Automation in tandem with Artificial Intelligence (AI) and Machine Learning (ML) are at the forefront of the Fourth Industrial (or rather technological) revolution, which is ushering the most radical economic and social changes since the industrial revolution of the 18th century.
These technological exploits are transforming our world and changing our social spaces as well as workplaces. Artificial intelligence, machine learning or intelligent automation is not limited to industrial or scientific procedures anymore. These are slowly encroaching into our private and public life to perform even menial tasks once helmed by human laborers. The experiences and technologies developed from the likes of IBM’s Watson, DeepMind, and Google’s driverless car are now steadily trickling down to the smallest of elements, which can be witnessed easily around us.
IA initially was limited to manufacturing processes, but slowly started taking over various other functions and processes. It is now an integral part in various enterprise functions as it has the potential to transform entire industries and businesses. Any organization or business endeavor that doesn’t recognize the necessity of introducing IA in relevant aspects of their enterprise functions is surely risking its future.
Since 2017, there has been a significant rise in the number of organizations adopting end-user process automation by using Robotics Process Automation (RPA). Many enterprises have realized the possibility of immense improvement in production quality and quantity through implementation of RPA. Also, after implementing intelligent automation into traditional processes, enterprises save a substantial amount of costs. This is possible due to the elimination of inefficient processes and utilizing the same resources better.
Automation in an enterprise setup mostly starts with the objective of reducing effort and maximizing output, essentially by eliminating the tedious, repetitive, and risky tasks, where humans are not as efficient as machines.
As per a recent study, as much as 45 percent of existing work activities could now be automated using existing technologies. Experts claim that this is only the beginning, as the automation potential will exponentially increase with the advancement in artificial intelligence and its variants. Existing automation technology is already on par with the required human performance and in many cases excess human performance vastly. There are many great examples in front of us that demonstrate this potential, for example, Amazon is already using Kiva robots that plan, navigate, and coordinate among different robot entities to fulfill warehouse orders faster than its previous warehouse system.
There is no denying that automation and its variants are changing majority of existing jobs occupations, which will have significant impact on our understanding of jobs and business processes. For example, mortgage-loan officers will not spend any time in inspecting and processing paperwork but will review exceptional instances that will allow them increase the number of loans processed. This will also provide a more advisory component to the job and as a result overhaul the entire understanding of it. Another significant area where automation might change the world is healthcare. Diagnosis is the backbone of modern health industry and with IA, health issues and symptoms could be effectively identified without any assistance from a medical officer or laboratory. Only a sophisticated robot with access to vast amounts of data could diagnose gamut of health issues and push doctors to handle severe or critical cases, where they would focus on advance medicine or treatment inaccessible to the machines. Intelligent machines will augment human capabilities and enhance quality of work in all aspects of our daily lives. Doctors and medical researchers will be focusing on improving public health; lawyers will be saving effort and time by using text-mining techniques to read through documents and dwell only into relevant materials for critical review.
To answer this, it is important to understand whether the business processes of your enterprise have tasks or jobs that can be automated and then understand what will be the impact of this adoption. Conventionally low-skill, low-wage task are the ones most susceptible to automation. However, recent researches suggest that a vast majority of ‘high-skill’ and highest-paid occupations (for example, financial planners and physicians) can also be automated using current and upcoming technologies. Mundane and laborious tasks such as report analysis, operational decisions, staff assignments, and reviewing statuses can be easily automated to save cost, time, and human effort. And contrary to popular perception, there are many ‘low-skill’ and lower-wage occupations (for example, landscapers and maintenance workers) where minimal activities and tasks could be automated with the available automation technologies.
This is why, you should explore there these two approaches of identifying automation feasibility - problem-driven approach and solution-driven approach. In problem-driven approach, organizations are mostly aware that there are some problems and inefficiencies in their daily processes, which must be addressed for better productivity. If you are using this approach, you may start with identifying the blockers in your organization’s processes and look for tasks where many employees are involved to complete repetitive operations. The following pointers may help in this problem-driven approach:
● Are there blockers that are affecting daily operations?
● Which business processes are causing blockers?
● Which tasks are taking up most of the employees’ time?
● Which tasks are mundane and repetitive, and how much time and human effort do they take?
Then there is the solution-driven approach, where organizations do not have evident blockers in their business processes but are looking for ways to better quality and enhance productivity by using automation. This approach mostly helps the organizations in further optimizing their processes. You may use the following pointers for solution-driven approach:
● Which performance criteria is crucial?
● Which KPIs impact our operations the most?
● Which business processes need faster turnaround time?
● Which of the key employees are performing menial tasks?
You can answer the first part of our question using these two approaches and consider benefitting from intelligent automation. Now that we have the means of identifying processes to automate, let’s look at the impact part of the question.
A resent research by Gallup points out that a vast majority of workers, about 71%, are unengaged from their jobs but they acknowledge the significance of their jobs in their lives. So if your organization is also full of employees who recognize the importance of jobs but are unengaged, that means your workers are underperforming and impacting productivity. Automating such tasks intelligently will address the problem of disengaged employees, and enhance the turnover rate significantly. Less repetitive tasks will free quality time for your employees and workers to add value to a different aspect of their role. It will also improve employee decision making and augment human intelligence as mentioned earlier. Similar to few other preceding examples, we can think of interior designers not being involved in measurements or illustrations, and focusing on developing innovative designs and environmentally sustainable solutions. In case of financial advisors, practitioners can spend more time in processing needs and providing out-of-the-box options.
More time, effort, and emphasis on innovative and out-of-the-box solutions will ensure customers get the best service and experience in every situation. Automation will not only open avenues for sophisticated solutions but also give access to service. It has already been established that better and easy service leads to more business, customer satisfaction and positive word of mouth furthers brand recognition and loyalty in the long term.
Companies that improve on customer experience also reportedly increase in revenue, which makes it all more significant more organizations to consider intelligent automation. But revenue and profit is not all that matters. There are far more profound questions staring at our way as we leap towards a new automated world. With large scale automation and job redefinition, more and more people are at the risk of losing out or their skill and jobs becoming obsolete. Substantial human costs, job losses, economic inequality are the next set of questions that must be addressed by organizations and governments before making individual dispensable. Every step towards automation will need predefined mitigating measures to up-skill, retrain, and discover new roles for all such out of work individuals. It is important to understand that these are same people who are also consumers after their jobs; it’s a cycle that needs to go on for organizations to exist and prosper.
Moreover, as data is the basis of automation and its variants, data privacy and user data protection will take precedence in government policy decisions and public focus, legal and regulatory implications are still an unexplored territory. For example, in case of an incorrect diagnosis by an automated health center or a financial miscalculation by an automated job, who is answerable and who is to blame? Intelligent automation in enterprises and organizations is inevitable and now only a matter of technological advancements. Executives, governments, and the public, everyone is a stakeholder now and every move in this direction is going to affect all of us.
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