Recent years have seen AI transform from a mere concept to providing practical business applications
Artificial Intelligence (AI) and cloud computing have been leading digital transformation for several years now. As we approach 2023, experts predict that AI will reach a tipping point, and businesses across all sectors will seek to capitalize on its capabilities. Technology organizations must be prepared to take advantage of this opportunity by utilizing cloud-based AI technologies in their operations.
The cloud offers various benefits to AI, such as flexibility, scalability, cost-effectiveness, and access to advanced technology and resources. Consequently, an increasing number of businesses and organizations are turning to cloud-based AI solutions to improve internal processes and efficiency.
The potential rewards of cloud-based AI are numerous and varied, ranging from enhanced customer experiences and greater operational efficiencies to lessened costs due to streamlined processes and improved data analysis insights. However, businesses must act quickly to keep up with the rapid advancements in cloud-based AI technology being made year after year.
By 2030, artificial intelligence is expected to contribute $15.7 trillion to the global economy, according to PricewaterhouseCoopers estimates. Research indicates that 45% of total economic gains by 2030 will come from product enhancements that stimulate consumer demand, as AI drives greater product variety with increased personalization, attractiveness, and affordability.
Despite the innovative solutions AI and machine learning (ML) offer businesses, many companies are yet to harness their power. This is mainly due to organizations’ main challenge revolving around the resources needed to incorporate AI/ML into their existing workflows and processes. Cloud computing AI/ML services can help overcome this obstacle.
Here are some of the ways businesses can leverage a cloud-based AI platform for flexibility and scalability:
Flexibility and scalability
Cloud-based AI platforms offer businesses and organizations a range of benefits, including flexibility and scalability. These advantages allow companies to adapt their AI solutions quickly and efficiently to changing needs and circumstances. The cloud infrastructure makes it easy to provision and de-provision resources, enabling businesses to scale up or down as necessary. This enables them to respond quickly to changes in demand and optimize the use of resources, which can be particularly helpful in managing cost.
One of the significant benefits of cloud-based AI solutions is their ability to offer flexibility and scalability to businesses of all sizes. Small businesses can leverage these tools by keeping costs low since they pay only for the services they use, making it feasible for small businesses to use these technologies even when they do not need them often.
By leveraging the cloud infrastructure, companies have access to the latest AI technologies, allowing them to stay ahead of the competition. The cloud infrastructure enables organizations to access data from multiple sources without relying on physical servers or data centers. With the help of cloud-based AI solutions, businesses can easily manage large datasets, analyze vast amounts of data and use the insights obtained to make informed decisions.
Furthermore, cloud-based AI solutions provide businesses with the flexibility to try out new applications and technologies without significant investments in infrastructure or hiring a dedicated team of AI experts. With a cloud-based AI platform, businesses can deploy new applications and run them quickly, experiment with new models and ideas, and iterate as needed.
The cost-effectiveness of cloud computing has been a game changer for businesses in recent years. While many industries have experienced constant inflation, cloud computing costs have continued to decrease. This is because more companies have entered the market and competition has grown, leading to greater efficiencies in the process of providing cloud computing services. With the ability to reach economies of scale, businesses providing cloud computing services are able to heavily compete on prices. As a result, more businesses can now afford to utilize cloud computing services.
AI tools have also benefited from cloud computing, as they can now be offered as a cost-effective solution to customers without requiring high upfront costs or extensive training. By providing AI tools over the cloud, companies can offer a more accessible solution to businesses of all sizes. This trend is set to continue in 2023, as cloud-based AI becomes even more cost-effective.
A cloud-based AI platform offers businesses the opportunity to avoid the upfront costs of purchasing and maintaining expensive hardware and infrastructure. Companies can instead pay only for the computing resources they need, when they need them, and avoid the costs associated with idle resources. This can result in significant cost savings, particularly for small and medium-sized businesses that may not have the resources to invest in expensive hardware and infrastructure.
Increasing Data Needs
In today’s world, almost every industry is collecting more data than ever before, with a growth rate of around 42% each year over the past two years, as reported by Statista. Furthermore, the collected data is more varied and complex than it has ever been. This increase in data collection is driven by the expansion of customer bases and the need to keep up with the competition.
To manage the growing demands of data, many companies must invest in new hardware and software solutions. The challenge of managing this growth can be prohibitively expensive for larger companies in terms of resources, personnel, and other costs. Smaller companies have even fewer resources available to them, making it even more challenging for them to manage their growing data needs.
Cloud-based AI has emerged as a solution for businesses to fully leverage the increase in data demands. The cloud infrastructure provides the necessary resources and scalability to handle large and complex data sets, allowing businesses to process and analyze the data in real-time. This can lead to insights that help businesses improve operations, drive innovation, and generate new revenue streams.
Edge computing facilitates low-latency data processing at the source of data generation, minimizing the need to transmit significant data volumes to the cloud for processing. By processing data closer to the source, real-time decision-making based on the data becomes possible. Edge computing is essential for applications requiring real-time processing, such as smart cities, industrial automation, and autonomous vehicles. Edge computing relies on cloud-based AI to collect, store, and process data in a single location.
The combination of AI and edge computing is a perfect match because of their ability to work together efficiently. By leveraging edge computing’s power, AI-driven applications can process data more efficiently and quickly, leading to faster decision-making in real-time. This is particularly important when working with extensive datasets as it enables AI systems to operate without relying on an external server.
Furthermore, edge computing allows organizations to keep their data secure while taking advantage of AI’s capabilities. As more businesses explore the potential of intelligent systems, the collaboration between AI and edge computing will become a crucial aspect of innovation in the tech industry.
You may also like
Appdome and GitHub Unite Forces, Transforming Mobile App Security for CIOs
NTU Singapore and Delta Electronics Establish S$24 Million Lab for Advanced Robotics
Optimizing Hybrid Cloud Costs with Cloudera Observability
Asia Pacific’s Tech Spend on the Rise, Unveiling Lucrative Opportunities for CIOs
69% of Workers in Singapore Believe That AI-powered Automation Improves Job Fulfillment