As 2017 winds down and a new year comes into view, Amit Zavery, senior VP, Product Development, Oracle Cloud Platform & Middleware, offered three predictions about cloud, AI, and automation for 2018—and beyond.
More than 80% of cloud operations activity will be automated.
Oracle predicts that a higher degree of intelligent automation will permeate the cloud platform, with machine learning and artificial intelligence helping users anticipate outcomes, identify risks in real-time, and take remedial action. Oracle’s conservative estimate is that operations currently experiencing 20,000 human-managed interventions per year will soon fall to just 20 by 2020.
AI will cement its place in the enterprise.
The central tenet of artificial intelligence—to replicate and exceed the way humans perceive and react to the world around us—is set to become the cornerstone of innovation. The proliferation of data across all industries and organizations is fueling the AI revolution, allowing technology providers to enrich their applications with adaptive learning and healing capabilities.
Business processes have always created vast floods of data, but only now can the enterprise use AI and machine learning to understand and contextualize both structured and unstructured data—and extract its true value. For the enterprise, AI is essentially a digital soothsayer; it can effectively predict the future, analyzing patterns and trends to offer more effective microsecond buying recommendations, and augmenting next-step actions with invaluable insights.
The path to effective AI integration requires domain expertise and data availability—as well as data science expertise. By 2020, Oracle expects domain experts and data scientists to embed AI into existing products—expanding and differentiating their capabilities.
More than 50% of all enterprise data will be managed autonomously in the cloud by 2020.
Autonomous operations supported by high service-level agreement guarantees will provide further incentive to migrate database operations to the cloud. Experienced database and infrastructure engineers are working alongside data scientists to build effective models for reliability, anomaly detection, performance, security, and remediation.