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RPA is rule based, follows a coded logic and can do repetitive tasks. Whereas AI is a step beyond RPA; and can mimic human behaviors such as cognition and reasoning and take complex decisions. The chosen best answer is for Ehtesham because of differences shown in lucid tabular format alongwith examples for both. The answer also has just the right detail that was asked for without any extra dimensions. R Rajesh's answer cites additional examples.

Definitions: Intelligence: Per English Dictionary, it is the ability to learn, understand and think in a logical way about things. In general human beings shows that intelligence predominantly and distinctly, when compared with the rest of the species in the Earth. Then What is Artificial Intelligence? A very simplistic definition : If the same intelligence is being shown by a machine, or a computer, then it is Artificial Intelligence (AI). Therefore, AI essentially simulates the human intelligence. What is Robotic Process Automation(RPA)? Simple Definition : As a software robot, it apes or mimics the human actions. RPA is all about the habit of doing automation of your day-to-day business processes by a s/w robot as automatic tasks. Let us compare and Contrast RPA and AI. In my opinion, i feel the points described here , are some of the key differences. 1. RPA needs structured inputs and/or well defined rule-based human processes whereas AI can handle even unstructured inputs/data(like email, audio, video files,...),semi-structured inputs/data (XML,Java Script Object Notation(JSON,....) 2. RPA cannot take decisions on its owns and aligns with what is programmed whereas AI has the potential intelligence to take decisions, depending on the needs. 3. RPA is 'dumb' in that it does what it is supposed/programmed to do, while AI is 'Self-learning' and can adapt itself as per the situation. 4. RPA does not possess cognitive skills (refer #3 for the reason) whereas AI has that Cognitive skills. 5. RPA has some limitations in its design as shown by aforementioned points whereas AI does not possess any specific limitations. 6. RPA 'does' things whereas AI focuses on 'thinking' 7. RPA is relatively less complex when compared with AI since AI has many branches/fields (like Machine Learning, Pattern Recognition, so on...) 8. RPA might be relatively less steeper to learn when compared with AI, primarily because of #7. Benefits of RPA: 1. Good in doing routine/repetitive tasks. 2. Eliminates manual errors(human induced) and unnecessary rework/delays and therefore increases the productivity. 3. Ensures 'Lower Turnaround time'. 4. Cost Efficient 5. Provides Better ROI 6. Helps the Stakeholders in focusing solely on strategical aspects alone (thats the very purpose of RPA . Is it not ? - to alleviate the workers from doing routine tasks). Benefits of AI: 1. Maturity of the AI software can make the decision making easy to stakeholders/mgmt. 2. Helps in providing accurate and precise information to the organisation 3. Identifies patterns/trends based on past data(historical). 4. Provides data on things which otherwise is difficult to get by human beings. Let us see some examples for RPA And AI and portray their Capabilities. RPA examples: 1. Imagine few processes such as cheque handling process and cash transaction process in a bank. You want to ensure that all manual operations/transactions/movement involved in this to be automated by RPA. This will be a good candidate for RPA. 2. Another specific example: Imagine a Money counting machine. In old days, the cashier used to count the money and used to give us the amount that we had specified (say using a withdrawal slip). The same task is done by the money counting machine and given to us. This is a typical RPA stuff. AI Examples: 1. Alexa , SIRI , Ok Google (Google Assistant) are popular AI products from Amazon. Apple, Google respectively. 2. Imagine you have some photos of yours in your mobile. You want to show your kids all the photos that you are in. Now you choose one photo of yours and when you click the details of that photo, it will show the rest of your photos in your mobile. This is nothing but a facial recognition of your photo which is an AI aspect. 3. IBM's Watson is an example of Cognitive Computing of AI. It is used across industries and very useful for health industry. 4. Take the game of chess. Remember 'Deep Blue'. The famous chess computer had a pitched-battle with the then World Champion , Garry Kasparov. The AI machine might say take account of algorithms like depth-first or breadth first as required. Professional players practice a lot with such AI chess systems to gain more insights into the nuances of the game and thereby in the process, fine-tuning their specific needs. 5. Shop sweeping bots 6. Drones can be controlled by AIs , which can collect critical information in war affected zones. Now we have seen benefits , examples, charactersitics of both RPA and AI. Let us see what can happen if both can be put into use together. Before doing that let us do a mimicking of these two aspects , with some imagnition. Since RPA is dumb,i will equate it to 'animals'. Since AI is having the ability to Self-learn, i will equate it to 'Human Beings'(only for this article :-) ). Now imagine Animals vs Human Beings. Can you tell who is powerful ? Think Elephant, Lion, Tiger, Cow, Dog..as animals. Can you handle them 1-1 without any weapons(if you face any of these 1-1, when if any one of them tries to attack you). Just for your support, imagine there is an elephant trap nearby and you are too close to that. You know if you run near that , the Elephant (if it is planning to attack you) can fall into that trap. You have 'thinking' ability has your biggest weapon here.Now imagine you have a physical weapon and you are holding a wood with a fire in it(Tranqulisers are not for you unless you are a forest official!!) to drive away the animals. What do you understand from this ? Both Animals and Human beings have their powers. You therefore , definitely want to harness both their powers. How many times,you would have seen 'Tarzan' movie, where Tarzan and his animals work in tandem and succeed with great and right results efficiently !! Now imagine replacing that 'Animals' and 'Human Beings' with the actual powers - RPA and AI. Don't you want to get this power. Well RPA and AI does this , when combined together. Let us some examples where RPA and AI systems can work in tandem (the answer could be theoretically almost in all spheres - but though depending on an Organisation's needs) 1. AI comes into picture where RPA falls short. Imagine cheque clearing, cash dispensing processes. Any routine tasks which are repetitive in nature, can be done using RPA, doing Optical Character recognition is part of AI. This is just a very basic example of combined usage of RPA and AI. 2. Similarly this can be the case on invoicing systems or any other systems where the need is there. 3. On systems where decision making is needed for the data obtained, post the business automation. Now to the question of achieving the highest automation without the two working in tandem, is that possible? The answer may not be 'yes'. We have seen above, both the imaginary and the practical examples. But there may be some scenarios where RPA alone might be suffice which may not need AI presence. It could be because the amount of investment(in terms of energy, effort) made for having that AI aspect may not be worth considering the information that you get it for that specified entity for which you do RPA and AI. If ROI is not enough for a given activity, the organisation may not think it worth. In that case, the organisation could be comforted with RPA alone. For the record, to bring about a change in the productivity,quick turn around time,some teams/organisations use the approach of implementing RPA first and see the ROI drastically changed. Then they go with AI combined with RPA. But nevertheless i feel, bringing both the aspects to the party will produce the maximum result. Conclusion: RPA and AI are two seperate aspects which however mostly can coexist in today's growing business needs. Both are at different points of the automation phenomenon. RPA has its own characteristics and AI has its own flavour. AI is very deep in its branches . Both RPA and AI have a history . RPA had its initial origin which was called Screen Scrapping and AI has been there for quite some time. Both have evolved. While RPA helps in doing effective automation on repetitive tasks, AI steps in where RPA is lacking - cognitive learning,self-adaptiveness, taking independent decisions (ability to deduce information and act upon) and so on,... Caution has to be put in place, to ensure that right data is captured by AI for processing information, for safety and security reasons. The language of use for RPA and AI can be decided based on the organisational needs or the team comfortness. It can be Java, LISP, C/C++, Python or any other AI or RPA based languages. Most of the organisations see rapid change in their Productivity, turn over time and have a great ROI and excellent customer satisfaction , by using RPA and AI. Imagine the superior performance of the Money counting machine and the way how you get response from Alexa/Google Assistant/Siri. Are we not happy with these things ? How about the Unmanned cars driven on the road ? Welcome to the world of RPA and AI!!

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.

SMED (Single Minute Exchange Of Die) SMED is a systematically proven improvement Lean methodology - improvement in terms of time and cost depending on the way it has been implemented. Ideally there are two generic approaches to achieve the goal with this Human ( Achieved through People and organization ) Technical ( Achieved through Technology)- Automation , RPA, AI ( on the broader perspective) The change in SMED comes as many as changeover steps involved as "external" and try to identify them as wastes in the process and ultimately removing these from the system or process. SMED process improvement methodology started in the Industrial manner with Shigeo Shingo, a Japanese Engineer with the effort of removing huge wasteful steps in the manufacturing industry and thus provide lower manufacturing cost and improved deliverables thus an increase in Customer demand which led to more production. The basic steps involved in a SMED structured approach are: 1) Identification of the Plot Area where a particular work is being carried out What work is done, how it is done, applications, products, equipment used People, culture, Duration, environment Risks involved, variation , Opportunities 2) Identification of the elements in the Plot Area Description of the problem identified Technology required ? Cost in time (Estimated) 3) Separate the External Elements from the Internal Elements Elimination of the External element identified Any inspection, retrieval, cleaning , re-structuring 4) Streamline the remaining Internal Elements Cost measured by Technology or Manpower needed to make necessary changes Benefit in time Establishment of the new process and continuing with the enhancement of the change. Please feel free to suggest your thought processes and ideas. Regards, Somrita