AI and cloud are radically changing the way business is done. The combination catapults growth to newer heights. As we look ahead to 2024, enterprises are banking on the goodness of AI to accelerate growth plans and stay relevant. Believe it or not, the era of AI is already upon us. Ever since Gen AI took the technology space by storm, AI and all that it has spawned are being integrated into the digital business process. It is well recognized that AI, together with its subsets of ML and Neural Networks, significantly reduces costs, boosts productivity, enables automation, and stimulates innovation and corporate transformation.
In contrast, the Cloud has a shorter history than AI. Debuted in 2006 with the launch of Amazon Web Services (AWS), it was originally sold as a cheaper alternative to the data center. Today, the cloud has gone beyond an inexpensive alternative to on-premises storage. In our previous blogs, we have presented a comparative analysis of On-premise and cloud storage and also expounded on the merits of migration from private cloud to public cloud storage. Read this blog to explore the significance of AI in cloud storage for enterprises.
With a Compound Annual Growth Rate (CAGR) of 17% between now and 2030, the cloud market is projected to hit a lofty $1.6 trillion by 2030.
According to a report in eWeek, AI boasts of an even more remarkable trend line. Growing at a fevered 38% CAGR, AI revenues are forecasted to zoom up to $1.8 trillion by 2030.
Well, it’s the combined revenue that’s the real stunner. Assuming the forecasts for 2030 are correct, adding the cloud’s $1.6 trillion to AI’s $1.8 trillion, that is the combined AI-Cloud market will be a jaw-dropping $3.4 trillion by the end of this decade.
As more and more applications leverage AI, stimulated by consumer demand for improved products, and increased personalization, the amount of data will explode. These various types of data will need to reside someplace– so far it has been residing on-premises on servers, desktops, laptops, etc. In order to harness the power of this data, which is fuel for AI to bring about innovation, a pivotal component called, “Storage,” is the need of the hour. And where better a place to store the data – the Cloud.
The Synergy of Artificial Intelligence and Cloud Storage: Its Significance for Enterprises
Machine Learning (ML) models are constructed when algorithms run on large datasets, and the more data delivered better the results. This requires extensive computing power which can be furnished by cloud service providers. Moreover, enterprises need not invest in any additional hardware or infrastructure when using cloud storage, thus making it accessible and cost-effective for all-sized companies when adopting ML-driven solutions. This approach brings automation of processes, and enhanced strategies and helps reduce costs, improve efficiency, augment customer experiences, and equip enterprises with a competitive edge.
Awareness of the difference between traditional and present-day cloud storage, helps gain a better perspective of how AI and cloud storage will work for an enriched future. AI & Cloud are drivers and motivators feeding each other in a continuous loop.
The table below displays the key differentiating parameters of cloud and traditional storage solutions.
| Parameters | Cloud Storage | Traditional Storage |
| Performance | Cloud storage performs better due to using NoSQL | Traditional storage performs a bit slow as compared to cloud |
| Data Sharing | Data is available anytime & anywhere | Data is in silos and fragmented |
| File Sharing | Dynamic file across geospatial spectrum | Requires physical drives to share data |
| File access time | Only dependency is network speed | Faster access as compared to cloud storage |
| Maintenance | Easy to maintain and the service provider takes care of maintenance | Difficult to manage and requires manual maintenance |
| Reliability | Highly reliable | Less reliable |
| Security | Secure but cyber security is currently a concern | Secure but viruses and malware can be a disadvantage |
| Backups | Can handle backups quickly and space-wise viable | Space constraints and major time investment |
AI & Cloud Storage offers the optimal blend of speed, scalability, and adaptability
With AI, cloud service providers can easily implement storage and maintenance of data with ease, given automation of tasks and forecasting capabilities. Not just providing security of data, but also intelligent data management. The role of data in the enterprise is changing as “intelligent data” is now being seen as a support to digital transformation. With AI capabilities in cloud storage, organizations can get better insight into the data, understand the context and the content of it, and enrich the management and quality of the management process.
With Cloud and AI capabilities, data is no longer in the danger of being kept in silos, but accessible across the geospatial spectrum, making it easier to handle and provides for a higher capacity to process extensive datasets rapidly and efficiently.
The cloud has been viewed as the platform where data is stored and easily accessible. Now combined with AI capabilities, data can be intelligently analyzed for deeper insights across the organization. Thus, the cloud with AI capabilities is now seen in terms of data processes rather than just data movement and storage.
Thus, for enterprises, the benefits of using intelligent data management incorporating the synergy of AI and cloud storage provide for:
Although Cloud storage is relatively new, yet rapidly evolving thanks to the 2019 pandemic, caution needs to be still maintained.
Cloud AI enables real-time data analysis and insights, which can facilitate informed decisions. Some key drivers that support AI-based Cloud Storage are:
Automation: Using AI-based tools data can be intelligently managed and inform where data is stored.
Predictive Performance: Cloud-based AI provides insights into how the storage infrastructure is performing and suggests ways in which it can be made more responsive or more secure.
Parallel Processing: Due to AI workloads and the use of Gen AI and LLMs, the use of Graphics Processing Units (GPUs) is needed to offload processing from Central Processing Units (CPUs), and also provide portability of data between locations to enable the most efficient processing.
Scalability: Easily scale its AI/ML solutions on a need-basis, without having to invest in additional hardware and infrastructure. Responds to changing business requirements and avoids costly downtime and delays.
Cost efficiency: Using the cloud with AI capabilities lets you pay for what is used.
Access to advanced technologies: Cloud storage provides for pre-built models, algorithms, and advanced computing resources.
Flexibility: Provides for wide deployment options, including on-demand, pay-per-use, or hybrid deployment models or a combination of on-premises and Cloud depending on applications and confidentiality.
Data Management: Cloud providers offer various data management services like data lakes, data warehouses, and databases to store and manage data in a scalable way.
Acceleration of new solutions & products: By leveraging on-demand computing resources and processing capabilities, one can gain valuable insights and fuel innovation to set products and services apart from the competition.
Safety: The best way for businesses to keep large quantities of easily accessible data safely is by keeping at least one copy of it in the cloud. Moreover, proprietary data for custom AI applications must be kept safe.
AI with its many sub-elements like deep learning, neural networks, Large Language Models (LLMs), and Gen AI, all require cloud space to train models on the datasets. With the introduction of ChatGPT in 2023, one of the most engaged of all other Gen AI tools, at work or personal, the amount of data being generated and needed has increased. This has led to many organizations adopting AI capabilities to embed Gen AI tools into their business process. As we know traditional AI excels in analyzing and automation, while Gen AI drives content generation in various data formats – images, text, audio, and video. Further, Gen AI can augment, automate, and bring efficiency to data management tasks, even in the privacy and Intellectual property domain. To handle such multifaceted data storage solutions, the Cloud becomes essential.
AI has expanded and Gen AI a subset of AI has now emerged and is pushing enterprises towards innovation. This innovation is based on real-time dataset analysis. Gen AI was introduced in the 1960s in chatbots. But it was not until 2014, with the introduction of generative adversarial networks (GANs)- a type of machine learning algorithm — that Gen AI emerged as a full-fledged digital technology. Gen AI, today, encompasses sophisticated ML models that generate text, images, audio, and other complex outputs. This complexity and capability are insatiable and look for vast, diverse, and ever-expanding datasets. These escalating data requirements are providing for a paradigm shift in how enterprises approach data, data management, and cloud storage. Gen AI is bringing about a digital transformation across all industries.
As AI models become more complex and scalable, varied and multifaceted data necessitates efficient storage solutions to handle the data-intensive workloads associated with Gen AI.
We are now seeing a steady but strategic adaptation to the demands posed by Gen AI. This adaptation is emerging as hybrid cloud storage with its blend of on-premises and cloud-based resources. The image below shows the Hybrid cloud and the Gen AI framework.
The traditional on-premises storage systems are robust and secure but lack scalability and flexibility to handle large and dynamic real-time data volume.
Cloud storage offers scalability but can sometimes fail in areas of data sovereignty and latency-sensitive operations.
The Balanced Solution: The hybrid cloud model offers.
Hybrid Cloud and Gen AI Framework
The convergence and synergy that AI and Cloud storage bring to the digital landscape is leading to an innovative atmosphere. AI will need storage which will continue to AI’s need for ever-more storage will continue to drive the cloud’s growth. As AI grows, so too will cloud storage, each feeding the other!
We, at Calsoft, being a Technology-First company and a pioneer in software product engineering services, are the front runners in guiding enterprises to drive beyond their digital boundaries using a balanced approach in the transformative AI and Cloud landscape.
