As cloud software evolved, businesses became able to process vast amounts of information and draw actionable insights via predictive, cognitive and prescriptive analytics.
Still, for enterprises, efficient data collection and processing is not yet a guarantee of business success. After all, insights are useless if they are not converted into action, and this is impossible if data is not synchronized between different departments, be it Marketing, Finance, Sales, or IT.
For this reason, companies use intelligent cloud software that synchronizes and analyzes cross-departmental data, which allows to remove communication and collaboration issues and narrow the gap between insights and actions.
Now it’s time to look at some existing intelligent cloud capabilities that enterprises can apply. Of course, this list doesn’t show a complete picture but highlights several opportunities. To get an in-depth understanding and align the technology with their business needs, enterprise executives typically get cloud consulting.
The Varieties of Intelligent Cloud
Cloud for AI
Migrating to the intelligent cloud, enterprises can cost-effectively integrate a wide range of AI-powered capabilities into their workflows. Here are just a few examples of what can be implemented.
Machine Learning Models
Today, several cloud platform providers offer functionality focused on helping enterprises build and deploy machine learning models. For instance, Azure Machine Learning tools help organizations forecast demand, personalize marketing and sales campaigns, segment customers, and manage inventory.
If the company’s goal is to improve data security, then Amazon Fraud Detector may come in handy. This tool allows enterprise security experts to automate building and training models for fraud detection and customize these models to tailor them to the needs of a particular business.
If an enterprise processes large volumes of text, text mining tools like Google Natural Language AI or Azure Text Analytics can help automate this process and make it faster and more cost-effective.
This type of software automatically analyzes large sets of textual information, finds specific patterns and connections between different elements, and offers insights based on the analysis.
From a business perspective, this functionality allows enterprises to improve customer experience, streamline document management, and increase employee productivity as team members can quickly get the information they need.
A significant difference between typical chatbots and their intelligent counterparts is that smart ones are powered by AI and machine learning. In practice, this difference gives smart bots an inherent advantage because they constantly analyze human behavior and learn.
In the customer service field, smart bots can improve customers’ experience as well as gathering consumer data (for example, most frequent requests), which can be valuable for adapting the company’s marketing and sales strategies.
Enterprises considering intelligent bot development and implementation may look up to a range of cloud providers: Microsoft, Amazon, and Google are among them.
Cloud for IoT
Cloud IoT technologies allow enterprises to implement and manage a system of connected devices, such as industrial and commercial IoT.
Commonly, industrial IoT is used by manufacturers to remotely control industrial systems or increase their productivity. Unlike industrial IoT, commercial IoT is focused on remote tracking and control of offices. Smart Building and Office, Smart HVAC, and Connected Lighting are often installed in commercial IoT systems.
Cloud for big data
The leading players in the cloud market offer various solutions for storing and analyzing large amounts of data, so an enterprise has many options to choose from. For example, a company can implement Amazon EMR, a big data platform compatible with Apache Spark, Presto, and Hive frameworks; others may consider Azure Databricks, which offers native Azure Active Directory integration. Like Google’s BigQuery Omni, some of the solutions even allow users to analyze data stored by other cloud providers, for example, Azure and AWS.
New times pose new challenges for enterprises, and migrating to the intelligent cloud is one of the best ways to remain competitive, optimize internal processes, and boost team productivity. Compared to traditional cloud solutions, intelligent cloud platforms allow companies to quickly and cost-efficiently implement AI-based capabilities, be it intelligent chatbots, industrial IoT, or big data analytics.