Artificial Intelligence (AI) and cloud computing are at the center of most enterprise solutions today. Individually, the two technologies have evolved to support businesses in handling large data volumes, structuring their IT infrastructure, and accelerating processes and operations. The AI cloud is the natural progression of the technologies, wherein AI is deployed within the cloud environment to enhance decision intelligence while reducing costs.
What is an AI Cloud
The combination of Artificial Intelligence (AI) and cloud computing, or the AI cloud, is an emerging concept in enterprise software architecture. It addresses the current demands and challenges of storing and processing high-volume data, building and running algorithms in the cloud, and integrating advanced machine learning services.
Intelligent automation: With the integration of AI and cloud, barriers to enterprise-wide adoption of intelligent automation are removed. AI cloud drives the hyper-automation needs in the face of accelerating digital transformation plans. This allows enterprises to smoothly transition from discrete automation tools to a highly connected automation platform.
Deeper Insights: Organizing, managing, analyzing, and using data at scale is a challenge for enterprises. The convergence of AI and cloud helps enterprises understand vast volumes of data and consume it as actionable insights, such as risk prediction/detection or new business opportunities.
Increased security: Big data brings several security and privacy risks that could negatively impact any business. AI helps enterprises with an intelligent data security layer that can self-analyze, predict, and respond to threats in real-time. Its self-learning model allows the cloud to detect anomalies quicker and efficiently.
Lower costs: Most cloud services provide a pay-as-you-use payment model. For an enterprise considering the upfront costs of AI cloud, it is a tremendous cost saving over traditional infrastructures, such as managing on-site data centers.
What does AI Cloud Change?
The AI cloud is a game-changer in our data-driven world. The ongoing COVID crisis shifted the gears on cloud adoption. Unlike traditional AI analytical models, the AI cloud enables extensive data management at a high capacity without physical servers. With the inclusion of AI, an enterprise can improve resource management with infrastructure optimization, fault management with self-management models, and load balancing with interconnected neural networks. As we move forward, AI cloud could lead to exciting results.
1. Rise in AI-based platform services
The hybrid structure allows enterprises to harness AI capabilities with an AI-as-a-Service (AIaaS) model. Today, most of our cloud services are available off the shelf; outsourced to third-party vendors. The future could see the availability of AIaaS platforms as new operating systems for digital businesses. The AIaaS market is forecasted to grow at 25.8% CAGR by 2030, that’s a USD 43.29 billion markets!
2. Incorporating AI cloud strategy
The last couple of years has seen a rising level of investment in cloud solutions. However, enterprises fail to have a holistic plan for AI integration. The next-generation cloud computing platforms require an enterprise-grade AI platform strategy backed by a multi-technology stack.
3. Application of cognitive intelligence
Powered by AI, future enterprises would evolve into cognitive enterprises. This involves combining data, processes, and workflows under a single framework. The AI cloud can deliver unrealized data value to a data-driven business platform.
Despite the benefits, the AI cloud model is still in its infancy. Enterprises are hesitant to take the plunge owing to technology integration challenges and a lack of skilled professionals. As cloud computing continues to dominate the tech industry, it is time businesses start exploring the capabilities of AI and cloud computing together.
Also Read: More Than Half of Enterprise IT Spending in Key Market Segments Will Shift to the Cloud by 2025