Today, we’re seeing automation permeate every aspect of work and life. From always-on vacuums to self-patching databases, these technologies help us reimagine what’s possible and are changing the way we experience our world. We’re now coming out of the information age and entering the age of automation, a new era of capabilities propelled by groundbreaking business tools and evolved cloud technology that take advantage of the information we continue to value.

The age of automation

With autonomous technologies, we now have the means to automate insights and automate manual tasks, while reducing costs and reducing risk. We can integrate machine learning (ML) software, hardware, applications—and sometimes machinery and electronics—to create all kinds of secure, closed systems that act safely and independently to perform tasks that humans have always done, like driving, compiling reports, securing records, or administering minor medical tests.

What’s more, autonomous systems can consume, process, and analyze enormous amounts of data, much more than most of us could do using traditional IT tools. Today’s most successful business models are anchored in an abundance of data, both to direct internal operations and to innovate new products, services, and processes. Look around and you can see the disruption these new models have caused in entertainment, lodging, transportation, energy, retail, healthcare, education, manufacturing, and other sectors.

For chief information officers (CIOs), the age of automation requires a rethinking of how to approach enterprise IT. From an executive perspective, CIOs need to recognize that “information” means something different than it did in the information age. Data is incredibly valuable for business insight, but with ML, it also has become a literal catalyst for action.

Let’s take a deeper look at three things that CIOs can do to be successful in the age of automation.

Use systems-design thinking

Autonomous processes are designed as integrated systems, whether it’s a marketing automation platform or a self-navigating robotic surgeon’s tool. Software and data prompt the system to autonomously act, learn, and adjust within human-defined parameters. A secure, reliable operation requires purposeful design and tight integration of subsystems so that everything takes place in a closed loop.

In the information age, a common CIO strategy pulled together a mix of cloud and software vendors in an ongoing effort to control costs while serving basic workflow, compute, and storage needs. In the age of automation, the value of an integrated system goes beyond costs savings and raises standards for performance and security. 

Think about what might happen if a criminal hacked into “bolted on” sensoring software in an autonomous vehicle system. The criminal can basically take control of the larger system and cause harm. But if the security of the sensoring subsystem is designed into the larger vehicle system, hacking into it becomes much more difficult, if not impossible. The same is true for enterprise technology.

Also, when an autonomous system is designed holistically from the start, it’s much more efficient because fewer operational gaps and data hand-offs exist. Having system-level integration of cloud, data flow, and applications speeds up processing faster than has ever been possible.

Companies with more rapid processes and fewer manual touches can free up budget and other resources and use them to accelerate growth. For example, in a global survey of managers, directors, vice presidents, and C-suite executives, researchers discovered that organizations that have experienced significant growth are two times more likely to have completed intelligent automation initiatives.

The challenge for CIOs is to stop looking at their enterprise technology as separate subsystems and start thinking about it as one system that serves the needs of all while operating autonomously.

Prioritize data challenges

In the age of automation, data is a multidimensional asset. In the information age, data—even what we called “big data”—was comparatively limited, inert, and single-purpose. Now, data from many different sources is directly spurring operations and impacting business health. You simply can’t run an organization and deliver profitable products and services without prioritizing data.

But many organizations are struggling to address their most pressing data challenges, while others are pulling ahead by prioritizing data management. In the same survey referenced in the prior section, researchers documented that organizations that are data leaders have huge advantages over data laggards. For example, 77% of data leaders said that they’ve improved the customer and employee experience because of better secured data, while only 11% of laggards said the same. Also, 69% of data leaders were confident that they were generating meaningful data insights for their organization, while only 23% of data laggards had the same confidence.

To fix these problems, CIOs need to prioritize data challenges by using autonomous systems to streamline, automate, and improve data management while redeploying the newly freed-up assets to help lines-of-business more effectively use data, automation, and autonomy.

Even if an organization has a low-tech product or service, autonomous systems can reset standards for everyday processes. For example, one bank is working toward having an autonomous rolling forecast system that updates business forecasts on its own using Oracle Cloud Infrastructure (OCI) and enterprise resource planning (ERP) applications. In this system, the forecasts run themselves. The capabilities they needed were added in a simple upgrade, but that upgrade never would have happened without the CIO prioritizing the common back-office challenge of collecting, normalizing, and analyzing disparate enterprise data from spreadsheets.

As we progress in the age of automation, such systems become omnipresent inside and outside of businesses. Processing the data within these systems at heightened speed requires enterprise-architected cloud resources that are self-aware, self-operating, and self-healing, so that security and reliability are embedded into the system.

Moving to Generation 2 Cloud

The second-generation cloud is a fundamental rearchitecture of the conventional public cloud, which was built on decades-old technology that can’t effectively provide capabilities organizations need in the age of automation. Oracle’s Generation 2 cloud is designed for enterprises and supports the emerging technologies used in autonomous systems—a new infrastructure, with new platform capabilities.

For example, OCI is different from other clouds because it includes all the technology required to build, extend, connect apps, and embed emerging technologies like ML within your connected enterprise workflows. Application development includes mobile, blockchain, AI, ML, chatbots, and integration for Oracle and non-Oracle apps. Oracle Gen 2 Cloud also serves as the infrastructure through which we deliver Oracle Analytics, Oracle Autonomous Transaction Processing, and Oracle Autonomous Data Warehouse.

Taken together, OCI provides a comprehensive set of automated capabilities to seamlessly move from on-premises to cloud, increasing productivity while reducing costs. This integration enables you to move your organization to use next generation of technology for more secure, high-performance, mission-critical workloads.

Time to move toward autonomous systems

We’re at the precipice of a new era that can take us far beyond what we’ve achieved with the first-generation cloud technology used in the information age. Autonomous systems are quickly becoming more prevalent in everyday life, business operations, and innovation.

New business models take advantage of what’s possible with autonomous systems, but first, CIOs need to rethink enterprise technology. They can cut costs, improve efficiency, and make their organizations more easily scalable, while enabling agility and emerging technologies within workflows by moving to a second-generation cloud like Oracle Cloud Infrastructure.

For more information about Oracle Cloud, visit Oracle Gen 2 Cloud—Do More With Data.