Cloud computing and artificial intelligence, the two different concepts have now combined to produce better results. Examples are Siri, Alexa, Google Home, etc. all these devices expect nothing more than a vocal input. The users just need to say what they want, and within seconds it happens. Previously we used to say we get anything in just a fingertip, and now it is more advanced. Adjust the thermostat, turn on a light, or play a piece of music you prefer- the only effort you need to make is to speak a bit loud. However, the majority of users who enjoy these privileges, have no idea that the secret behind this reality is the combination of 2 huge spheres in technology. Namely Artificial Intelligence and Cloud Computing.
AI and Cloud Computing
When the AI capabilities are implemented into the business, we can make it more efficient, insight-driven, and strategic. Similarly, when introducing cloud computing to business, the advantages are flexibility, agility, and cost savings. Now let us take a detailed look at when these 2 come together.
Based on the studies of Statista, it is expected that the market of AI will go beyond 89 Billion dollars per year after 2025. But the point is that a remarkable percent of this value is achieved as a result of AI powering cloud computing. On the other hand, Cloud Computing makes the market of AI larger, by increasing its scope and impact.
Self-Managing Cloud with AI
The purpose of AI is to automate regular and repetitive tasks. And for the same reason, it is embedded into the IT industry to streamline workloads. It has later developed to become more sophisticated so that both private and public clouds will start to depend on AI tools for activities like monitoring, managing, and even handling a faulty situation. So that we can say that, even though AI was used initially to automate core workflows, later on, its analytical capabilities were also made use of.
Data Management with AI
Let it be any business, the data flow associated with it will be huge. Managing the data infrastructure includes data identification, data ingestion, and cataloging, etc. Fortunately, AI tools can also handle such data management activities. To explain this let us take the example of banking. Even the smallest financial organization will have to handle thousands of transactions each day. AI tools can assist in managing these transactions while analyzing the ingested and updated data. As a result, the financial organization can provide more accurate and real-time data to their clients. Likewise, with the same process, we can flag fraudulent or similar activities. The same is possible with other areas like marketing, customer service, logistics, etc. where huge data handling is necessary.
AI–SaaS Integration
SaaS providers now integrate the AI tools with their software suites, so that the end-users can enjoy better functionality and value. We will explain this with an example of Salesforce and the EinstienAI tool. Salesforce is a CRM, and so the main goal is to analyze data of customers and make it possible for an easier customer relationship and personalized interactions. However, the quantity of data to handle here will be enormous. Einstein is an AI tool introduced by Salesforce, to turn data into actionable insights and so the businesses can sell more alongside improving their sales strategies and engage more with customers. Moreover, the tool is capable of understanding the customer interaction pattern and makes suggestions based on that for the next step to take.
Dynamic Cloud Services
AI as a service is also transforming the ways companies depend on tools. Consider a cloud-based retail module that performs it more comfortable for brands to sell their goods. The module has a pricing characteristic that can automatically adapt the pricing on a returned product to account for problems such as requests, inventory levels, competitor sales, and market drifts. Complex analysis that’s based on modeling–pulling on deep neural networks–can give companies a much more reliable command of their data, with extensive real-time connections. An AI-powered pricing module such as this guarantees that a company’s pricing will perpetually be optimized. It’s not just about getting more regular use of data; it’s attending that analysis and then placing it into action without the requirement for human interference.
Conclusion
AI and cloud computing are changing business at each level. From more recondite learning to near-complete automation of key methods, the potential is encouraging. While there are some instances of this in the market now, a look at the scene suggests that this will only remain, but grow in the years ahead. Begin to examine how AI and cloud computing collectively could help you achieve more loyal practices, work more efficiently, and apprehend the maximum value from the data and insights you accumulate in the market. For AI assistance in your business, contact customer support at Ewaantech.