Artificial intelligence in cloud computing: When machine learning meets unlimited data

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  Quantumrun Foresight
• December 26, 2022

Insight summary

AI cloud computing is reshaping how businesses operate by offering data-driven, real-time solutions across various industries. This technology combines the vast storage capabilities of the cloud with the analytical power of AI, enabling more efficient data management, process automation, and cost savings. The ripple effects include everything from automated customer service to increased workplace efficiency, signaling a shift toward more agile and flexible business models.

AI in cloud computing context

With large database resources available in the cloud, artificial intelligence (AI) systems have a playground of data lakes to process in the search of practical insights. AI cloud computing has the potential to bring into the different industries automated solutions that are data-driven, real-time, and agile.  

The introduction of cloud computing has changed IT services in irreversible ways. The migration from physical servers and hard disks to what seems like unlimited storage—as offered by cloud service providers—has enabled enterprises to choose piecemeal which subscription services they want to complement their data storage needs. There are three main types of cloud application development services: Infrastructure-as-a-Service (IaaS, or renting networks, servers, data storage, and virtual machines), Platform-as-a-Service (PaaS, or the group of infrastructures needed to support apps or sites), and Software-as-a-Service (SaaS, subscription-based application that users can readily access online). 

Beyond cloud computing and data storage, the introduction of AI and machine learning models—such as cognitive computing and natural language processing—has further made cloud computing increasingly fast, personalized, and versatile. AI operating in cloud environments can streamline data analysis and provide organizations with real-time insights into process improvements that are personalized to the end-user, allowing for worker resources to be more effectively deployed.

Disruptive impact

AI cloud computing being leveraged by corporations of all sizes offers several benefits: 

• First, is optimized data management, which covers many critical business processes, such as customer data analysis, operation management, and fraud detection. 
• Next is automation, which eliminates repetitive tasks prone to human error. AI can also use predictive analytics to implement improvements, automatically leading to minimal disruptions and downtime. 
• Companies can lower staffing and technology infrastructure costs by removing or automating labor-intensive processes. In particular, companies can achieve an excellent return on investment from capital expenditure on cloud services. 

These services will be selected as needed, compared to investing in technologies that may not be necessary or become obsolete in the near future. 

The savings gained through lower staffing and technology overhead costs can potentially make organizations more profitable. Savings can be redeployed in a given business to make it more competitive, such as raising salaries or providing workers with increased skill development opportunities. Companies may increasingly seek to hire workers who have the necessary skills to work in conjunction with AI cloud services, leading to these workers being in high demand. Businesses may become increasingly agile and flexible since they would no longer be restrained by built environment infrastructure to scale their services, especially if they used work models that leveraged remote or hybrid technologies.

Implications of AI cloud computing services

Wider implications of AI being used within the cloud computing industry may include:

• Fully automated customer service and relationship management through chatbots, virtual assistants, and personalized product recommendations.
• Workers in large organizations gaining access to personalized, workplace, AI virtual assistants that assist in their daily job activities.
• More cloud-native microservices that have centralized dashboards and are updated frequently or as needed.
• Seamless data sharing and syncing between hybrid setups of on-service and cloud environments, making business operations more efficient and profitable. 
• Economy-wide growth in productivity metrics by the 2030s, especially as more businesses integrate AI cloud services into their operations. 
• Storage concerns as cloud service providers run out of space to store massive enterprise data.

Questions to consider

• How has cloud computing changed the way your organization consumes or manages online content and services?
• Do you think cloud computing is more secure than a company using its own servers and systems?