Cloud computing services have morphed from platforms such as Google App Engine and Azure to Infrastructure which involves the provision of machines for computing and storage. In addition to this, cloud providers also offer data platform services which span the different available databases. This chain of development points in the direction of the growth of Artificial Intelligence and Cloud Computing.[3]

Figure 1. The AI in Cloud Computing

Figure 1 shows The AI cloud, a concept only now starting to be implemented by enterprises, combines artificial intelligence (AI) with cloud computing. Two factors are driving it: AI tools and software delivering new, increased value to cloud computing which is no more just an economical option for data storage and computation but playing a significant role in AI adoption.[4]

The Role of AI and Cloud Computing

According to Statista, the global value of the AI market will surpass more than an estimated $89 billion annually by 2025. A significant percentage of that value will occur as artificial intelligence powers cloud computing—and, in turn, as cloud computing acts as an engine to increase the scope and impact AI can have in the larger market.

McKinsey recently conducted a study to explore how AI could impact value creation in a range of industries. They estimate that across 19 business areas and more than 400 potential use cases, AI could create $3.5 trillion and $5.8 trillion per year in value. That number is actually conservative, because it reflects a specific sub-segment of AI techniques. More broadly, McKinsey estimates the impact could be as large as $15.4 trillion per year.[2]

The benefits of AI in cloud computing

• Enhanced data management: We live in a data-driven world with countless data out there. Simply managing that data is a huge challenge that enterprises face. AI tools and applications that run over the cloud that help to manage data effectively by identifying it, updating it, cataloging it, and offer real-time data insights to customers. AI tools also help in detecting fraudulent activities and noticing some patterns in the system that look out of place. Financial institutions and banks are heavy users of this technology, this allows them to stay relevant and secure in very risky environments.
• Automation: This combined technology of AI and cloud removes the barriers to Intelligent automation and enables enterprise-wide rollout across the organization. AI brings in predictiveness as algorithmic models provide real-time insights based on data pattern, historicity, etc. Leveraging AI and cloud computing solutions can generate forces of hyper-automation for enterprises as it will not only bring in cognitive automation on semi-structured and unstructured documents but also push boundaries for effective infrastructure management thereby ensuring minimum disruption. This leads to cost transformation for enterprises and transformative end customer experience.
• Cost Savings: The adoption of the cloud enables enterprises to only pay as much as they use. This is a huge cost saving over traditional infrastructure costs of setting huge data centers and managing them. The cost saved from this arrangement can be used to set up the more strategic development of AI tools and accelerators that can be further used to generate greater revenue and save fundamental costs for the enterprise.[1]

References:

1. https://www.devopsonline.co.uk/the-role-of-ai-in-cloud-computing/
2. https://community.connection.com/4-ways-ai-is-improving-cloud-computing/
3. https://www.goodfirms.co/blog/role-of-ai-in-cloud-computing
4. https://www.thehindubusinessline.com/opinion/understanding-ai-cloud/article34635575.ece

Cite this article:

Thanusri swetha J (2021), AI in Cloud Computing, Anatechmaz, pp. 32