Call it digital transformation, digital disruption, digital operations or digital process automation. No matter what term an organization uses to describe automation technology, the goal the same everywhere: to harness the power of digital to elevate the customer journey and drive end-to-end business outcomes.
It all comes down to how an organization understands and uses its information cornerstone for success in creating a smart digital business. Software robots, often referred to as robotic process automation (RPA) systems, have gained considerable ground on this front, welcomed by C-suite executives who are keen to cut costs, improve productivity and gain a competitive advantage.
Laying the Groundwork for AI
RPA technology is in a relatively early stage, laying the groundwork for not only digital transformation, but also a new generation of intelligent applications that go beyond automating repetitive tasks, such as robots powered by artificial intelligence (AI). Research from Gartner suggests that the state of the market is such that CIOs shouldn’t hesitate to begin experimenting with AI technologies.
The research firm predicts that by 2020, AI will be a top five investment priority for more than 30 percent of CIOs. In the interim, CIOs will be scrambling to make sense of machine learning and other AI technologies, to figure out what roles those systems can play in digital business, and to launch the internal pilots that will test that knowledge and insight. At the same time, CIOs will have to sift through competing vendor claims and promises to identify and assess the genuineness of AI capabilities.
Today, there is confusion when it comes to which use case is best, where to start and what technologies to apply. The question is which technologies work together or complement one another when it comes to AI. It doesn’t help that much of the messaging today tends to be bandwagon cheerleading and hype. Because of this, there are often misconceptions about how these technologies work, and which technologies and approaches are truly best suited for different business processing situations. These messages will become clearer as more real-world use cases prove AI to be effective.
The key is for users to define tangible problems they are trying to solve and not worry so much about the technology terms, such as cognitive computing, natural language processing and machine learning. It’s critical to note that Gartner also suggests that CIOs take the simplest approach that will do the job, rather than jumping headfirst into cutting-edge AI techniques. […]