When they think of automation, many people still envision Charlie Chaplin and his classic movie, Modern Times, even though it paints a nostalgic and unrealistic picture. But one thing is for sure: Automation is nothing less than a game changer – for every industry, every context, every system.
“Self-replication is a key aspect of biological life that has been largely overlooked in artificial intelligence systems. Here we describe how to build and train self-replicating neural networks“ – an assertion, written by Oscar Chang and Hod Lipton of the Department of Computer Science at Columbia University in New York, published in a paper briefly titled “Neural Network Quine“. In this, two scientists explain how software not only optimizes itself, but also multiplies. Meaning nothing less than that “survival of the fittest“ has reached the code. Is there any more for artificial intelligence to achieve? And if the idea of a replicating program were to be thought out further, what kinds of automation would then be possible?
A global force affecting all activities
From software to artificial intelligence, from machine learning to deep learning, from machine-to-machine communication to co robots – all of these developments are finding their way into automation in order to increase productivity and efficiency, but not without consequences: “Automation will be a global force, affecting all countries, all sectors, all jobs, and all work activities,” says the McKinsey report “A Future That Works: Automation, Employment, and Productivity”, continuing: “Already today, machines and algorithms are playing a much larger role in the workplace, but how soon will it be before we all feel the impact of automation technologies? Could machines really carry out much or most of the work humans do today – and if so, by when?”
Indeed, automation may appear to be a simple transfer of tasks from man to machine. But its real power lies in its ability to fundamentally change traditional ways of operating, for businesses and individuals, with machines that offer strengths and capabilities – in terms of scale, speed, and the ability to cut through complexity – that are different from but crucially complementary to human skills.
Agility, scalability, responsiveness, and transparency are key
While the pre-digital economy was designed principally for efficiency, in the digital economy, it is agility, scalability, responsiveness, and transparency that are key, notes Aman Katyal, head of the supply chain at Capgemini’s Business Services, in the paper “Reimagining the Supply Chain in the Era of Intelligent Automation.”
A transformation built upon four pillars: a connected ecosystem, intelligent processes, cognitive analytics, and autonomous fulfillment. Plus: a new mindset. “Successful digital transformation comes not from implementing new technologies alone, but from transforming the organization to take advantage of the possibilities new technologies provide,” Katyal continues.
Imagine new paths for growth, making today’s business relevant for tomorrow, re-engineering to achieve more with less to deliver better business outcomes, and orchestrating new, innovative ways of working. Throughout the automation journey, organizations implement and adopt robotic process automation (RPA), automating rule-based processes with software programs that do not require human interaction and applying them to systems like ERPs or databases.
Machines that understand increasing levels of complexity
Systems that will continue to reach and exceed human performance
And beyond RPA comes intelligent automation, “which includes technologies such as machine learning and dynamic workflow,” says professional services firm Genpact. “Intelligent Automation delivers exponential value by learning and adapting as it automates.” As machines become adept at understanding human language, reading the news and blogs, talking to people and understanding what they hear, they will be able to understand increasing levels of complexity and to structure data and contexts in a way that makes it easier for their human co-workers to use them.
“That will make them increasingly useful assistants, allowing humans to improve the quality of their services to their colleagues and clients. As AI-enabled systems take over more of the routine work, humans will likely have more time for more creative endeavors,” the UBS Group Innovation states in its white paper, “Intelligent Automation.”
An insight that even has advanced into high politics: “Although it is unlikely that machines will exhibit broadly applicable intelligence comparable to or exceeding that of humans in the next twenty years, it is to be expected that machines will continue to reach and exceed human performance on more and more tasks”, according to the study “Artificial Intelligence, Automation, and the Economy,” published by the U.S. administration in December 2016.
The well-earned result will be truly intelligent environments that meet people where they are.«
An “internet of thinking” fueled by robotics, immersive reality, and AI
What does this mean in practice? Examples from logistics show how far intelligent automation has already progressed, including the genesis of new businesses and operating models. When the condition of shipments and systems becomes available via image recognition or when software and intelligent automation enables completely autonomous transport and reduces repetitive tasks, the focus of operators can shift to more demanding tasks.
“Intelligent automation will enable enterprises to innovate and evolve by increasing their agility, reducing the complexity of systems and operations, accelerating their time to market, and creating the ability to experiment continuously with new products and services,” explains Paul Daugherty, Chief Technology Officer at Accenture.
He even goes one step further, seeing an “internet of thinking”, fueled by robotics, immersive reality, artificial intelligence, and connected devices, which brings a new level of technological sophistication to the physical world. To succeed on this level, companies must make a significant effort across key areas of business processes and strategy, from service design to infrastructure transformation and hardware considerations. As Daugherty argues in Accenture’s “Technology Vision 2018”: “The well-earned result will be truly intelligent environments that meet people where they are.”