Ehtesham Alam Sheikh

Artificial Intelligence is a technology so powerful that it competes with human capabilities and intellect. It is an intelligent machine that mimics human mental capabilities like cognition, reasoning, problem-solving etc. to learn, think and take decisions to maximize success of the defined action.
Let’s understand this better with an example
A good example of Artificial Intelligence is commercial promotions and friends suggestion on Facebook, where through analytics of profile data usage and recent browsing history , AI cleverly and selectively promotes products and suggests friends. Other good example is use of Artificial intelligence is in the health industry to diagnose critical illness with utmost accuracy. Recent research shows that results acquired post-clinical test in medical field with the help of AI is accurate and error proof as compared to human driven tests.
Machine learning (ML) and Natural learning processing (NLP) are enablers of self-development capabilities in AI.
 
Robotic Process Automation or (RPA) is a rule based software/robot that mimics repetitive human tasks which are repetitive and time consuming exactly the same way, based on “if-then” commands. This automation does away with human dependency, with no changes in existing system integration. It works on sequence of commands, for software/robots under some defined set of business rules.
Let’s understand this better with an example
A good example of RPA is Customer Experience Management (CEM) tool used in by many Telecom companies, which has reduced the human intervention for network complaint handling and trouble shooting. Logics are built to capture network experience for each customer connected to network sites and accordingly the code based system autosuggests solutions. CEM has enabled frontend to effectively attend to customer queries/complaints and provide on time resolutions. Another example is IBM Watson which auto troubleshoots for any queries/complaints based on input received from frontend .It has completely removed the manual task of navigation between different applications to derive any solution/conclusion at customer touchpoints.
 
Let’s note some key differences between AI and RPA
 
Differences
AI
RPA
1.       Self-learning Vs Command Oriented
§  AI is ‘self-learning’
§  AI is capable enough to self-learn and evolve through experience
§  RPA are ‘Command oriented’
§  RPA works on set of instructions to automate a rule-based task
2.       Self Sufficient Vs Support System
§  AI is capable enough to perform human task with perfection and completely remove human intervention.
 
§  RPA is a software/robot used to reduces human task and help us concentrate on more creative work
3.       Decision Making Vs Execution
§  Works on concept of systems that “Think”, “Learn” & “improvise task
§  Technology used in case of ambiguity or decision making requirement,
§  Used usually when process/task scenario are unstructured (converting voice message to text)
§  Deals with large amounts of data, as it can analyze & manage that unevenness.
§  Works on concept of “Do”.
§ Software/robots will do exactly what it is designed for, in same way every time.
§  Work on rule-based processes where compliance and accuracy are critical
 
4.       Agile Vs Monotonous
§  AI algorithm can adapt to a new environment, learn from the outcomes of decisions and improve itself over time.
§  RPA works constantly on the same logic for ages unless commends are changed.
5.      Simplicity
§  AI is bit complicated.
§  Needs changes in existing system integration.
§  RPA is the relatively simpler technologies.
§  Works with existing system integration.
6.      Technical Barrier
§  AI requires programming skill sets
§  RPA has low technical barrier, as programming skills are not necessarily required
7.      Analytical capability
§  AI can process large data sets and analyze to make decision making easier
§  RPA lacks this ability
 
Conclusion
RPA and AI are two separate technologies, but complement each other very well. By combining the potential of AI and RPA a completely autonomous process can be achieved. RPA along with  AI and machine learning capabilities can handle high-volume, repeatable tasks with effective solution and deliver precise outcomes. Synergy of RPA and AI can help in natural transition from automation to intelligence. As AI adds value to RPA, in order to achieve the highest level of automation, these two technologies needs to work hand to hand.