Article | April 30, 2020
As the world looks for a way to manage the spread of the coronavirus while getting back to a more familiar way of living, how can apps provide a solution that is both effective and respects the privacy of all citizens?It seems that no other app has attracted so much attention over the past weeks as the coronavirus app, described as a powerful tool to curb the spread of COVID-19 so we can go back to normal life.
Article | April 30, 2020
In the area of computer intelligence where we have robotics, machine learning, artificial intelligence, etc. There is a new game-changing concept that is so profound that industries are already finding a use for it and it is paying off. This new concept is called Intelligent Automation (IA).
Discussions with heads of global organizations as well as research, and experience of experts show that IA is establishing itself as a future key driver of competitive relevance and enterprise efficiency. This is why IA experts are convinced the concept can provide solutions to several urgent issues in the world right now such as improving our planet, education, and life-saving measures. The impact of IA is becoming more prevalent, and that saw the concept selected by Gartner as the number one tech trend in 2020.
What is IA?
The concept of Intelligent Automation otherwise known as Hyper automation leverages the new-gen software-based automation, which blends technologies and methodologies to implement business processes on automation for knowledge workers. This is achieved through IA imitating the skills used by knowledge workers to execute their work. All these are done to attain a business outcome via purposeful redesigning of automation carried out with little or no human oversight. The end game is cost reduction, which improves process speed, optimization of decision outcomes, improved process resilience, and improved quality and compliance. In the end, businesses and organizations will see an increase in revenues and enhanced employee and customer satisfaction.
Who are the knowledge workers?
Who are the knowledge workers that IA is purposefully designed for? For starters, knowledge workers' main currency is the knowledge they possess. We have examples like pharmacists, designers, programmers, architects, lawyers, physicians, engineers, public accountants, scientists. Any worker that has to “think for a living” is considered a knowledge worker. This type of worker is mainly domiciled in the service industries. A knowledge worker is information-based compared to manual labor that is material-based and mainly domiciled in the manufacturing industries.
Where does IA feature here? We already know the importance of industrial automation to the manufacturing process. We can consider IA the “white collar” version of industrial automation. IA can be used to supplement the job of a knowledge worker such as call center agents, financial controllers, etc.
Let us break down what IA does specifically for a knowledge worker. Imagine IA as a digital worker created to imitate the activities of a knowledge worker to deliver the same outcome as a human would. It mimics all the human business processes, which is a succession of tasks by reproducing the human capabilities of reading, speaking, learning, hearing, seeing, acting, and reacting to produce the same business processes as a knowledge worker.
The synergy between IA and humans
IA creates a synergy by merging the software-based workforce with the human workforce. On the task spectrum, IA shoulders a load of executing tedious, low value, and monotonous tasks like processing and digitizing paper invoices, reconciling data, etc. IA equips a worker with what we can call superhuman abilities like the ability to generate insights from millions of analysed data done in just a few minutes. That is on a human level is virtually impossible to do.
The uniqueness of IA
How is it that a concept so recent that its name was only created in 2017 by IEEE has witnessed a rapid expansion and is expected to have a lasting impact on us? We believe the answer lies in its unique features, which are listed below:
The IA pools together new technologies, most of which are recently developed in the last decade.
The application of several IA functionalities is universal. They are applicable across several business functions like finance, sales, etc., and industries such as retail, banking, among others.
IA programs are scalable. Once developed, scaling can be carried out immediately and infinitely at no added cost.
Its availability is unmatched; IA can deliver 24/7.
IA is economically viable and reliable. It gives the same results based on settings repeatedly at a reasonable cost. In less than a year, the program will normally generate payback on the initial investment.
AI and IA, two sides of the same coin?
Here comes the inevitable question. Is Intelligent Automation (IA) any different from Artificial Intelligence (AI)? Are they not just two sides of the same coin? Well, in the world of computer intelligence, laying down the differences between robotics, AI, IA, among others is a very complicated process.
The line between is so blurry that they can sometimes overlap due to the continuous evolution, emergence, and convergence of these concepts. However, that is not to say there are no areas where there are clear demarcations.
For the purpose of clarity, a few key anchor points are drawn using the analysis of the survey of the opinions of more than 200 IA experts as well as our experience in IA. These are the main anchor points:
AI and IA –Since IA has to do with the automation of knowledge work that is the area where AI and IA interrelate. That means IA comprises all use cases of AI in all industries excluding industries like fundamental research, arts, gaming, or any other that is not information-based.
For robotics –physical robotics utilized in the manufacturing industries are not classified as part of IA. It only covers software-based robots.
Lastly, under workflow, business process management, and cloud; only programs or platforms that exhibit a form of intelligence fall under the class of IA. Programs that have limited capabilities to process end-to-end tasks and offer little insight into business processes are not included.
The unfolding potential of IA
The adoption rate of this phenomenon is already significant to the extent that a recent survey of world business leaders shows that 86% of them believe they must implement IA in the next five years to stay competitive. According to a survey by Gartner, 42% of CEOs have embarked on the digital transformation process already with 56% reporting gains from the application.
Due to the uniqueness of IA, in the next five year, experts believe that it is very likely to reach a sophistication and adoption level that took more than 200 year for industrial automation to achieve. A Deloitte survey already indicated that the adoption rate for IA is more than 50% and the rate is predicted to jump to over 70% in two years. If it continues at this rate, we could see a near-global adoption level achieved in the next five years. Despite being a new concept, IA is progressing very rapidly in terms of capabilities.
Article | April 30, 2020
Intelligent Automation (IA) is one of the trending buzzwords of our times. What makes automation smart? Is it new? Why the renewed focus? Bill Gates believed automation to be a double-edged sword when he said: “Automation applied to an efficient operation will magnify the efficiency. … Automation applied to an inefficient operation will magnify the inefficiency.”
IA lies at the intersection of robotics, artificial intelligence (AI) and business process management (BPM).
But before you think HAL from 2001: A Space Odyssey, J.A.R.V.I.S. from Iron Man or Terminator 2: Judgment Day scenarios, first, a little context. IA is not new; automated manual processes have been in existence since the dawn of the Industrial Revolution. It enabled speeding up go-to-market, reduced errors and improved efficiencies. Over time, automation made its way into software development, quality assurance processes, manufacturing, finance, health care and all aspects of daily life.
“Intelligent” automation backed by robotics, AI and BPM creates smarter business processes and workflows that can incrementally think, learn and adapt as they go — for instance, processing millions of documents and applications in a day, finding errors and suggesting fixes or recommendations.
What Intelligent Automation Does, Humans Can’t
IA enables the automation of knowledge work by mimicking human workers’ capabilities. It includes four main capabilities: vision, execution, language, and thinking and learning. Each of these capabilities combines different technologies that are used as stand-alone or in combination to complement each other.
One oft-quoted IA example is fraud detection and prevention in the BFSI sector. Robotic process automation (RPA) optimizes the speed and accuracy of the fraud identification process. Since RPA can go through months’ worth of data in a matter of hours and throws up exceptions, teams cannot keep up with the speed and scale needed to resolve the issues flagged. However, speed and efficiency are of the essence where fraud management is concerned.
The answer lies in AI and BPM coupled with RPA. IA can streamline the process end-to-end. Pascal Bornet notes in his book, Intelligent Automation, that IA can help improve the overall automation rate to nearly 80%, and it can help improve the time to solve a fraud incident and obtain clients’ refunds by 50%.
While RPA provides excellent benefits and quick solutions, cognitive technologies offer long-term value for businesses, employees and customers.
IA And Digital Transformation
IA adoption is growing swiftly across the enterprise, being fast adopted by more than 50% of the world’s largest companies. Its benefits are relevant to the majority of business processes. For example:
• Industrial systems that sense and adapt based on rules.
• Chatbots that learn from customer interactions to improve engagement.
• Sales and marketing systems that predict buyer journeys and identify leads
The Future Of Work: Bitter Or Better
There is much speculation when it comes to IA and the future of work. The main contention is that robots will take away jobs from humans. My argument is that, while it will cause role changes, it doesn’t necessarily mean job losses.
The Industrial Revolution helped automate “blue-collar” jobs in manufacturing and agriculture. Similarly, IA will automate many white-collar jobs that are tedious and tiring. A recent IBM report shows that 90% of executives in firms where IA is being used believe it creates higher-value work for employees.
So, no, we will not be living in a dystopic world controlled by bots running amok! IA means better roles, the elimination of laborious tasks and improvements in employee well-being.
The Promise Of The Better Life
In 2018 alone, over $5 trillion (6% of global GDP) was lost due to fraud. Medical errors in the U.S. incur an estimated economic value of almost $1 trillion — and 86% of those mistakes are administrative. A 2017 Medliminal Healthcare Solutions study found that 80% of U.S. medical billings contain at least minor errors — creating unnecessary annual health care spending of $68 billion. The World Economic Forum cited an ILO report that “estimates that the annual cost to the global economy from accidents and work-related diseases alone is a staggering $3 trillion.”
Now, let us imagine we can save $5 trillion globally through the deployment of IA. It means:
• Global budgets allocated to education could more than double.
• Global healthcare budgets could be increased by more than 70%.
• Environmental investments could be multiplied almost twentyfold.
Transitioning To Intelligent Automation
However, adopting IA is not like flipping a switch. There are some key steps an organization must experience in its bid to be automating intelligently.
• Planning. For the successful adoption of IA, business leaders must understand the relationship between people and machines. Enterprises must plan so as not to disrupt other parts of the business and integrate IA seamlessly into the existing programs. Instead of adopting IA across the processes, identify where it delivers the most value. Automating broken processes will not fix the problem. IA will only reap rewards on stable and mature processes
• Change management. IA is not easy to implement. There will be a great deal of resistance to adopting IA in your organizations. Designing a change management strategy, an execution road map, an enterprise operating model and key metrics for ROI will help your cause. Invite key stakeholders from the outset to ensure buy-in and train your employees to work in collaboration with IA.
• Governance framework. Establishing a governance framework helps determine who will watch the watchmen. The bigger the role of IA in your organization, the more critical governance becomes. Designing a framework will help you monitor performance as well as define exceptions and errors. It is a recipe for disaster if you don’t have a command and control center to ensure IA is making the right choices. Even more reason for humans with industry expertise to still “have their jobs” and excel at them.
Future Of Intelligent Automation
The future of IA will direct businesses to a more adaptive model that is beneficial for business leaders to uncover higher value and employees to do more satisfactory and creative roles. Preparing for an intelligent future means adapting our technology, skills and education to fit the future of the workforce.
What are we waiting for?
Disclaimer – This article was 1st published on Forbes.comEnable GingerCannot connect to Ginger Check your internet connection
or reload the browserDisable in this text fieldRephraseRephrase current sentenceEdit in Ginger
Article | April 30, 2020
For organizations that are considering or already leveraging Sitecore to host their digital experience, they’ll be excited to learn that Sitecore announced the release of Sitecore ® Experience Platform ™ 10, (XP 10 for short), plus Sitecore Experience Commerce™ 10 (XC 10).