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I is for intelligence. Two robot trends disrupting the business world

Published on 25 August 16
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As intelligent technologies advance exponentially and disrupt established business models, companies are eager to reap the benefits in order to gain competitive advantage. Robotic Process Automation (RPA) and Cognitive or the infamous Artificial Intelligence (AI) are the powerful enablers currently causing the business world to run a fever.

I is for intelligence. Two robot trends disrupting the business world - Image 1

Software with human like capabilities for manipulating data and processing tasks; digital machines that can understand, communicate and solve problems; these are intelligent robots trained to automate business activities and take on increasingly complex roles in the workplace.

There is however still a great deal of confusion about this new class of digital labor. What do we actually mean when we say these robots are intelligent? Which elements of work do they address? And where is the novelty? Augmenting work with new technology is presumably as old as mankind itself. Understandably it’s all a bit confusing, so let me address some of these questions by focusing on two robot technologies currently singled out as particularly disruptive.

A digital workforce at your service

First there is Robotic Process Automation (RPA) which is software that mimics the actions of business users at interface level and can automate any repetitive, rules-based, transactional work process. RPA is all about the rote work. It copies and pastes data between different sources, processes transactions, triggers responses and communicates with other digital systems. It is fast to implement and easy to scale and unlike human users, RPA robots work 24 hours per day without getting tired and making mistakes. This technology is very hot right now in the business environment all the way up to big enterprises, with benefits for operational efficiency and cost reduction so compelling even Luddites pay it a grudging respect.
The cognitive leap
Next there is Artificial Intelligence. Back in the summer of 1956 a team of ten scientists all sharing a common interest in computers and neural networks were submitting a proposal to the Rockefeller Foundation for the funding of a two month long study to be carried out (...) on the basis of the conjecture that every aspect of learning or any other feature of intelligence can in principle be so precisely described that a machine can be made to simulate it (...) This was the ‘Summer Research Project on Artificial Intelligence’. It took place at Dartmouth College and is said to have marked the dawn of AI research.

Since then AI technology has advanced at more or less steady pace until recent times, when faster processing power and greater availability of data sets, what we call Big Data, have made it gain significant traction. Computer systems now use machine learning algorithms to churn through data and detect patterns of information which are fed back into the system in an iterative process of self learning and self improvement. Unlike RPA which handles structured data to automate repetitive, high-volume work, AI technology enables businesses to make sense of unstructured data (i.e speech and images) and build cognitively enhanced virtual assistants. IBM Watson is a good example of a cognitive platform specifically designed for business development.

Merging tendencies?

While RPA is said to have already passed the hype, at the moment there aren’t as many AI tools fully developed for wide business use. The two trends are not aligned. However, that doesn’t mean they shouldn’t be, some time in the future. It’s not rash to imagine what a convergence of RPA and AI applications with machine learning and data analytics could create: a blend of technology so powerful that the possibilities should surpass projected use.


A safe conclusion for now is that both robotic process automation and cognitive computing platforms are key to the future of business. Professionals are actually talking about a capability curve, where RPA is expected to gradually extend the scope of rules-based, transactional processing and integrate cognitive features, while standalone AI products are projected to gain optimization power by progressively feeding on various business applications.

Look Ma, no hands!
People have an inherent tendency to either exaggerate or undervalue their own realities and with technology that human predisposition certainly flavors their evaluations. John McCarthy, organizer of the ‘56 Dartmouth Summer Project proverbially baptized that first era of enthusiastic AI research as the Look Ma, no hands! Era. He was pointing to the fact that behind many AI initiatives at the time stood the pure ambition to reply to skeptics, who were doubtful as to what intelligent machines might be able to accomplish. Today, RPA robots have been labeled precisely that, the eyes and hands of their human counterparts, while a lot of hope is placed with AI tools to stand for the brain.
Please hold the door
Although still far inferior to human general intelligence, today’s digital machines are expected to do just what the Dartmouth team envisioned, which is to simulate processes of human perception and rationality. And with all the data that businesses can collect with these digital technologies, not only is there an unprecedented level of analytical insight to be unlocked, but as increasingly self-adjusting systems, these machines deliver an impressively high capacity for prediction. And prediction is the currency of today’s - and tomorrow’s technology enabled business.













As intelligent technologies advance exponentially and disrupt established business models, companies are eager to reap the benefits in order to gain competitive advantage. Robotic Process Automation (RPA) and Cognitive or the infamous Artificial Intelligence (AI) are the powerful enablers currently causing the business world to run a fever.

I is for intelligence. Two robot trends disrupting the business world - Image 1

Software with human like capabilities for manipulating data and processing tasks; digital machines that can understand, communicate and solve problems; these are intelligent robots trained to automate business activities and take on increasingly complex roles in the workplace.

There is however still a great deal of confusion about this new class of digital labor. What do we actually mean when we say these robots are intelligent? Which elements of work do they address? And where is the novelty? Augmenting work with new technology is presumably as old as mankind itself. Understandably it’s all a bit confusing, so let me address some of these questions by focusing on two robot technologies currently singled out as particularly disruptive.

A digital workforce at your service

First there is Robotic Process Automation (RPA) which is software that mimics the actions of business users at interface level and can automate any repetitive, rules-based, transactional work process. RPA is all about the rote work. It copies and pastes data between different sources, processes transactions, triggers responses and communicates with other digital systems. It is fast to implement and easy to scale and unlike human users, RPA robots work 24 hours per day without getting tired and making mistakes. This technology is very hot right now in the business environment all the way up to big enterprises, with benefits for operational efficiency and cost reduction so compelling even Luddites pay it a grudging respect.

The cognitive leap

Next there is Artificial Intelligence. Back in the summer of 1956 a team of ten scientists all sharing a common interest in computers and neural networks were submitting a proposal to the Rockefeller Foundation for the funding of a two month long study to be carried out (...) on the basis of the conjecture that every aspect of learning or any other feature of intelligence can in principle be so precisely described that a machine can be made to simulate it (...) This was the ‘Summer Research Project on Artificial Intelligence’. It took place at Dartmouth College and is said to have marked the dawn of AI research.

Since then AI technology has advanced at more or less steady pace until recent times, when faster processing power and greater availability of data sets, what we call Big Data, have made it gain significant traction. Computer systems now use machine learning algorithms to churn through data and detect patterns of information which are fed back into the system in an iterative process of self learning and self improvement. Unlike RPA which handles structured data to automate repetitive, high-volume work, AI technology enables businesses to make sense of unstructured data (i.e speech and images) and build cognitively enhanced virtual assistants. IBM Watson is a good example of a cognitive platform specifically designed for business development.

Merging tendencies?

While RPA is said to have already passed the hype, at the moment there aren’t as many AI tools fully developed for wide business use. The two trends are not aligned. However, that doesn’t mean they shouldn’t be, some time in the future. It’s not rash to imagine what a convergence of RPA and AI applications with machine learning and data analytics could create: a blend of technology so powerful that the possibilities should surpass projected use.

A safe conclusion for now is that both robotic process automation and cognitive computing platforms are key to the future of business. Professionals are actually talking about a capability curve, where RPA is expected to gradually extend the scope of rules-based, transactional processing and integrate cognitive features, while standalone AI products are projected to gain optimization power by progressively feeding on various business applications.

Look Ma, no hands!

People have an inherent tendency to either exaggerate or undervalue their own realities and with technology that human predisposition certainly flavors their evaluations. John McCarthy, organizer of the ‘56 Dartmouth Summer Project proverbially baptized that first era of enthusiastic AI research as the Look Ma, no hands! Era. He was pointing to the fact that behind many AI initiatives at the time stood the pure ambition to reply to skeptics, who were doubtful as to what intelligent machines might be able to accomplish. Today, RPA robots have been labeled precisely that, the eyes and hands of their human counterparts, while a lot of hope is placed with AI tools to stand for the brain.

Please hold the door

Although still far inferior to human general intelligence, today’s digital machines are expected to do just what the Dartmouth team envisioned, which is to simulate processes of human perception and rationality. And with all the data that businesses can collect with these digital technologies, not only is there an unprecedented level of analytical insight to be unlocked, but as increasingly self-adjusting systems, these machines deliver an impressively high capacity for prediction. And prediction is the currency of today’s - and tomorrow’s technology enabled business.

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  1. 05 September 16
    1

    @Francis: In my experience, organizations prefer to take a safe route and not jump into the ocean with a big overnight transformation. A matter of calculated costs and risk, of course. But I think you are right, technology is perennial by enduring ongoing change. @ Aravinthan: I appreciate the kind words!

  2. 26 August 16
    2

    What is occurring faster, RPA plus AI (which dictates your wrap your legacy (historical applications) OR "proper" digitization of the Enterprise. I think there is zero doubt the acceleration of technology to move the business processes into new technologies (especially for Banking and Insurance) that drive digital transformation is much faster. And this too, includes AI but in the depth of the applications, not wrapped around them. Nothing wrong with RPA, it's very tactical but do not believe the days of "these systems are going to be around forever" is still real in most cases. "Forever" is here now!

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