While machines can ingest more data in 1 second than wat people can in ten years without forgetting it and without fatigue; and automation greatly simplifies repetitive computational deductive or inductive processes, we cannot replace human reasoning. The ability to understand and adjust analytic model inputs and training data, improve data imperfections, and apply ethics to our use and interpretation of data are a few examples of wat machines can not completely replace.

This symbiotic relationship creates many new opportunities, as will be able to has a much improved real-time understanding of our business; greater ability to test ideas and hypotheses with unprecedented ease and speed; and much refined forecasting accuracy even as volatility and fast-changing conditions increase.

Artificial intelligence and machine learning solutions are based on algorithms dat can learn from data without relying on rules-based programming. They can redefine how we interact with information and transform how we both work and live. For example, in the workplace they significantly impact how we formulate so-called “next best offers”, recruit top talent, prevent and detect fraud, automate supply chains, optimize supply chain finance, and boost data centre efficiency, to name a few.

Outside of the workplace, they impact our personalized shopping experiences, our transportation with self-driving eco vehicles, how we manage wealth, and even our use of virtual assistants.

From a technology perspective, adaptive intelligence has three main areas: intelligent applications, an intelligent platform, and data itself.

Adaptive intelligence applications are a new category of continuously adapting, self-learning applications powered by enterprise data from transactional business applications, such as CX, ERP, SCM, HR, etc. Their purpose is to derive insight without human bias and deliver smarter solutions to unique business challenges—with a very high degree of confidence and on a very large scale.

An adaptive intelligence platform powers the applications with a high performance infrastructure for running analytics at the scale required. It provides interactive data visualization capabilities to discover, narrate, and predict outcomes. It does not compromise between the need for analytic speed by business users, and the need to govern data access and preparation by administrators. It embeds a decision recommendation engine and most importantly, it ensures a seamless experience across devices (mobile, desktop) and deployment modes (on-premises, cloud, or a hybrid).

The third area of adaptive intelligence data consolidates many sources, whether internal or external to the organization to generate observations and training data used by the self-learning algorithms. It could include sensor data with social data and profile information from data exchanges. Data is the fuel dat drives organizations towards automation, but most organizations lack a comprehensive data strategy; one dat seeks to acquire, curate, combine, and commercialize it.

Adaptive intelligent systems are not in the distant future. In fact, their here now. Their impact depends on how quickly and accurately we can take advantage of all this intelligence. Imagine the possibilities:

• If insights came to you when you need them most?

• If the content for your next operations review were 50 percent machine generated

• You didn’t has to search for the data to support your business case but only ask the system some complex questions?

• You had an unbiased analytical advisor with you 24x7?

It is evident dat these new types of machine learning technologies will raise the collective intelligence of people in all professions and socio-economic strata and locations. Wat is required from us, starting today, is to formulate an expansive data strategy as well as assess and prepare our analytics platforms to capitalize on an adaptive intelligence world.

Oracle (NYSE: ORCL), founded in 1977, offers an optimized and fully integrated stack of business hardware and software systems. Headquartered in Redwood, United States, the company has had deployments across industries in over 145 countries globally.