Q. 207 As AI gets more powerful in coming years, what will happen to the fast growing RPA? Will RPA be aided by better AI and grow faster? Or will RPA's growth rate slow down? Give reasons to explain your answer.

 

 

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Robotic Process Automation (RPA) it emphasises on using machines to do time consuming, repetitive, objective, transactional, and mostly mundane activities which other wise will need humans to do. Since these are repetitive and transactional in nature it would be better structured and can be broken down to simpler process steps. It will tend to replace or shrink the human resources needed for delivery 

 

Artificial Intelligence on another hand focuses more on supporting the human resources with analysis and insights which otherwise would be tough for a normal human brain to validate / interpret. Its main focus remains on the aiding the human resource rather than replacing. With the multiple tools available in market primary use of AI is for finding anomalies, insights, simulation, etc.

 

In years to come, RPA will grow but rate of growth will slowdown. Improvement in AI will aide the growth of RPA but the contribution may not be a breakthrough in volume or value. For any RPAs currently work on a stable process/ transactional process. It may not be wrong in totality that AI will lead way for RPA as Analytics and Insights will help define the process and once they are standardized can be used as input for further processing into different interfaces or applications.

 

A fictitious scenario of 2050 or 2100 may be - having the RPAs driving the necessary functions for AI, extract output, post process, etc.

 

However,  like it is said... Artificial Intelligence being Artificial cannot replace human brain same way RPA cannot replace AI. RPA will hold a special importance from an delivery speed, cost, and quality perspective but it will eventually slow down once the transactional piece of work is exhausted... it can take over the mass not the class.

To automate or not to automate is no longer a question anymore. Enterprises will have to integrate IA and automation for their own benefit and survival, RPA Will be better aided by AI and grow faster….

 

It is important to understand that RPA and AI are nothing, but different ends of a continuum known as Intelligent automation

 

AI that augment and mimic human judgment and behaviour complement RPA that replicate rules-based human actions “The two technologies work hand in glove, just like traditional ‘white-collar’ knowledge-based workers and ‘blue-collar’ service-based workers collaborate to drive productivity for an organization”

 

In a sense, it doesn’t matter whether we think or know that RPA is a specific branch of AI or not, but we should be aware that the two technologies are increasingly going to work together.

 

Intelligent Process automation:

 

Reshaping the future of work with automation

 

IPA “takes the robot out of the human.” At its core, IPA is an emerging set of new technology that combines fundamental process redesign with robotic process automation and machine learning. RPA tools assist the human workers by removing simple, routine, repetitive, rule based tasks.

 

IPA encompasses five core technologies:

1.    Robotic Process automation

2.    Smart workflow

3.    Machine learning

4.    Natural-language generation (NLG)

5.    Cognitive agents

 

With Intelligent process automation, bots can replace manual clicks (RPA), interpret heavy text (NLG), make rule-based decisions (machine learning), offer customers suggestions (cognitive agents), and provide real-time tracking of handoffs between systems and people (smart workflows).

 

Analysts predict automation technologies will have an economic impact of between $5.2 and $6.7 trillion by 2025. Technologies such as machine learning, big-data, RPA work in tandem to support this trend.

 

Combining RPA with intelligent technologies means that the “learning” process can take place at faster pace, while these two technologies are only starting to be used together, the enhanced automation they produce can help organizations to foster both increased productivity and creativity going forward.

Robotic Process Automation is a way of automating (using machines called bots)mundane rule based tasks which do not have any exceptions.

 

Robotic: Robots or Bots are machines that can copy the human actions facilitated either by coding or recording the screen.

 

Process: A series of steps that leads to an output is called a process. Something as simple as making tea or your favorite dish is also a process.

 

Automation: Any process which is done by a robot without human intervention.

 

Automating simple, rule based, sequence of steps that lead to an output is known as Robotic Process Automation.

 

RPA helps us to save our time and resources, what took hours/days/weeks to perform tedious tasks one after the other now they can be performed with speed, accuracy and precision so that we can have time to think, to be creative and pursue new ideas.

 

RPA is probably the fastest path to digital transformation with efficiency and effectiveness.

 

RPA is a technology that enables computer software to emulate and integrate actions typically performed by human interacting with digital systems.

The computer software that executes the operation is called a “ROBOT”, RPA Robots are able to capture data, run applications, trigger responses and communicate with other systems.

 

RPA targets processes that are---

1. Highly manual.
2. Of low-complexity.
3. Stable.
4. Repetitive,
5. Rule based. 
6. With lower exceptions rate or without exceptions.
7. Standard electronic readable input.

 

Artificial Intelligence is concerned with design of intelligence in an artificial device or mimicking human actions with intelligence built in the machines.

What describes intelligence?

1.    Having intelligent behavior like a human.

2.    Behaves in a best possible manner.

3.    Thinking capabilities.

4.    Acting capabilities.

 

There are three types of AI systems---

1.    Artificial Normal Intelligence (ANI)--- it is also known as weak AI. Systems that cannot truly reason and solve problems but can act as intelligent simulating pre-defined human behavior. They do not possess thinking abilities like self-driving cars, Siri, Alexa, Sophie-humanoid, etc. all AI developments currently fall in this category.

2.    Artificial General Intelligence (ASI)—It is also known as strong AI. These systems are self-aware, thinking capabilities like humans. No examples as of now.

3.    Artificial Strong Intelligence (ASI)—when capabilities of machines will surpass human beings. It is a hypothetical situation. Examples are several movies showing machines gaining control over humans.

 

RPA is just mimicking repeatable human actions based on certain pre-defined rules using AI.

Whereas AI is simulation of human intelligence by machines.

 

RPA is a ll about doing whereas

AI is a very broad and wide term as it is all about building all human capabilities into a machine. thinking and acting capabilities are not rule-based or repetitive and are rather complex.

 

Both are used for solving-real world problems RPA utilizes very little AI capabilities like cognitive tools (OCR, etc), but AI has a broad spectrum over RPA because it utilizes—

Machine learning capabilities, Deep learning capabilities, Natural language processing & understanding, Robotics, Expert systems and Fuzzy Logic, cognitive Science.

 

RPA is process driven, it’s in it name, it automates repetitive activities and, in this pursuit, it interacts with several system through IT systems. It involves process mapping, process documentation i.e. all activities relating to process improvement and/or process automation opportunities assessment and process Design Documentation for implementing RPA.

Whereas AI is about good quality of data i.e. helping RPA to complete its work using machine learning i.e. reading data for implementation into the RPA project from sources like invoices, forms, etc.

 

For example, RPA project involves invoice processing. Customer sends an invoice through email, robot will read email; download the invoice; now the AI comes into reading contents from the invoice utilizing machine learning capabilities using human intelligence using ML algorithms or using cognitive tools like OCR (optical character reader).

 

Popular RPA tools are------

1. Uipath-- its a software which is user friendly and utilities drag and drop activities requiring very little programming skills in visual basic and .Net technologies.

2. Automation Anywhere-- it's also a software but it requires programming skills in C# (c sharp) and .Net technologies.

3. Blue prism-- it also requires programming skills in C# and .Net technologies.

 

whereas some of AI tools are---

1. IBM Watson

2. Googles TensorFlow (cloud based)

3. Infosys Nia

4. Wipro Holmes

5. Microsoft Azure

6. TCS Ignio

 

Both RPA and AI are growing leaps and bounces, both complement each other i.e. RPA uses AI machine learning algorithms and AI uses Robots, but AI is much broader and wide concept. 

 

Mckinsey & Company says, about 22% of the IT jobs will be replaced by RPA in the coming years. FORRESTER Says, RPA market will grow by 2.1 Billion Dollars by 2021. It is expected that in 2021 there will be 2 Lakhs jobs for RPA professionals in India.

 

According to market research firm Tractica, AI software market is expected to grow from around from 9.5 billion US dollars in 2018 to an expected 118.6 billion US dollars by 2025.

According to world economic forum, automation will replace 75 million jobs but will generate 133 million jobs worldwide by 2022

 

RPA is expected to grow faster with AI getting stronger. 

 

Image Analysis and Text Analysis, for example are two areas within RPA that will be more successful as it is infused with Machine Learning capabilities. Reliable Artificial Intelligence can make more processes RPA-ready in future. Large number of processes today are considered unsuitable for RPA because of good percentage of exceptions in them. If Artificial Intelligence can reduce these exceptions significantly, or ideally eliminate them, RPA will become the preferred mechanism for such processes. 

As AI continues to advance, the landscape of Robotic Process Automation (RPA) is likely to be significantly impacted. Here are some potential scenarios and reasons for how AI might influence the growth of RPA:

RPA Growth Aided by AI Enhancements
Improved Capabilities: Enhanced AI can improve the capabilities of RPA by making bots smarter and more versatile. For instance, AI can enable RPA bots to handle unstructured data, understand natural language, and make decisions based on complex rules.

Broader Application: With better AI, RPA can be applied to more complex and varied tasks. This would lead to broader adoption across industries, thereby accelerating growth.

Automation of Cognitive Tasks: AI can help RPA move beyond simple, rule-based tasks to automate cognitive processes that require understanding and interpretation. This would significantly expand the scope of RPA.

Integration with AI Tools: Seamless integration with AI tools such as machine learning models, NLP engines, and computer vision systems can make RPA solutions more powerful and comprehensive, driving higher demand.

AI Development Services: Companies offering AI development services can further enhance the integration of AI with RPA, providing specialized solutions and support that accelerate the adoption of AI-enhanced RPA across various industries.

RPA Growth Rate Slows Down
Shift to AI-Driven Solutions: As AI becomes more capable, organizations might shift their focus from traditional RPA to more sophisticated AI-driven automation solutions. This could slow down the growth rate of RPA as a standalone technology.

Complexity and Integration Challenges: The integration of advanced AI with RPA can be complex and may require significant investment in technology and skills. This might slow down the adoption rate as companies navigate these challenges.

Market Saturation: In markets where RPA has already seen significant adoption, growth might naturally slow down as the technology reaches maturity. Companies might look for the next big thing, which could be AI-driven automation, rather than traditional RPA.

Factors Influencing the Outcome
Innovation and Adaptation: RPA vendors' ability to innovate and integrate AI capabilities into their offerings will be crucial. Those that successfully leverage AI to enhance their products will likely continue to see strong growth.

Industry Needs and Trends: The specific needs and trends within various industries will also play a role. Industries with high volumes of repetitive tasks might continue to rely heavily on RPA, especially if AI integration makes it more powerful.

Economic Factors: Economic conditions and the availability of investment for technological upgrades will influence how quickly organizations can adopt AI-enhanced RPA solutions.

Conclusion
Overall, AI has the potential to significantly aid the growth of RPA by making it more capable and applicable to a wider range of tasks. However, the growth rate might vary depending on how well RPA solutions can integrate AI, the complexity of such integrations, and market dynamics. The most likely scenario is a symbiotic growth where AI enhances RPA capabilities, leading to an overall increase in the adoption and sophistication of automation solutions. Companies that provide AI development services will play a pivotal role in this evolution, enabling smoother transitions and more effective integrations of AI within RPA frameworks.