Create a simple bot to fill Timesheets

Do you want to get your feet wet by building a quick RPA bot?

Here is an interesting project to get you started. This should take you around 20 minutes to complete.

Each of the steps is broken down into a few actions in a video of about 1 to 2 minutes. So hopefully, you can go through each step and get to your bot in less than 20 minutes.

As shown in diagram on top, you would enter data into an Excel Timesheet and invoke the bot using “Cntrl + T”. The bot will then read the Timesheet data and input it into the Aptivo Timesheet system.

Sounds simple? Let us create an Attended bot with UiPath to carry put these steps. So, let us start by installing UiPath.

Install RPA tool

Go to the UiPath Community edition home page and follow the steps in this 1-minute video to install UiPath. 

Now that we have our UiPath Studio ready, let us do some groundwork for the automation.

Project Groundwork

Let us create the spreadsheet and get set up on the Timesheet application before we start on the project.

First, create a spreadsheet with the below format. You can also download and use my spreadsheet (right-click and save)

2020-01-15 10_03_20-TimeSheet.xlsx - Excel.png

Next, let us also sign up for the Apptivo application. Go to and sign up. Once you get in, you should see an interface like this. The Timesheet is under “Project Management” (menu on top).

2020-01-15 08_45_56-Home _ Apptivo.png

Create Attended Automation Project

Let us first create our project using the UiPath “Trigger Based Attended Automation” template. It gives you a basic template to build Attended automation. Follow the steps in this quick video and you will be all set.

So, we set a trigger to start our Automation – “Alt+ T”. That was pretty simple so far, right?

Now let us get to the meat of the Automation. We will start by reading the spreadsheet.

Reading the Timesheet entries in Excel

Here we will use UiPath Excel activities to read the spreadsheet and store the data in a DataTable variable. The variable as we know is a place to store data and Datatable is used to store big pieces of information like the spreadsheet data in this case. We will also add a Try-Catch activity to handle any exceptions – we will start with that in another 1-minute video.

So, we now have all the Timesheet data read and stored in our DataTable. We will now iterate for each row in the DataTable and input the data into the Timesheet Application.

Creating the Timesheet in Apptivo Timesheet

We have made it to the last part of the Automation! This part is a little bit harder than the rest. Here we will use a Web recorder to record the steps to input the data into the Apptivo application. Ensure that you have the Apptivo application open and signed in on your Chrome browser.

Let us start by setting up the DataTable Iteration in another quick video.

As you have seen, there is some code we need to add to update the values. Here is the code so that you can paste them in quick:



You can replace “Sun” in the above code with Mon, Tue, Wed, Thu, Fri, and Sat to read all the columns from the Timesheet.

Did you get through fine? Sometimes the web recorder may be a bit tricky. If there are issues, try recording again. If you still have issues, leave a comment or drop me a line.

Hopefully, you could build the bot. Let us run the automation and test it now.

Running the Automation

Let us now take our Automation for a spin. Go ahead and run the Automation from the Studio.

If you did everything right, it would take data from your spreadsheet and create entries in the Apptivo Timesheet application.

Try adding another task with hours in your spreadsheet and run again. It should create two Timesheet entries in the application.

If you do Timesheet entry every week, you can try it out on your application as well. If you are starting out though, I would suggest that you create this project as-is and then take up the part of customizing for your application.

How was the experience? Were you able to follow along and build the bot? Appreciate if you can share your experience and let me know if this was helpful.


Would RPA emerge as a Transformative tool for companies?

With Process Automation as the core, RPA is emerging as a hub to add and orchestrate emerging technologies to solve business problems.

Organizations have started using RPA for:

  • AI / Machine Learning (ML)
  • Document Processing (ICR, OCR)
  • Natural language processing (NLP)
  • Computer Vision
  • Text Analytics
  • Conversational AI (Chatbots)
  • Process Mining and Discovery
  • and more..

More skills are being added daily on all the top RPA Platforms:

  • AA Bot store
  • UiPath Go!
  • Blue Prism Digital Exchange (DX)

Hopefully, in 2020+, we will see RPA delivering these transformations at scale enabling businesses to innovate quickly and efficiently.

Microsoft RPA – What is it? How does it work?

Microsoft now has it’s own RPA!

To me, the great news for all of us RPA practitioners is that this is another validation of the technology. With SAP and Microsoft in the fray, it is now proven that there is a real need for this kind of technology in the enterprise.

I would also argue that this technology is in a unique position to orchestrate all the emerging technologies like AI and Blockchain. With supporting technologies like Process Discovery, iBPM (Intelligent BPM), ICR (Intelligent OCR) etc. also enabling Process Automation, this is an exciting space to be in right now!

Microsoft RPA – UI Flow in Power Automate

Microsoft has added the RPA capabilities to its Flow Platform which was rebranded to “Power Automate”. The RPA capability in Power Automate is called “UI flows”.

UI flows is right now in public preview. Creating a UI flow is like in RPA – point-and-click experience with some coding. It can automate and orchestrate tasks across APIs with prebuilt connectors for more than 275 apps, SAS providers, UI-based recording, and even do Virtual agents and AI – now that may be a real end to end Automation platform!

We will look at each of the other features separately in a bit but before that, let us see how it actually works.

How does it work?

If I have to say it simply – I think it works almost like UiPath. Why not take the lead from the most popular RPA in the market? 🙂

You start off by choosing if you want to do a Desktop or Web automation.

Next up, choose the inputs you want to use. It is like adding variables in UiPath.

Then as in UiPath and other similar RPA, you have a recorder. Use the recorder to point to the items on the screen and map them.

You even get a Recorder panel like UiPath!

Once you have recorded the steps, you can add it to an overall flow like below. I feel that Microsoft has made it easier to add your Actions (like UiPath Activities) and configure them as well. So when fully developed, this may be more like StudioX and maybe better.

   Screenshots from Screengrab – courtesy Mariano Gomez

So, that was a quick look at how the UI Flow actually is. You can view a complete video of how to create a simple workflow here.

Now that you got a sense of the UI Flow RPA, let us look at the other features of Power platform itself. It is more than just RPA.

Microsoft Power Virtual Agents

This is a low-code application that allows you to create and deploy chatbots. So, from an RPA perspective, you have integrated, easy to create Chatbots that you can use with your automation.

The idea is that people in business like customer service, sales, marketing, finance, or HR can easily create these Chatbots. It has an easy to use, guided low-code point-and-click graphical interface to create these Chatbots or “Virtual agents” without the developers.

How cool is that? Microsoft Power Virtual Agents is also now in preview but you can try it out here.

Microsoft AI Builder

This is another low-code application to add AI to your workflows. They have a few prebuilt AI models– like key phrase detection, language detection, sentiment analysis, etc.

It enables organizations you to add AI to your specific business needs with your unique data without the need to hire data scientists or developers as per Microsoft. It takes common AI scenarios and provides point-and-click solutions to solve everyday tasks like forms processing, object detection, and text and binary classification.

Now available in preview, these prebuilt scenarios include:

  • Key phrase extraction— identifies the key talking points from your text
  • Language detection—identifies the predominant language for your text
  • Text recognition—extracts embedded, printed, and handwritten text from images into computer-readable form
  • Sentiment analysis—detects positive, negative, neutral, or mixed sentiment in your text data

Process Discovery with FortressIQ

Microsoft also announced a partnership with FortressIQ to enable you to discover the Processes for automation.

FortressIQ is a computer vision based solution for process discovery. They use your computer Graphics card to passively identify opportunities for process automation. Apparently, you can create a Power Automate “Flow” with the click of a button!

There are other aspects to the Power platform like Power Bi and Power Apps that you can explore here. I only covered the aspects which I thought were key to Process Automation.

So, that was a look at the Microsoft RPA and the overall Power Automate platform. It is an emerging low-code platform that can in the future help us create a quick end to end Automation.

Here is my take on what it means for the existing RPA vendors.

How does Microsoft RPA affect the existing RPA Vendors?

Not much at least for now.

The top 3 are pretty ahead in terms of what they have already built out in terms of assets and clients.

They are all built on top of Microsoft libraries but that does not discount the effort the current vendors have put in to create the market as well as the assets on top of them. It will take some time for anyone to catch up – SAP has also started along the same path.

Zooming out

I think the bigger theme is Microsoft using low code across all the Power Automate features. I think that low code is a big trend. “Learn to low code” is the new “learn to code”.

Bottom Line

Microsoft is probably testing the waters. It will take some time to catch up. Overall, It is good to know that RPA is getting attention from top tech companies.

Top 5 Open Source RPA Choices

We are seeing a good amount of interest in Open Source RPA.

To my surprise, a post on a Linux version of TagUi garnered quite a bit of interest. We recently saw a company announce a $5.6M investment to bring open-source RPA. We also had Softomotive announce a new project to develop an open-source RPA programming language.

Mainstream tool vendors have marketed RPA as “Bot” creators that can carry out tasks Cheaper, Better and Faster. While RPA mostly delivers on ROI, the Pricing or Licensing costs are critical issues hampering scalability as per HFS Research.


Source HFS Research

Considering the recent developments, I think we will soon start seeing a wider array of Open source options for RPA.

Generally, as the Technology matures, we would see more compelling open-source options that could even overtake the mainstream technologies (eg. Android, Linux, etc.)

This could be the next big thing in RPA!

So, I thought I would summarize the Top 5 evolving options we have as of now. Note that all these tools are evolving and do not have a mature Control room or Orchestrator. So, this can be used only for simple Automation.

With that said, here are my top 5 as of now.


TagUI is an open-source RPA maintained by AI Singapore, a government-funded initiative. It currently has nine contributors and has pretty good documentation.

TagUI uses “human language” like Command line syntax to build your automation. So, you can automate with “language” like this:

You can also do Visual automation for Websites and Desktop using integration with Sikuli. Under the hood, it converts that “language” you wrote or recording into JavaScript code.

Here are some key features:

  • Automate Chrome in visible/invisible mode
  • Visual automation of websites and desktop
  • Write in 20+ human languages & JavaScript
  • Chrome extension for recording web actions
  • Python & R integration for big data / AI / ML

Here are some advantages with respect to other mainstream RPA tools:

  • Cross-platform works on Windows, macOS, Linux
  • $0 to use, under Apache 2.0 open-source license
  • Headless, runs in the background – you can continue using the computer uninterrupted.

They also are in the process of adding Python RPA.

If you like to try out, TagUI tools and documentation is on Github.  Python Beta library is here.


Robin is a free open-source programming language specifically for building RPA software bots.

The idea of Robin is to develop a standard language for RPA tool development. This would enable easy migration of bots built on one platform to another.

Softomotive, the company behind Robin is looking to build its future tool version based on Robin. But would others follow suit? The current vendors are unlikely to as of now. But, we could see more Open source tools that build on top of this providing better options.

From a technology perspective, Robin is a Microsoft .NET Domain Specific Language (DSL). It runs on Microsoft .Net Common Language Runtime (CLR), the virtual machine component of Microsoft’s .NET framework. You would need a basic understanding of that to get started.

Robin Software Development Kits (SDK) is expected soon and should make it easy for developers to code. As per the site, developers can “turn your code into a Robin module filled with actions with just a few steps.”

Robin is in the initial stages and has a long way to go. It is currently at the beta stage – version 0.9. They plan to release a Version 1.0 on Github soon.

You can download and try it out!  Here is a quick start tutorial to get you started.

Robot Framework Foundation

Robot Framework is a popular open-source automation framework for Testing. It is a generic keyword-driven test automation framework for acceptance testing and now RPA as well. I am assuming they added RPA functionality as it has a lot in common with testing.

They have a dedicated page for RPA but not many details. As I understand, they have a bunch of libraries that you can use to build your automation. Some of the functionalities available include “optical image recognition, database access, HTTP APIs, iOS and Android application support, and remote execution”. I think you will have to work with the partner companies listed on the page to meaningfully use this.

Based on what I can see from the Testing framework, it can work on any operating system and on any application. It uses a syntax based on keywords that are quick to edit and configure to match the application being automated.

The core framework is implemented using Python. It is easy to create new libraries for your specific needs out of Python or Java code.

The test automation solution and has a pretty active community with many companies using it in their software development. So, the Robot Framework is actively supported and continuously improving.

The libraries and documentation are on Github with over 95 contributors.

Robo Corp

This is a new Open-Source RPA which is under development. The tool though has investor backing after a recent $5.6 million seed investment.

The Robocorp RPA is being built on top of the open-source Robot Framework project, that we looked at above. They say they have been working on it for ten months and is looking to release it soon.

As per the Robocorp builders, they want to fill a gap. “What is missing in RPA are the tools and a platform that can unify the industry and enable companies of all sizes to benefit from automation. Building this kind of ecosystem needs open-source tools that are widely available to everyone, and that is exactly what Robocorp is launching.”

They already have a Robocloud platform that they are piloting with “consulting and system integrator partners across finance, transportation, logistics, and other high-impact industries.”

Robocorp is looking to create a new industry called “robosourcing”. As per them, people will not look to outsource work to India or the Philippines. They would look to outsource work to robots and they like to be in that.

You cannot try it out yet but you can sign up here to stay updated on their progress.

Auto Magica

Automagica is a company out of Belgium that has an open-source RPA platform that they call “Smart Robotic Process Automation (SRPA)”. They have a portal where you can sign up and go about building your bot. Here is how to get started.

Auto Magica is implemented using Python.  It helps you build out Automation scripts using Python. They provide wrappers around known automation libraries to enable you to automate. It is not exactly the easiest or quickest way to automate but then with Open-source, you may want to be ready to put in the work.

Here is an example that opens Notepad and types ‘Hello world!’

Automagica officially supports Windows 10. Linux and MacOS are not officially supported as of now.

Here are a list of features:

Automagica can be downloaded from their Github site. They have pretty good videos on YouTube.


Those were the top 5 Open-source options that I have across. ‘Am I missing anything?

I appreciate your comments and feedback!




Evolution of AI through the ages

Vikas Kulhari

This is a guest post by Vikas Kulhari. Vikas is an Intelligent Automation Consultant at KPMG. He is a Certified Solution Architect helping clients design, create and maintain Intelligent and Robotics Process Automation (RPA) solutions.


Artificial Intelligence (A.I.) is not new technology anymore.

Most of the sectors have already started investing in AI research and implementation. It is ubiquitous now – Autonomous vehicles, Voice controlled bots, Facial Recognition, computer vision, ICR, search recommendations, robots, etc.

However, all of you may be thinking:

  • Who invented AI?
  • Who coined this term (AI)?
  • Where did all this begin? 

So, I thought to write a post about the AI journey. Here is a brief Timeline as I see it:

1943 – Turing Machine: Alan Turing invented the Turing test, which set the bar for the intelligent machine; the computer that could fool someone into thinking they were talking to a real person. Grey Walter built some of the first-ever robots.

1950 – I, Robot: It was published a collection of short stories by science fiction writer Isaac Asimov.

1956 – Artificial Intelligence: John McCarthy coined the term “Artificial Intelligence”. A “top-down approach” was dominant at the time: pre-programming a computer with the rules that govern human behavior. 

1969 – Shakey The Robot: The first general-propose mobile robot was built. It was able to make decisions about its actions by reasoning about its surroundings.

1968 – 2001: A Space Odyssey: Marvin Minsky, the founder of the AI Lab at MIT, advised Stankey Kubrick on the film 2001: A Space Odyssey, featuring an intelligent computer, HAL 9000.

1973 – AI Winter: The AI Winter began – millions had been spent with little to show for it. As a result, funding for the industry was slashed.

1981 – Narrow AI: Instead of trying to create a general intelligence, research shifted towards creating “expert systems”, which focused on much narrower tasks. 

1984 – Bottom-Up Approach: Rodney Brooks spearheaded the “bottom-up approach”. aiming to develop neural networks that simulated brain cells and learned new behaviors.

1998 – Deep Blue: Supercomputer Deep Blue developed by IBM, Faced world chess champion Garry Kasparov.

2002 – Roomba: iRobot created the first commercially successful robot for the home – an autonomous vacuum cleaner called Roomba.

2005 – BigDog: The US military started investing in autonomous robots. BigDog, made by Boston Dynamics, was one of the first.

2010 – Dancing NAO Robots: At Shanghai’s 2010 World Expo, 20 NAO robots danced in perfect harmony for 8 minutes.

2011 – Watson: IBM’s Watson took on the human brain in jeopardy and won against the two best performers of all time on the show.

2014 – Eugene Goostman: 64 years after the test was conceived, a chatbot called Eugene Goostman passed the Turing Test. Additionally, Google invested a billion dollars in driverless cars, and Skype launched real-time voice translation. Amazon launched Alexa, an intelligent virtual assistant with a Voice.

2016 – TAY: Tay was Microsoft’s chatbot. It caused some controversy when the bot began to post inflammatory and offensive tweets through its Twitter account. Microsoft then shut down the service after only 16 hours of launch.

2017 – AlphaGo: Google’s AlphaGo was the first computer program to defeat a professional human Go, player, the first to defeat a Go world champion, and was arguably the strongest Go player in history.

2018 – Google’s fascinating—and creepy—AI: it could make calls on behalf of a user and perform tasks such as booking restaurant tables and hair salon appointments.

2019 – Tesla and Scania’s Autonomous Vehicles: Tesla and Scania have already come up with concept self-driving cars and trucks. Scania trucks don’t have a cab and that may be a game-changer.

As AI grows rapidly, you would see a lot of big-scale AI projects shortly.


Like to make a Guest Post? Would love to hear from you.

Open-source RPA Language – Robin

Robin is a free open-source programming language specifically for building RPA software bots.

It runs on Microsoft .Net Common Language Runtime (CLR), the virtual machine component of Microsoft’s .NET framework. You would need a basic understanding of that to get started.

Robin Software Development Kits (SDK) is expected soon and should make it easy for developers to code. As per the site, developers can “turn your code into a Robin module filled with actions with just a few steps.”

To use of UIAutomation and WebAutomation actions in Robin, you have to use AppMasks. AppMasks contains the selectors for the elements of Web and Desktop Applications used.

Fair warning – this is in the initial stages and has a long way to go. You would be disappointed if you start comparing this to mainstream tools.

It is currently at the beta stage – version 0.9. They plan to have new versions every week which is pretty ambitious!

Softomotive (who has created this) may follow the UiPath Community model to enable wide adoption quickly. We should be seeing free online training soon from Softomotive.

Excited to see how this pans out.

Meanwhile, do download and try it out!  

Here is a quickstart tutorial to get you started.

What is an RPA or Automation CoE ? Why do we need it?

We have probably come across this scenario.

Bob manages Accounts Payable for his Organization. The group always had an issue with the tedious work of processing Invoices.

The IT group after all the cajoling had come up with an Oracle custom solution to reduce the work. It was an incomplete solution and also failed all the time.

Seeing all this trouble, Lin the tech-savvy intern in Bob’s group downloaded an RPA solution and demoed what can be done. Bob was excited and showed it to his boss who was even more excited.

They reach out to an RPA vendor who is happy to put in a place a quick solution within a month. Bob is a hero. No one knows about Lin though he did everything 🙂

Bob’s peers are envious. Some are scared that this automation is going to take away their jobs. They come up with an idea to use Oracle upgrade to stonewall any rollout for their group.

And the upgrade did come! One screen changed drastically – the whole automation is failing. Lin is on the phone with the vendor who is having a tough time fixing this as he had moved on to a dozen other projects that he now has.

Bob is now a Zero and so is the Organization.

In hindsight, Bob’s boss and the management thinks a CoE would have helped.

What is an RPA CoE?

An Automation/RPA Centre of Excellence (CoE) is generally a unit within the organization that provides high-quality Automation services to meet the enterprise’s strategic objectives.

The unit provides a centralized structure for all aspects of automation including resources, messaging, assets and security standards, and best practices. Quality resources and messaging would have helped Bob roll-out and manage his automation more smoothly.

Why do you need an Automation/RPA CoE?

The Centralized structure that CoE provides creates a framework for smooth roll-out of RPA and other automation technologies. It enables:

  • Robotic Strategy & leadership – ensures maximum value is delivered
  • Demand management – Process identification and prioritization
  • Change Management – Involve key stakeholders like IT, Compliance, Security, Procurement etc.
  • RPA Tool management – Efficient use of automation vendors, Tools, and Licenses
  • RPA Capability development – A pool of quality resources across all phases
  • Consistent Implementation – Standards for Design, Implementation & Support
  • Organizational IP – Reuse of robot assets and code
  • Benefits Tracking – Establish, measure and report metrics
So an RPA CoE enables your automation journey right from Strategy to reporting.
Most organizations tend to try out RPA and evaluate it’s potential before rolling out a CoE. It is wise to lay the groundwork for your CoE as you do this though. You can then grow it out as you progress on the journey.  For eg. You can define your Strategy ahead and have a few team members focussed on the key aspects like Change Management,  Tool Management and capturing Best practices during the initial implementation.
That was a quick look at What and Why of RPA CoE. We will look at the structure of typical CoEs, when and how to set it up in a future post.

The Emerging RPA Platforms

This post is based on a Webinar. If you like to watch that for more details, it is here.

We live in a complex world with rapidly evolving Technologies. The rate of human progress has increased exponentially what Ray Kurzweil calls “The Law of accelerating returns”

In a world of exponential Technologies, it becomes difficult for any single person or vendor or provider to have all the answers. So we have to make sense of these Technologies together – a networked sense-making

Towards this many of the software vendors including the top RPA vendors are inviting all of us to be part of this sense-making. They’re moving towards being platforms where all of us can participate.

RPA Core

In the RPA world, the core platform includes bot(s), a studio and a controller. I like to call this the “operating system” for bots because they provide you a way to build and manage the Bots.

You configure your workflows within the studio and attach them to the Bots which is deployed and managed using a Controller. The terms for these components may change like the Controller may be called Orchestrator or Control room but the core philosophy of the RPA tools remains the same.

This was and remains the core platform. Now there are many components plugging into this provided by the vendors themselves, their partners and people like you and me.

Process discovery

One of the key areas of innovation plugging into this platform is happening upstream to discover the processes. The Process discovery component is being included by the vendor themselves or is being provided by partners. Some vendors are claiming that a major chunk of the automation workflow can be automatically generated using this tool.

Strategic Skills

Within the platform, many of the RPA vendors are including more and more components which they see as strategic and necessary for the tools to be successful. For example, Blue prism just came out with Decipher which addresses unstructured data. UiPath has a multitude of “Activity packs” and Automation anywhere has many reusable components through their Bot store. 

These components can mostly be included in your workflows through drag-and-drop interfaces. I think the RPA vendors will keep adding these drag-and-drop components as needed. But there is a limit to what each of the vendors can develop.  


This is where it gets interesting – the tool vendors are adopting a Platform approach where you and me can contribute to this ever-increasing components for automation. You can contribute components even now though it cannot be monetized.  I think we are moving to a future where we would have wider participation and you can monetize what you contribute.

So we are moving to an app store like approach where you have different operating systems and applications for those operating systems. Like you participate in the Google Play Store or IOS app store you have different RPA platforms on which you can automate Enterprises using the respective ecosystems.


Finally, this platform sits on top of a foundation enabled by the RPA vendors.  This includes a learning academy where you can learn and try out the tools.  You also have a community where you can make sense of the evolving technologies together. The vendors also have an ecosystem of Partners that can help you with your automation.


So this is what I see as the emerging RPA platform.  A platform where you can use the rapidly emerging technologies to solve real-world business problems.

RPA is not a path to AI

Let’s start with the standard narrative on RPA.

RPA then Cognitive  

RPA is supposed to be the “gateway drug” to Intelligent Automation and beyond.

RPA  is low-level stuff – screen scraping and rule-based. Then there’s Intelligent automation (or similar term) which includes pattern recognition and finally, there’s cognitive where you move to human-like self-learning.

So some people have come to think that it’s all neat little boxes where you flow from one to another both in terms of a career as well as how you implement automation.

While the overarching narrative is correct, there is some misunderstanding though.

Career path

If you are into RPA thinking that you would first learn RPA and then move into AI, then I think that is a wrong assumption.

RPA is more of a process Improvement track which we have been on for more than 30 years now. It’s a continuation of the Journey of TQM, EAI, BPM and BPA. To me, RPA is a career in process improvement and automation.

Modern AI has a similar but different track which starts with the Dartmouth summer research project Followed by multiple AI Winters finally culminating in deep learning and beyond.

So, AI is a completely different career track which impacts a lot more than automation. If you like to be on AI, you should go pursue that track.


In terms of implementing RPA, some people tend to think that you do RPA first and then you get to intelligent Automation and then Cognitive. I think that’s another misunderstanding. You do not need to wait to incorporate any technologies that suit your automation.

Include Cognitive right from the beginning. In fact, include all available technologies that can help with the use case being automated.

The good news is that you can do that with RPA. You always could – we always used an ecosystem of technologies including internal IP for automation projects.

RPA vendors are making it easier to include emerging technologies as drag-and-drop. They are extending the low code simplicity to include other technologies. So go ahead and include what’s appropriate for your automation now.

RPA is a path to Future of Work

RPA is a way to introduce Digital labor into the Enterprise. RPA is a path to Process Improvement and Automation. So for me, RPA is a path to the future of work where humans work with Bots.

As a career, if you like to stay in automation then RPA is a good bet. If you like to pursue AI, you probably should take up AI separately. You can also do both but you would mostly be better off specializing in one of them.

While you implement RPA, don’t get into the “first RPA then Cognitive” narrative – it is not a sequence. Include Cognitive right from the beginning. Choose fairly decent RPA platform and design your ecosystem including Cognitive now.