RPA vs IPA

[Vishwadeep Khatri]

Q 508.  What is the difference between Robotic Process Automation (RPA) and Intelligent Process Automation (IPA)? Elaborate with suitable examples.

 

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[Hirak Raval]

1. Robotic Process Automation: RPA is used to perform repetitive human task, It is rule based actions to perform a task like automatic reply to an email. Software based bots which are capable of automating human actions or behavior are considered as RPA.RPA makes routine task quicker, more reliable, efficient and reducing human efforts to lowest possible extent. Workflow automations, Screen scrapping, Data capturing at particular conditions are some of the applications where industry is using RPA . 

 

2. Intelligent Process automation: IPA = RPA+ Artificial intelligence + Machine Learning. IPA are required to perform more complex and end to end process solutions with decision making capabilities. IPA enables business to automate process by removing repetitive, monotonous & routine task from the process and make process more efficient. It uses fundamentals of process redesign mostly. 

 

One of the best example of RPA and RPA to IPA conversion used in the industry is managing data base of employee attendance and managing pay roll from that available data. Managing employee attendance was very large scale data handling process and required minimum error as it is linked to employee compensation . We have many RPA based applications where large organizations using these attendance data and leave balance data to generate consolidated report .

 

Further to this, now a days some industry is using employee attendance data to digital workforce allotment on shop floor. Once employee punches his attendance at Factory gate , based on his skill level and subject matter expertise ,he gets area/machine allocation automatically. Here RPA of employee attendance further linked with employee skill map matrix and allowed system to take decision on machine/area allocation to employee on Realtime basis as per production planning and requirement in area. This has improved productivity and removed extra processing of workforce allotment manually to each employee. 

 

There are many other examples of hyper automation through IPA like Managing freight cost through optimum route selections, Procure to pay cycle automation with cost comparison, Customer relationship management, Real time Quality management, Financial transactional RPA with fraud detection analytics etc. 

 

Regards,

Hirak

[Ashish Kumar Sharma]

Background

In the ever-changing evolving dynamic world, need for skilled base man power is growing and is influencing innovation around reducing rather eliminating all historic time and effort activities, been carried out by human. Just for remembrance from late 90’s, the biggest challenge of BPO sector was to avoid human negligence in copy pasting details from PDF to Excel form and data that use to run in million lines. Often, we will hear now Generation Z expressing their dissatisfaction around repetitive and monotones job profiles. Generation Alpha getting ready to search for job profiles would get surprised to see how accounts were prepared in 90’s. The art of developing human like machines who can do exactly the same activity faster, accurately, all the time and with determined ownership towards end result.

Robotic Process Automation is a software technology, easy to build, deploy and manage work eliminating defined repetitive human actions. Using a software do human task allows later to concentrate on complex decision making or processing stuff which as on date is yet not covered by a automation software and at the same time is faster, cheaper, maintain standard flow and is extremely manageable. Example, a software can screen 100+ profiles to categorize most relevant to Finance Profile and recruitment team will save 10 days of TAT and appropriate screening man hours. Robot can reach out to all eligible relevant profiles and schedule a meeting, providing all the essentials in attachment or voice message. Now the precious time of recruitment team is to interact and decide basis one on one interaction and only because the human aspect on emotions recommends this discussion should ideally not be automated. The choice of deploying, to what extent and where allows organization to be more flexible, relevant, profitable and be available. In fact, it’s best suitable for automating workflows that involve old legacy systems that lack APIs, database access and virtual desktop infrastructures (VDIs).

Intelligent Process Automation also serves the same purpose as RPA but its advanced model and technology that combines artificial intelligence, cognitive automation and machine learning. IPA will take RPA capability to the next level on deployment, is cheaper and covers a larger landscape. IPA is a cheaper, smarter and efficient technique that serves a lot more around productivity and comfort on usage. Instead of just mimicking like human being, IBA will allow thinking, learning and adapting to the situation and data work flow. Signing into desktop, recognizing natural language and interpretating, filling up a form with basic information are all example of IPA.

Now do we see any similarities in RPA and IPA, of course. IPA in a way is advanced, upgraded and next level to RPA. It handles more complex processes, critical data formation and most importantly takes decisions. RPA is a simple and continuous repeat of what has been mentioned while IPA can take smarter decision in order to reach to an expected outcome. RPA can help and very well be the initial road and allow organization to get matured with automation initiatives involving IPA.

Similarity statement between RPA and IPA also voice out logical difference. Some of them are narrated below for a quick reference.

S. No	RPA	IPA
1.	RPA uses structured input and logics but is not impactful with variables.	IPA uses unstructured input and develop its own logic, adapts with Variables
2.	Is a software-based Robot, rule based that needs a rule feed on what do with Exceptions	Combination of RPA with AI Technology. Smart enough to interpretate and handle exceptions.
3.	Automate repeatable human action and behaviour. “Mimicking like Humans”	Handle more complex processes and have the ability to learn and decide. “Act like Humans”
4.	Evolved from Screen Scrapping, Workflow and Artificial Intelligence	Build in with RPA along with Natural Learning Processing, Machine Learning, Data Extraction and AI
5.	Best suitable for High Volume Processing. Saving Time and efforts	Best suitable where decision making is needed to move between steps. It will be everything which is RPA but smarter and flexible
6.	RPA has its restrictions; analyst still need to spend time in retraining Bot	IPA automates more and automates more efficiently, adapts, learns on its own.
7.	Productivity is limited to the scope of work is with activity rather processes	Cost of Adaption is cheaper and generates more productivity
8.	Easy to use and don’t require deep technology skills and ranges from basic to mature	Significantly complex and hence skill requirement ranges from matured to advanced.
9.	Generally Human Dependency is reduced and not absolutely avoided.	IPA can elevate the process to run without manual intervention needed

 

Where is IPA heading towards…. It has been said about “Chess” it is a mind game and works to sharpen the human mind. World Champions across world are considered to brilliant mind. But with technological advancement, Automated game is very much capable of defeating human mind for its adaptability to think, react and act just like human being except for the fact it will not forget to make a loop of what best it learnt in giving situation.  

 

An example from mail management, with a simple RPA we can deploy a Bot to send one pre-formatted mail across individually to multiple mail id. With IPA, Bot has the capability to read the body of the mail and interpretate the severity, category and assign the mail to a specific individual.

Another example from a Call Centre, RPA can assign calls to the specified calling agents and note the Call Handling Time. Using IPA, the BOT can measure and comment on the Agents Call Quality. It can interpretate the sentiments and reaction of the customer and guide logical solutions.  

 

[Anjali Nair]

Robotic process automation (RPA) is a software technology which makes it easy to build, deploy, and manage software robots which would in turn emulate human’s actions interactions with digital systems and software. 

 

Benefits

Robotic process automation streamlines different workflows, which in turn makes organizations more profitable, flexible, and responsive and also increases employee satisfaction, engagement in the activities and more productive by removing non value added tasks from their day to day activities

 

Types of RPA

The 3 major types of robotic process automation

 

Flow of Building a Bot

 

Key characteristics of RPA include:

·        Computer-coded software.

·        Programs imitating human interaction with applications.

·        Cross-functional application.

·        Virtual workforce controlled by business operations.

·        Agile and non-invasive, works with existing IT architecture and governance.

 

Advantages of RPA

 

 

Disadvantage of RPA

 

 

Intelligent process automation (IPA) also referred as hyper-automation or intelligent automation or digital process automation is that the process of combining robotic process automation (RPA) with process mining, OCR/ICR, analytics and AI (AI) which helps in creating business process automation that would thinks, learns, and adapts within the autonomous fashion.

Benefits of intelligent process automation

IPA facilitates the end-to-end processes which enable modern, resilient, flexible business operating models. Combination of IPA with the human experience which may unlock the kind of innovation that inspires teams to create new business value.

A successful IPA initiative will demand teamwork between business functions and IT which might evaluate existing processes, then incorporate systems that drive scalable and sustainable become the process framework. It’s critical that employees should be an element of such an initiative, so as to experience the first-hand the benefits of this transformation that happens

IPA combines RPA software with intelligence technologies which is as follows:

Process mining— is an analytical approach which might diagnoses business processes, then uses data analysis to capture and improve processes.

Natural language processing—Also called NLP, which refers to software that empowers hardware to know, interpret and manipulate language, whether spoken or written.

Computer vision—Refers to technology tools, like OCR (optical character recognition),which would scan documents and transform them into text.

Machine learning—Uses AI software algorithms to spot patterns in structured, historical data and uses these patterns which makes precise predictions on outcomes.

Artificial intelligence—Technology that seeks to mimic, and exceeds, human intelligence by analysing data which is quicker than people can and learning from past decisions.

 

 

Advantages of Intelligent Automation

• Efficient use of kit and manpower
• Increased effectiveness
• Lower costs and high ROI
• Seamless customer experience
• Enhanced cybersecurity
• Focus on critical issues instead of on mundane work

Disadvantages of Intelligent Automation

• Establishing a strong governance
• Creating a correct IT environment and technological ecosystem
• Developing the implementation strategy and selecting the right tools
• Restructuring the prevailing system and retraining employees
• Teaching necessary metrics and assigning tasks
• Managing risks

 

Difference between RPA and Intelligent Automation.

 

[Ambikesh]

RPA ( Robotic Process  Automation )

RPA Robotic Process Automation is used to perform the atomized process by eliminating human interference. RPA  is as software that mimics human behaviour, with little or no human assistance. RPA was developed based on the rule and logical repetitive standardized process. RPA is the technology that automates high volume, clerical repetitive, monotonous tasks and performs at higher speed. It works to compile data, data segregation, data reorganizing, and perform tasks.

                 RPA is mostly used when simple and easy to automate, High volume, low accuracy, short turnaround time, speed sensitive, required round clock staffing, has lots of steps etc.

RPA – Examples from Real World

·       Call Centre Operation ( check account balance, transition history)

·       Banking forget password

·       Insurance sector claim

·       Help desk ( Auto repair commands )

·       Pulling the data from multiples sites to find the best deal

·       Sending message

Example customer service

Problem statement:- The customer representative must understand and solve the customer queries carry out the necessary actions by switching between the various software and applications and inform the customer this must wait while the representative is busy dealing with data sometime asking for information that has already been requested this tends to decrease customer satisfaction extends call duration.

The solution requires identifying frequently asked customer questions assessing customer representative actions in response to those questions and developing RPA solutions to facilitate those questions. When several sets of information need to be coordinated across systems the customer service representative can launch a bot the bot completes all actions in seconds with the press of a button for frequently asked questions a dashboard can be created.

   IPA (Intelligent Process Automation)

IPA is the high level or can say next level of RPA, in this Machine learning and Artificial Intelligence that enable Businesses to automate processes by removing monotonous, repetitive, and scheduled tasks from the equation. IPA is a higher version of RPA that combines fundamental process redesign with RPA and machine learning. by joining RPA and AI technology. Intelligent RPA is more reliable and performs routing tasks more quickly, efficiently and error-free.

 A most important quality of IPA is making decisions and delivering results at most efficiently.

 

 

RPA  are automated rule-based task repetitive tasks but if embed that rpa with AI that is artificial and machine learning and some other technologies for analysis then we result in to intelligent process automation so this  enables us to automate not only  rule-based task but also automate the cognitive process where the judgments everything apart from the rule is required.

Why IPA need ? 

There are some limitations to rpa that’s  why the industries are shifts towards intelligent process automation if we have Processes where we need to have a human judgement or we need to make decisions that are not rule-based then we need to have the IPA. Whenever we have complex processes which are not rule-based, as explained whichever needs a decision to be taken on during run time then we need AI models to be embedded with the RPA. Resulting the Intelligent process automation.

Examples :-

Health Care Domain

Imagine a bot that can detect diseases on the provided data and the detail of patients in some legacy application. So we can use intelligent process automation in health care.

Customer service

Many companies provide the best services to the customer and try to resolve the issue of the customer so imagine a bot embedded with natural language processing that classifies those emails and auto-resolve the complaints  

RPA	IPA
RPA stands for Robotic Process Automation	IPA stand for Intelligent Process Automation
RPA is the software base robot (or bot) that is capable of automating human action or behavior in the workplace	IPA is the combination of RPA and AI technology to handle more complex processes rather than automating the routing process
Automate high-volume processes for which people were formerly responsible	RPA brings a measure of decision-making to the process to meet the challenging demand
RPA involved three primary technology  technologies: Screening Scrapping ,  work flow automation and Artificial intelligence	IPA Brings Innovative new technologies to RPA, Such as Natural Language Process NLP, Machine Learning , Data Extraction AI

 

 

 

 

 

 

 

[m.v.elango79]

RPA	IPA
Robotic Process Automation is computer program which perform repeated task in the process	Intelligent Process Automation is software combination of AI + Machine Learning + RPA ·       AI-Artificial intelligence which Mimic human behaviour, which enables machine to think ·       Machine Learning which subset of AI, based on static tool to explore and understand about the data and provide suggest to change.  Which can fall any of below 3 categories o   Supervised – Need Past data o   Un-Supervised – Work based on clustering/grouping based on methodology o   Reinforced – Semi Supervised where limited past data is analysed and based more data rule get updated.
Its program/ workflow based on rule and logic which can be repeated based on set Logic but cannot incorporated any rule change without intervention in program or workflow	Its program which can perform more complex process and also which can understand change based on previous data and change the rule of the process and incorporate the changes to process on regular basis
RPA need structure data to execute the rule	IPA since use AI this can handle unstructured data and convert that to structure data
RPA has limitation on handling multiple data format and complex rule	IPA can handle the multiple data and complex rule
RPA does require extensive collaboration between IT & Business team	IPA need extensive collaboration to make better understanding of Data to make decision
RPA is ease to use and doesn’t need deep technology skill, hence its more attractive and more process getting automated through RPA	IPA is not easy and need some good understanding of technology, due to complexity IPA are not only looked based on feasibility of data
Eg. Banking Break allocation tool: Which need data to taken from multiple source and formatted as per system format in spreadsheet and capture to system. Since the source file is going to same format and rule to enrichment are same this can be Automated to RPA function.  But once data is capture allocation of break to different department need to done by User	Eg.  In case of IPA, Based on Machine learning based on previous data system can create rule to allocate the break to department. Also when there is change in Break allocation force change based on algorithm it read number time change happen take decision to change.
Having mentioned IPA is more better automation option, but in term of breaking complex process in multiple task and doing RPA is much preferred. Due to ease to work and less resource and complexity and creating the rule	IPA intelligence are depended on AI & Machine learning. Even some cased Deeper learning program. Which need more data to understand the behaviour of data and take the decision. Also, some cases in complex process there been issue with ML &AI based decision making when to change. Eg on above break allocation, when there is market scenario allocation pattern has changed, but will back to old allocation when scenario is over. But ML can’t change until it see substantial data to prove the theory to change.

[Rakesh Chandra]

Difference between RPA and IPA with examples

Robotic Process Automation (RPA)

·         Robotic process automation uses technology to emulate human tasks to complete a business process. Types of human actions that Robotic process automation (RPA) bots mimic are repetitive computer-based tasks that are rule-based and have defined inputs and outputs are repeatable and also occur frequently.

·         Robotic process automation utilizes structured data to complete the tasks e.g. data entry, data processing & mapping,  client onboarding and new accounts opening.

·         Robotic process automation (RPA) is often confused with artificial intelligence (AI) while some argues that RPA qualifies as a form of AI technology and RPA is often combined with AI, the two technologies are distinct. Unlike the AI, RPA bots generally do not have the ability to learn. With RPA, if something changes there in an automated task, the bot will not be able to adjust and figure it out on its own. RPA is basically designed to mimic the human actions while AI is intended to simulate the ways that humans think. 

Intelligent Process Automation (IPA)

·         IPA  is based on Artificial intelligence technologies

·         IPA can mimic human actions as well as can learn to do them better over time.

·         IPA builds upon and encompasses RPA with AI.

·         IPA consists of four core technologies:

1.       Machine learning (ML)

2.       Natural language processing (NLP)

3.       Intelligent workflows

4.       RPA

Machine Learning- It is an application of artificial intelligence. ML gives systems the ability to access data and learn from it without being programmed. Machine learning (ML) uses algorithms that are either supervised or unsupervised to identify patterns in structured data, supervised algorithms create inputs and outputs prior to making predictions of their own while unsupervised algorithms observe structured data and develop insights from pattern recognition.

When combined with RPA, bots can evaluate their efficiency and make adjustments to improve the processes. Through deep learning (DL), systems can utilize data gathering in one context to improve upon others. 

Natural language processing- It (NLP) is a software tool that analyses human language to give machines the ability to read, understand, and derive meaning. This technology works through a combination of techniques like statistical and machine learning (ML) to algorithms.

NLP is commonly used to create chatbots. Chatbots use RPA to communicate with human users and to complete the tasks. Among other things, Natural language processing (NLP) helps chatbots to determine the meaning of interactions and to provide users with relevant responses.

Intelligent workflows- Introducing of bots into workflows may lead to confusion and inefficiencies. Human stakeholders need to understand their own roles and responsibilities. For the instance, when does a robot handoff a task to a human etc., Process management software helps stakeholders to understand and track processes to avoid bottlenecks etc.

IPA plays an important role in improving employee satisfaction and customer experiences both. For employees, they better understand their roles and appreciate the opportunity to work on tasks that are less repetitive and offer more values to their organizations. Value is passed onto customers since more resources can be devoted to providing excellent customer services.

Customers are also benefitted from user-friendly IPA technology. For example- new customer onboarding has traditionally been a drawn-out process, especially in industries like banking where organizations must collect large amounts of information and documentation etc. With IPA, however, organizations can easily capture and extract the data from onboarding documents, reducing waiting times and significantly improving customer experiences. 

Robotic Process automation- RPA (Robotic process automation) uses the technology to emulate human tasks to complete a business process. The types of human actions that RPA bots mimic are repetitive computer-based tasks that are rule-based also, have defined inputs and outputs, are repeatable and also occur frequently. Robotic process automation (RPA) utilizes structured data to complete the tasks. Examples of the tasks where RPA technology works well are data entry, data processing & mapping, client onboarding and new account openings etc. RPA is often confused with artificial intelligence while some argues that RPA qualifies as a form of Artificial intelligence (AI) technology and RPA is often combined with AI, the two technologies are distinct. Unlike AI, RPA bots generally do not have the ability to learn. With RPA, if something changes in an automated task, the bot will not be able to adjust and figure it out on its own. RPA is designed to mimic human actions while Artificial Intelligence is intended to simulate the ways that humans think.

 

 

[PriyankaBose]

Robotic process automation

Robotic process automation (RPA) is a form of business process automation technology that uses software robots to automate and mimic tasks that are typically performed by humans. RPA can be used to automate repetitive, rule-based processes, such as invoicing, data entry, creating reports, and/ or claims processing.

 

Intelligent process automation

Intelligent process automation (IPA) takes things a step further by utilizing the application of AI (artificial intelligence), ML (machine learning), NLP (natural language processing), Computer Vision, Cognitive automation, and related technologies, to automate processes with complexities and variations. Needless to say, this convergence of technologies produces automation capabilities that have a significant impact on business value and competitive advantages for customers.

 

IPA = RPA + DPA + AI

The three primary technologies that are used in IPA are Digital Process Automation (DPA), Robotic Process Automation (RPA), and Artificial Intelligence (AI).

 

IPA robots are constantly learning and growing smarter after every task they complete. This gives them an ever-growing list of potential tasks and processes to automate, making them more intelligent with every new task. This added intelligence can create transformation across the full spectrum of emerging technologies.

 

Used Case Example: Invoice Automation

RPA robots can help organizations by taking on various roles and repetitive tasks virtually, including those that are typically carried out by human employees.

While RPA can automate data input, reconciliation error correction, and some decision-making for invoice processing. However, the challenge arises when trying to deal with the many different formats that vendors use for their invoices.

This is where IPA can contribute - by using NLP and other machine learning techniques to understand and extract the necessary data from invoices, normalize it to a structured format, and then send it back to the RPA platform for automated data input, error handling, and so on. By combining Robotic Process Automation (RPA) and Artificial Intelligence (AI), bots will be able to scan, digitize, and validate essential data from purchase orders to generate invoices.

 

RPA Vs. IPA

RPA is excellent at automating simple and straightforward tasks, and therefore RPA is most widely used for automating repetitive tasks that are carried out the same way each time, with minimal variation.

RPA is rules-based and applies instructions set by humans to perform a particular task - for example, sending an automatic reply to an email; while it lacks any form or sense of intelligence, adaptability, and/or cognitive functioning; and operates in a linear arrangement aka. the human operator needs to have designated inputs and outputs which doesn't allow for much flexibility or scope for variability.

 

In contrast, IPA is used for more complex end-to-end processes.

IPA is a more efficient and intelligent option when it comes down to choosing between the two. This is because IPA automates more processes than RPA. Not to mention, IPA can structure data, handle exceptions, and variations and learn over time - meaning the automation is of much higher quality, can handle higher complexities in the process, and hence saves more money in the long run.

 

However, it must be kept in mind that IPA comes with its own set of challenges, due to the sheer nature of technology augmentation and deployment/ integration along with other organisation-wide legacy softwares.

 

[Rahul.Arora2]

Let us understand the difference between RPA & IPA based on certain criteria along with relevant examples :-

 

Execution Approach :

 

Robotic Process Automation (RPA), refers to a set of automated tools that help businesses to automate processes by mimicking human actions on computers, with little or no assistance. RPA tools are designed specifically for automating mundane, repetitive tasks that follows defined business rules & requires mimimal decision making. Eg : Bank reconciliation where the transactions recorded in general ledger are matched with bank statements. In this case the RPA bot logs into bank portal as well as the oracle in order to fetch the general ledger as well as bank statements, performs reconciliation of each transaction based on a business rule. 

 

Intelligent Process Automation (IPA), on the other hand augments the traditional rule-based automation with decision-making capabilities in order to deliver results with utmost efficiency. It is combination of RPA & AI technologies, which handle more complex processes rather than just routine rule-based tasks. Eg : In an accounts payable process where we are getting scanned invoices in different formats from different vendors, here we will not be able to get the information in a standardized format, here RPA will not be able to decipher information from those invoices & requires OCR technology to extract required information from invoices & then using RPA will copy paste that extracted information into the ERP.   

 

Automation Development Complexity :

 

RPA helps automate high volume rule-based processes & does not require any prior coding knowledge in order to build the automation. Most platforms such as UiPath & Blue-Prism provide flowchart based designs which makes it easy to automate business processes. Nowadays platforms like Uiath provide StudioX where a business owner can build automation logics himself/herself in order to automate its simple routine tasks.

 

IPA requires coding knowledge & require expert IT professionals to build the automation logic as it includes scenarios like API automation in order to integrate applications or classification of invoices involves a complex logic, which requires knowledge of model building & these tasks only be performed by expert developers having expertise in such areas.

 

Scalability :

 

RPA bots can easily be monitored & scaled up or down quickly basis the changes in work volume since we are here dealing with repetitive, rule-based tasks. Thus with changing work demand, RPA bots can be easily & quickly deployed at minimal costs without any compromise in terms of quality of work. Eg: RPA bots can be easily monitored & scaled by leveraging Uipath Orchestrator which will ensure their efficient utilization with minimal to no human intervention.

 

IPA on the other hand, requires considerable effort when it comes to scaling the technology as the work involved is of higher complexity & this results in higher deployment costs as well. However coupled with RPA can be scaled up or down to a lesser degree of effort as it will be implemented to augment the effort of RPA bots. 

 

Underlying Technology :

 

RPA thrives on common technologies like Screen Scrapping, Workflow Automation which supports in automating back end business processes with more accuracy compared to when they were manually executed.

 

IPA brings & supplements RPA with newer technologies such as Natural Language Processing (NLP), Machine Learning (ML), Data Extraction (OCR) in order to supplement the existing capabilities of RPA so as to perform more complex tasks.

[Babita Mallick]

 

Robotic Process Automation (RPA)	Intelligent Process Automation (IPA)
RPA uses technology to emulate human tasks to complete a business process. RPA bots mimics the human actions that are repetitive computer based tasks and are rules-based with defined inputs & outputs, repeatable and occur frequently.	IPA is the process of combining RPA with digital process automation (DPA) and artificial intelligence (AI) to create business process automation.
RPA is helpful to automate high volume processes for which people were formerly engaged; for example, sending an automatic reply to an email.	IPA can handle more complex end-to-end processes, both unstructured and structured data and helpful in automating non-routine task which need thoughtful considerations including judgements and conclusions.
Unlike AI, RPA bots generally do not have the ability to learn. It follows rule based instructions. For example, if a changes occurs in an automated task, the bot will not be able to adjust and figure it out on its own. RPA can only mimic human actions unlike AI which is intended to simulate the ways that human think.	IPA has built in knowledge repository, learning capabilities and brings a measure of decision making to the process.
RPA needs structured data for it to perform.	IPA can turn an unstructured data into structured data to use with RPA technologies.
RPA evolved from three primary technologies: screen scrapping, workflow automation and AI.	IPA refers to the application of Artificial Intelligence and related new technologies, including Computer Vision, Cognitive automation and Machine Learning to Robotic Process Automation.

One major industry with RPA and IPA commonly used is the Insurance Industry. Using traditional RPA, some of the processes can be automated while using a lot more processes in insurance can be fast-tracked using cognitive automation. Auto Insurance, for instance, depends heavily on images of the cars or vehicles that are damaged using which the claim is assessed.  When using image recognition, RPA can access the claims and process it with minimal human intervention.  

[Subham De Sarkar]

Intelligent automation uses artificial intelligence (AI) technologies like machine learning, natural language processing, structured data interaction, and intelligent document processing, whereas RPA typically focuses on automating repetitive tasks and rules-based processes. RPA is great for repetitive tasks that frequently string together to form a simple business process, like logging into an account, clicking a box, or moving a file from point A to point B, for instance, when you log in to your email account with the same username and password.

The RPA solution does not function entirely at its best when a variation is introduced, it is a fact. Variations are adapted by people, but software bots that only follow rules do not. Due to this The RPA solution does not function entirely at its best when a variation is introduced, it is a fact. Variations are adapted by people, but software bots that only follow rules do not. Because of this, rule-driven RPA is inferior to AI-driven Intelligent Automation, also known as Intelligent Process Automation (IPA). IPA implements RPA capabilities in addition to adding capabilities to process automation that are only possible with bots that can continuously learn and adjust to changing data.

[M V Ramana]

RPA is a software-based robot (or bot) that is capable of automating human actions or behaviour in the workplace, generally for administrative functions.

RPA, refers to a set of automated tools that help enterprises / businesses automate processes by mimicking human actions on computers, with little or no human assistance.

RPA is designed to minimize the burden for workers of mundane, repetitive tasks.

RPA is regarded as a transformational technology that can bring significant value to the organizations adopting it.

To automate any business process RPA allows to configure own software robots.

 

IPA abbreviation is Intelligent Process Automation and refers to the application of Artificial Intelligence and related new technologies, combined with RPA application.

The robot learns from doing tasks and becomes smarter after the completion of every task using IPA.

IPA grants the robot access to endless possibilities of potential tasks and processes to automate.

Adding intelligence to IPA creates transformation across the full spectrum of emerging technologies.

 

The main difference between RPA and IPA

Automating repetitive tasks and rules-based processes are focused by RPA, artificial intelligence (AI) technologies like machine learning, natural language processing, structured data interaction, and intelligent document processing are incorporated by intelligent automation.

Cost of adoption is one of the differences between RPA and IPA

[Godwin Thomas]

RPA	IPA
RPA stands for Robotic Process Automation	IPA stands for Intelligent Process Automation
RPA provides mechanisms to build and manage software robots that can imitate human actions based on pre-defined rules with speed, accuracy and availability thus helping to automate repetitive, less cognitive mundane tasks.	IPA is the combination of RPA and AI or in other terms, an upgraded RPA. IPA provides capability to develop bots that can continuously improve by learning from humans.
Rule based, the bots cannot think and take decisive actions.	Structured/unstructured Data based with continuous learning capability provides decision making ability to the bots and keep improving.
Example: In an invoice approval workflow, RPA can be designed to have predefined sequence with Person A approving the invoice and then it needs to move to Person B and so on.	Example: With IPA a variety of use cases and complexity can be addressed to fit for scenarios such as understanding if all approving authority are available and if not, take decisions to move the workflow to the next available suitable authority, route the workflow to different stake holders with additional steps depending on certain variables in the invoice
Based on certain keywords, RPA can categorize files/emails/folders	IPA can classify or categorize using advanced sorting criteria such as an email pertaining to a particular subject coming from a particular person within a certain timeline needs to be moved to a certain label.

[Mayank Gupta]

While all answers are very detailed and informative, there are two answers that clearly bring out the difference between RPA and IPA. These examples highlight how IPA is the next level of RPA and hence both of them have been selected as the best answers - Congratulations to Hirak Raval and Ashish Kumar Sharma. 

[Dheeraj Bhardwaj]

Difference between RPA and IPA 

 

 

S.no	RPA	IPA
1.	Robotic Process Automation	Intelligence Process Automation
2.	Software that mimics human behavior	Combination of RPA +AI +Machine Learning
3.	Based on Manually written, rule engines and algorithms	Based on more complex and end to end process solution with decision making capabilities.
4.	Can not auto learn new capabilities.	Can auto learn new capabilities
5.	Example- Processing Payroll, Call Center Operations	Example- Natural Language Processing, Computer Vision
6.	Best used for volume processing without too much decision making	Best used for decision making required to move between steps
7.	Human dependency reduced but not completely	Can be process without Manual Human intervention