Article | March 12, 2020
Artificial intelligence is the most electrifying and exciting technology in the business landscape. It has the potential to drive value across the business, particularly delivering enhanced customer experience, reducing cost and spurring revenue. From smarter products and services to better business decisions and optimized business processes, the technology can transform almost everything. However, before getting started with this disruptive technology businesses need to define their AI strategy effectively in order to boost revenue and accomplish business goals. They must ask themselves how do they create a utilitarian AI strategy to harness its power? What exactly it brings for them and how it helps them in achieving their goals? So, to start modeling an AI strategy is very distinct from creating a traditional business strategy. An artificial intelligence strategy exists to support the business strategy.
Article | March 12, 2020
Coronavirus, COVID-19, is the talk of the town over weeks now if not months. The pandemic nightmare continues to terrorize on a global scale. It is bizarre to believe that bustling shopping malls, house full PVR halls, the crowd at Starbucks phase into Mexican Drug Ghost-towns. As of March 23, 2020, more than 349,000 people have contracted the novel coronavirus and at least 15,308 have died, according to a tally by Johns Hopkins University. Although the documented cases in terms of total recovery are at 100,165, the number of causalities by Coronavirus is larger than SARS (2002-20040 and Bird Flu of 2013, and is slowly closing to the total deaths in Swine Flu (2009-2010) i.e. 18,036.
Article | March 12, 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 | March 12, 2020
SARS-COV-2 has upended modern health care, leaving health systems struggling to cope. Addressing a fast-moving and uncontrolled disease requires an equally efficient method of discovery, development and administration. Artificial Intelligence (AI) and Machine Learning driven health care solutions provide such an answer. AI-enabled health care is not “the medicine of the future,” nor does it mean robot doctors rolling room to room in hospitals treating patients. Instead of a hospital from some future Jetsons-like fantasy, AI is poised to make impactful and urgent contributions to the current health care ecosystem. Already AI-based systems are helping to alleviate the strain on health care providers overwhelmed by a crushing patient load, accelerate diagnostic and reporting systems, and enable rapid development of new drugs and existing drug combinations that better match a patient’s unique genetic profile and specific symptoms.