In this fast-paced, competitive and dynamic world, the need for speed is imperative. Businesses want increased productivity with fewer resources, further cost savings and enhanced accuracy to offer the ultimate customer experience.

As the nature of work has changed, so too have the methods of automation. To meet the customers’ on demand 24*7 services, there has been a surge of interest in Robotics Process Automation (RPA) and Artificial Intelligence (AI), in recent years. Robots are not new. In manufacturing, specifically automotive, factories first opened their doors to industrial robots in 1961. Similarly, these provide the foundation for significant competitive advantage through process automation enabling large volumes of tasks to be achieved quickly and accurately.

RPA offers dramatic improvements in accuracy and cycle time and increased productivity in transaction processing, while it elevates the nature of work by removing people from dull, repetitive tasks.

RPA as a Catalyst to Improve Productivity

In 2011, RPA officially claimed front and centre of the business stage and quickly became a dominant topic for industry observers and participants alike. Across Twitter, blogs and other social media, the RPA story caught fire and an array of automation experts appeared overnight, ready to help companies reap the benefits of this “newly discovered” technology.

RPA is vitally important to understand as it is the starting point for what we see as the evolution of automation - from systems that do, to systems that think, learn and, ultimately adapt. Organizations today are investing much time and effort in the first category, of which RPA is a great example.

While organizations are investing much time and effort into understanding and applying systems that do, the real excitement is around what’s coming next, as systems that think and learn become more prevalent. Whereas RPA systems can work only with structured inputs and hard-coded business rules, the next level of automation – systems that think – are able to execute processes much more dynamically than he first horizon of automation technologies.

RPA as a Catalyst to Build Capability

RPA has fast emerged as a disruptive technology solution capable of delivering multiple benefits. It is already having an impact on organisations currently deploying virtual workforces.

Over the last 20 years, as computing power has continued to swell, the potential now exists to automate many rules-based, repetitive tasks, and to some extent, even teach robots to think like human beings. These capabilities are the genesis of RPA. Emerging as a major driver of innovation around back-office processing, RPA is well positioned as an enabler of innovation.

RPA being the pillar of the convergence of low-cost, easy-to-implement process automation, coupled with machine learning, data analytics and cognitive innovations, is creating a new class of digital labour.

One of the major benefits of RPA is that people can move on to better jobs, better pay and more interesting roles. But India is set to lose 640,000 low-skilled positions to automation by 2021, according to a report by US-based research firm, HorsesforSources (HfS). Low-skilled workers conduct simple entry level, process driven tasks that require little abstract thinking or autonomy According to HfS report, the question we are facing today is – will smart automation, intelligent software bots and brainy robots take away our jobs anytime soon?

What are the Benefits and Challenges of Automation?

According to HfS report, India needs to focus on new avenues for services job creation where it has strength in numbers and strength in potential. India talent is proficient in data and technology and has a very strong competency for process as well as automation capability. And RPA holds rich opportunities to deliver the innovation advantage:

  • Cost Savings: While an outsourcing provider may deploy onshore and offshore resources at different price points, a robot can cost merely 10 to 20 per cent of the cost of an onshore full-time employee in high cost locations like the U.S.
  • Accuracy Improvement: Robot based end-to-end processes reduce the need for human involvement to carry out exception processing, which increases consistency and accuracy.
  • Efficiency Improvement: Robots have a tolerance to work 24/365 and can complete routine mundane tasks that humans often find draining. Robots also address issues like erratic cycle times and throughput. They can even solve the “human” problems such as mood swings, absenteeism, sickness and attrition.
  • Timeline Optimization: The increased speed in implementation is a major winning factor for RPA over traditional transformation tools.
  • Scale Expansion: A robotic workforce is highly flexible and scalable. Once the process is designed, it can be scheduled to run when it is needed on as many robots as required. That is not to say RPA is all benefits and no challenges. Implementation challenges can be serious, but proactive planning upfront can reduce or eliminate them.
  • Security: Organizations typically do not have a defined IT and security policy needed to govern the implementation. Concepts, such as robots approving robots and user identifications for robots, need to be accepted and applied to ensure comfort of stakeholders.
  • Build or buy? While automating, customers have a big decision to make: Build robotics capabilities or purchase them? If looking to purchase, one has to consider the providers’ existing capabilities and any third-party providers they, in-turn, may need to connect with, to provide such services.
  • ROI: Due to lack of understanding of investment to benefits linkages, in the absence of structured methodology of defining the investments and returns, measuring the Impact of RPA remains a challenge as this gets deeply ingrained in provider offerings, relevant methodology for measuring the ROI need to be created and tracked to define automation as a success or failure for the business.

The next likely phase in automation will be driven by intelligent and cognitive automation. Technologies that are able to perform tasks which previously required human perceptual skills are known as cognitive, and are closely related to research on AI. Some examples of cognitive automation would include reading handwriting, identifying images, and translating speech.

The illustration, Figure #1, brings out the difference in the required inputs and obtained outputs as processes move up from being merely automated to being intelligently automated. The shift from RPA to Cognitive Automation is in its nascent stage but shows exciting results and real potential to achieve new thresholds of business value.

How is AI Going to Revolutionize Enterprises Fundamentally?

In order to understand how AI is fundamentally going to revolutionize enterprises, one of the best known examples lies with “Watson,” IBM’s cognitive computing technology. However IBM isn’t the only organization investing money in these disruptive knowledge systems. Both Microsoft and Google have research arms focused on improving machine learning.

One of the major benefits of RPA is that people can move on to better jobs, better pay and more interesting roles.

Google now not only lists basic information, but also provides users a range of suggestions, including when would be the best time to visit a local restaurant.

“AI enables workers to focus on what they do best - imagine, create and innovate to fuel labour and capital augmentation existing labour and capital can be used much more effectively.”

Microsoft’s investment in machine learning, big data and the work of its Machine Translation team has led to enhanced translation features and capabilities across Microsoft’s latest products, including Bing, Windows Phone, Windows, Internet Explorer, Office, and Azure.

AI enables workers to focus on what they do best-imagine, create and innovate. There’s no doubt that AI is now seen in day-to-day interactions with enough examples in the market, such as Siri, Apple’s personal assistant, which provides information in response to voice commands.

It is present in phone systems which listen for human input then route calls accordingly.

It is important for all enterprise leaders to not ignore the fact that computers are able to process significantly more data than humans can, and machine learning will play an ever-increasing role in enterprises monopolizing on the opportunity that the data that they have at hand presents.

AI As a Business Need to Fuel Innovation

AI is poised to transform business in ways we have not seen since the impact of introducing computer technology in the late 20th century. The AI enabled technology can now deliver a higher level of intelligence, looking at unstructured data and applying a degree of higher intelligence, making inferences about what is happening. Further, the AI capabilities can be used to make recommendations or judgments about the next course of action in a process, or respond to a complicated and dynamic environment.

As humans, we have already relinquished many intelligent tasks, such as the ability to write, navigate, memorize facts or do calculations. The notion of AI is not of computers to be like humans, but be better than humans, and solve problems faster and better so as to escalate innovation and improvement in various critical areas such as healthcare, science, technology, learning and commerce.

AI has undergone tremendous change over time and latest trends indicate that it is gradually turning into a cost-effective and easy-to-deploy technology. This is evident as Big Data is growing in volume, variety and at an unprecedented speed. It has the potential to offer substantial insight to businesses. Due to the massive growth of Big Data, AI allows businesses to perform data analysis with one click of a button, which can be acted upon in real time. Today, companies gather insights into how a customer feels about a product, or how an employee feels about a project or HR service using several large and small AI applications on a real-time basis.

The reason organizations invest or are planning to invest so much money on technology is to amplify human intelligence, where machine learning plays a crucial role. Machine learning is a technology that identifies important patterns and adjusts accordingly. It enables systems to speed up and intelligently scale to a degree that simple information systems cannot rival.

Indian market is going through a fundamental shift away from traditional business intelligence and data management towards big data, advanced analytics, and platforms are emerging to support the ‘as-a-service’ economy. When talking about AI and innovation, it is important to keep two perspectives in mind. On the one hand, AI is being used to drive innovation at a macro level, affecting countries and entire industries. But at a more immediate level, AI is being directed to generate business insights that can keep a company competitive and growing faster than competitors.

AI as a Vehicle for Impressive Growth

With the Industrial Adoption of AI, it is now firmly embedded in our day-to-day lives. Maps that compute the optimal driving route for a journey based on current traffic, smart song suggestions from Pandora, friend recommendations, job recommendations, product recommendations based on your purchase history all are powered by AI. Even email spam filters, which learn to differentiate between emails you do and don’t want to receive, rely on some form of AI.

Today, there is a growing list of AI applications by tech giants namely, Apple’s Siri, Google Now and Microsoft Cortana as well as hundreds of smaller companies that are working in this area. These kind of AI applications, will fade out many apps, making them irrelevant, leaving people with fewer and yet ‘more meaningful’ apps. Google’s chatbot AI for example has interesting ideas about morality, philosophy and the meaning of life. Facebook was earlier using AI to understand the context of individual posts so that its algorithms can determine the best way to filter them. Over the next 10 years, the social networking major aims to build AI systems so that users can see or hear things at a more advanced level.

Different industries are looking to use AI in their day-to-day tasks. For example, Aviation relies on airport gate selection and simulation strategies. Financial organizations use it to maintain operations, investments and properties. Toy makers have released electronic pets and robots with simple AI capabilities.

AI is poised to deliver impressive economic growth. But from an individual company’s point of view, the benefits are more immediate: increased productivity, higher profitability, reduced errors, better customer service and more.

How AI Adoption will improve the Workplace, and Not Threaten it?

The driverless cars have replaced drivers with GPS; calculators have made math a machine game more than a mind game. AI comprises systems that are built to interact intelligently with humans with their ability to learn and make contextual interactions. These abilities are far more superior to normal search because they don’t just show options, but they understand, learn and then consider data to come out with creative options that suit the situation and needs of people. The benefits of AI are in three large areas: Engagement, Discovery and Decision Making. The advanced computing systems are not only altering the way humans and machines interact, but are expanding the ability of humans by providing them expert assistance and better understanding of situations in real-time. This way, they prove that the two – humans and machines – are more effective than either one alone.

As AI systems become ever more sophisticated, another wave of job displacement will almost certainly occur. It can be a distressing picture, but here’s what we’ve been overlooking – That there will be the emergence of entire categories of new, uniquely human jobs. These roles are not replacing old ones. They are novel, requiring skills and training that have no precedents.

The Road Ahead

RPA has the potential to add substantial value and improve customer outcomes — and the concept of virtual workers operating as part of a blended human and machine workforce is set to continue in 2018 and beyond.

Nevertheless, emergence of AI is necessitating a “new thinking” that is constructive and competitive. I anticipate a time when the philosophical discussion of what is AI, or otherwise, will end because there will be no such thing as intelligence, but just processes. The winners will be neither machines alone, nor humans alone, but the two working together effectively.

 

ABOUT THE AUTHOR

Vartul Mittal

Vartul Mittal is an Independent Director – Technology & Innovation and a Global Business Transformation & Automation leader. He has 11+ years of strong Global Business Transformation experience in Management Consulting & GICs with a remit to drive understanding, and deliver Business & Operations Strategy solutions globally.

A Mechanical Engineer & MBA by education, a Digital Business Transformation & Automation Consultant by profession, he is essentially a Technology Evangelist by passion. He is a notable keynote speaker on Robotics Process Automation (RPA), Artificial Intelligence (AI) and Innovation at Universities & International Conferences.