Everybody loves predictions. Forbes published its educated guesses on politics, mergers, and even self-driving cars (thanks to a venture called Robot Taxi). How about Gartner’s 2016 predictions for a digital world? Visions of smart machines, robo-bosses, and digital assistants make it seem like we will be working with Wall-E in 2020. Really?
The best way to predict the future
At Xerox PARC in 1971, Alan Kay said, “The best way to predict the future is to invent it.” Today, organizations are beginning to invest in creating their futures to prepare and transform their businesses with intelligent automation (i.e., software robots, cognitive computing, and smart machines). At Cognizant, we expect that in 2016 software “robots will begin to meaningfully compete for work. Too much of our day remains tied up with repetitive and non-value-added tasks.”
For example, Bonnier and Cognizant are working together to streamline and automate a broad range of accounting services, including purchase to pay, order to cash, and records. The goal is to drive higher levels of cost efficiency throughout the organization.
Taking a nearer-term view, what will the state of intelligent automation look like in 2017?
Introducing systems that do-think-learn
The future of enterprise automation is represented by what we call Cognizant’s “Do-Think-Learn” Intelligent Automation Continuum. Simply put, Do-Think-Learn categorizes automation technologies along three horizons: systems that do, systems that think, and systems that learn.
While today organizations are investing much time and effort into understanding and applying systems that do, such as robotic process automation (RPA), the real excitement is around what’s coming next as systems that think and learn become more prevalent.
In fact, thinking and learning technologies are already delivering tremendous improvements on work processes, outcomes, and the speed and quality of information. For example, virtual agents, able to understand unstructured spoken or written requests thanks to intelligent automation, allow companies to promote people into jobs where they solve problems far more complex than answering less valuable questions about forgotten passwords, account balances, or gate and arrival times.
How enterprises will use intelligent automation in 2017
Automate first. Rather than looking at wholesale system changes, process engineering, or complex studies, companies will realize that intelligent automation can be tried, tested, and either fail or scale in very short cycles. Why not automate first and start capturing the benefits right away, while in parallel taking the time to consider expensive and more complex approaches to create efficiency?
Automate ambitiously. Intelligent automation will span many technological approaches and address all sorts of process challenges, from high volume to low, high complexity to simple, structured data to unstructured, and rules-based to dynamic. Companies will take a multidimensional approach to applying intelligent automation and will apply it ambitiously and in parallel with back-, middle-, and front-office processes.
Automate with purpose. The ability for intelligent automation to drive new types of outcomes will be well understood by mid 2017. That level of awareness and insight will form the new benchmark, and the incremental successes delivered today by systems that do won’t be enough any more.
How the automation landscape will evolve
Embedded intelligence becomes table stakes. Imagine your set-top box without a DVR or your smartphone without a voice-activated personal assistant. Expect the same transition to occur in automation as today’s systems-that-do vendors build or buy their ways to smarter technologies. This change will make implementations faster and easier, extend applicability to more dynamic processes, and improve outcomes by creating fewer exceptions, improving output data, and further compressing cycle times.
Do-think-learn becomes think-learn-adapt. As the technologies that enable intelligence become more pervasive across the ecosystem, the systems-that-do horizon will become narrower and less useful. Systems that think then become the entry tier as learning systems become mainstream. By mid 2017, the new horizon three will be systems that adapt, meaning systems with the self-awareness to not only learn but also decide autonomously how to apply that learning to provide smarter, more effective outcomes.
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