In the wake of the COVID-19 pandemic, there has been an exponential rise in the application and implementation of technology in businesses. Enterprises have realized that technology helps ascertain how smoothly they can readjust and habituate to emerging trends and new market opportunities. It also provides a basis for a competitive edge in a highly saturated market. Among the many upcoming technologies that have been utilized for this purpose, AI (Artificial Intelligence) is one of the most important.
AI is ubiquitous in today’s world and has proven to be transformative for businesses. It provides a platform for innovation and improvement while also helping develop agility and resilience in ever-changing circumstances. The integration of AI also helps cut costs and provides the ability to adapt and scale efficiently.
To create an IT framework that is AI-ready, it is vital to modernizing the IT environment with hybrid multi-cloud. Hybrid multi-clouds are also important for creating AI guidelines. The next section outlines why enterprises should consider building their hybrid multi-cloud with AI.
How AI Helps As Organizations Invest In Multi-Cloud Environments
Multi-cloud refers to the IT architecture that uses multiple cloud environments. Using this approach, businesses can pick the cloud providers and environments that apply best to their model, based on utilization or workload. Other issues like data privacy and security are also tackled efficiently.
As enterprises adopt a multi-cloud approach, research suggests that 78% of worldwide respondents are leaning on artificial intelligence for viable solutions. Organizations need to take up extensive multi-cloud management solutions that enhance cloud performance and cut costs while also comprehending the current infrastructure and maintaining vital aspects of it. AI offers organizations solutions to help compartmentalize the data that is created by technology systems through machine learning and deep learning, to identify, evaluate and act upon insights indicating potential issues. Some more benefits are listed in the section below.
Benefits
There are quite a few benefits as to why companies should move towards a tightly knit environment of Artificial Intelligence and multi-cloud deployments to improve the company’s performance, efficiency all while keeping the data secure and protected; thus giving an edge over their competitors.
Data Safety
It is risky to store a multitude of data and important records in a single location, as that creates a single point of failure. So from the point of view of disaster management, the multi-cloud approach is important, as it can help with on-premises integration.
With impending climate crises and other sudden changes in circumstances (e.g., accidents), physical data centers can be vulnerable to an array of calamities and leading to power outages and loss of connectivity. To protect themselves from the increasing risks, enterprises can build resilient data infrastructure by adopting a multi-cloud strategy.
Flexibility
The multi-cloud strategy allows organizations a sense of flexibility, security in how they decide to grow and scale their business. It enables them to manage and move their apps across different clouds flawlessly using tools and workflows offered by hosting providers through a unified platform. A multi-cloud approach also makes a decent financial impact as a business scales and the workload gets complex, as there will be scenarios where running a specific workload for cases turns out to be cheaper.
Application Ecosystems
In today’s reality, with the pandemic and changes in work structures, the majority of employees are following work from home to ensure the safety of the workforce. In many instances, this causes an organization’s workforce to be geographically dispersed. Employees working from home generally tend to work on unsecured home networks or devices shared with family members, allowing organizations very little control over the security of their corporate resources and data.
To protect themselves from potential security hazards, companies have started using remote desktop solutions that are completely owned and monitored by corporate IT, helping them make sure that corporate security standards are complied with. The remote desktop workspace then connects via a cloud VPN service or a private network to corporate resources stored either on-premises in a physical corporate data center or on another cloud provider’s platform, thus forming a multi-cloud ecosystem.
Predictive capabilities
The use of an AI-enabled platform can help discover recurring issues as well as monotonous tasks ideal for automation by identifying repetitive patterns from any data source. A well-designed AI system is then capable of dynamically learning the behavior of existing infrastructure and managing capacity efficiently. This includes multi-cloud utilization in the context of applications and services. These predictive capabilities enable IT teams to drastically reduce mean time to efficient issue resolution and identify false alarms.
Agility
Multi-cloud offers companies the advantage of using different cloud providers for different use cases. Previously, companies such as AWS had high paywalls if you wanted to port or switch between different cloud providers. But now, the right to data portability – thanks to laws such as CCPA (California Consumer Privacy Act) – is encouraging multi-cloud deployments at little to no cost. This offers greater choice and portability which improves agility.
Faster Response Time and Reliability
When choosing a multi-cloud approach, enterprises must consider some important factors like bandwidth and latency, especially in conditions where use-cases critically require a quicker response time for business success. In cases such as this, running AI projects over multiple cloud service providers ensure a certain amount of reliability, allowing business continuity by reducing the risk of downtime.
Conclusion
With the usage of Artificial Intelligence and multiple cloud platforms, it is important to have an overview of how your business’ data is processed in different cycles between different teams and individual employees. It is advantageous to have a seamless AI-optimized data highway for efficient data organization.
Having an AI backing your data management system will help you streamline the process of data flow, thus empowering automation and improving agility. If you take a proper view of how the data is processed across various modules and keep track of it, it would let you efficiently take an edge over your competitors in the industry.