In its simplest form, automation includes any improvement to a process that reduces human labor while resulting in an outcome that’s the same or better than that of the previous process. The goals of automation include improvements not only in productivity but also in quality and consistency.
Most of us are familiar with information systems that automate and streamline decision-making using tools to aggregate, extract and analyze information. All of that has been around for a while. But newer systems — based on cognitive automation — now include natural language processing, machine learning algorithms, real-time computing, big data analytics and evidence-based-learning. This level of automation opens up exciting possibilities.
Cognitive automation — basically, the intersection of artificial intelligence (AI) and cognitive computing — has become one of the fastest-moving technologies because of the rise of the digital and connected workforce. According to one forecast , the global cognitive robotic process automation market will generate revenue of $50 million in 2017 and will expand at a compound annual growth rate of 60.9 percent from 2017 to 2026.
Artificial Intelligence Buzz: C-Suite Interest?
The earliest successes in the field of cognitive automation involved products such as warehouse robots powered by AI, automated restocking systems, self-driving cars and systems that predict electricity demand. However, despite the influx of billions of gigabytes of data and vast investments, deployment of AI is still relatively low — though it appears that, thanks to the current wave of AI buzz, C-level executives are taking an interest in how investments in AI can result in greater success.
In a Harvard Business Review article, researchers from the McKinsey Global Institute reported that only 20 percent of respondents to their survey said they use one or more AI technologies at scale, while 41 percent said they were experimenting or piloting AI. Nonetheless, a McKinsey report sees AI as a new disruptor that will accelerate “shifts in market share, revenue, and profit pools.”
McKinsey identifies early adopters as digitally mature larger businesses that will use AI in core activities through multiple technologies, and that focus on growth over savings. […]