5 RPA Programming Options You Need to Know in 2024
Hi there! As an RPA consultant, I often get asked – what are the top RPA programming options I need to know about for automating processes in 2024?
It‘s a great question. With robotic process automation exploding in popularity, having the right programming approach can make or break your automation initiatives.
In this comprehensive guide, I‘ll walk you through the five RPA programming options making an impact this year:
- Code-based RPA
- Low-code/No-code RPA
- Recording RPA
- Conversational AI RPA
- Self-learning RPA
For each approach, I‘ll overview how it works, key benefits, potential limitations, and when it‘s the best choice. You‘ll get actionable insights to pick the right RPA programming style for your needs.
Let‘s dive in!
Code-Based RPA Programming
With code-based RPA, developers write lines of code to program robotics process automation scripts. This typically involves using a language like C#, VB.Net, Python, or Java to interact with applications, extract and input data, make decisions, handle errors, orchestrate tasks, and more.
Code-based RPA gives you complete control over the automation logic. Developers can build complex algorithms, integrate APIs, implement robust error handling, and customize bots to your heart‘s content.
But with great power comes great responsibility. Code-based RPA requires skilled developers and longer development cycles. You can‘t just drag and drop some blocks to automate processes. This approach demands serious programming muscles.
Let‘s explore the key pros and cons of code-based RPA:
Pros
- Complete flexibility to customize automation logic
- Handles exponentially complex processes and decision trees
- Can integrate APIs and connect to other systems as needed
- Enables robust error and exception handling
- Mature option leveraging proven programming languages
Cons
- Requires experienced RPA developers
- More time intensive to develop and maintain vs low-code
- Not user-friendly for non-technical people
- No built-in activities – developers must code all logic
- Changing requirements means rewriting code
As you can see, code-based RPA is a double-edged sword. You gain unmatched control and customization for automation. But you sacrifice speed of development and business user involvement in favor of technical specialization.
When Code-Based RPA Shines
Code-based RPA works extremely well when:
- You have complex decision logic, data transformations, or integration needs
- Your developers have the skills to code automation scripts efficiently
- Your processes don‘t change often so maintenance is low
- You value total control and customization over rapid development
For example, code-based RPA is great for:
- Automating intricate approval workflows across multiple systems
- Parsing unstructured data using advanced AI algorithms
- Connecting APIs to orchestrate end-to-end processes
Key Vendors Offering Code-Based RPA
If you decide code-based RPA is right for your needs, some top vendors to evaluate include:
- UiPath – Supports C# and VB.Net for Studio Pro and StudioX
- Automation Anywhere – Uses traditional coding languages and Java for IQ Bot
- Blue Prism – Leverages C# and VB.Net for development
- Microsoft Power Automate – Enables coding bots with C# and Python
These tools provide seasoned developers the languages and environments to build the highest quality automation. Now let‘s explore a very different RPA programming approach – low-code and no-code platforms.
Low-Code/No-Code RPA Platforms
Low-code/no-code RPA platforms minimize or eliminate the need to write code when building bots. Instead, they use visual, drag-and-drop interfaces to develop automation.
Low-code RPA tools like UiPath Studio offer hundreds of pre-built activities for things like reading emails, scraping data, filling forms, and more. Developers simply piece these blocks together into flows like a jigsaw puzzle.
No-code platforms like Automation Anywhere allow business users with zero coding skills to automate processes entirely visually. Anyone can be a bot developer!
Let‘s examine the unique pros and cons of low-code and no-code RPA:
Pros
- Much faster bot development vs coding everything
- Intuitive interfaces allow non-technical staff to automate
- Built-in activities reduce programming effort
- Changes can be made quickly by updating flows
- Democratizes RPA across the business
Cons
- Less flexibility than coding custom scripts
- May still need coding for very advanced logic
- Some constraints around customization
- Dependence on vendor built-in capabilities
So with low-code/no-code RPA, you trade off some degree of customization for radically faster development and business user empowerment. But for many simpler automation use cases, you never need the total control that coding provides.
When Low-Code/No-Code RPA Excels
Low-code/no-code RPA works great when:
- Your processes are relatively straightforward and rules-based
- You want business teams to own automating simple tasks
- You prioritize development speed over complete customization
- Your developers have limited bandwidth to code bots
For example, these tools shine for:
- Automating repetitive data entry across systems
- Pulling simple reports and distributing via email
- Scraping websites and saving data to a database
Leading Low-Code/No-Code RPA Platforms
Some top low-code and no-code RPA platforms to consider include:
- UiPath – Low-code Studio + no-code StudioX
- Automation Anywhere – no-code Bot Store collection
- Microsoft Power Automate – Low-code desktop flows
- Blue Prism – Low-code Process Studio
These tools make RPA accessible to technical and non-technical teams alike. Next up, we‘ll explore RPA bot recording.
RPA Bot Recording
Many RPA platforms can watch and record your actions, then convert those recordings into bots.
For example, recording software tracks as you log into Salesforce, copy some data, switch to Excel, paste it in, format a table, and so on. Those recordings are translated into automation scripts.
This approach requires zero coding or drag-and-drop skills. You simply perform the steps you want automated while the recorder captures your every move.
Let‘s break down the unique advantages and disadvantages of RPA recording:
Pros
- Extremely fast way to generate automation
- Allows non-technical people to build bots
- Works well for simple, repetitive processes
- Saves screenshots to document the automation
Cons
- Recordings often need cleanup before deployment
- Captures existing process vs optimal process
- Maintaining recordings can be challenging
- Advanced logic requires other methods
RPA recording removes the barrier to get started automating. In minutes, you can generate bots and prove out the technology. Just beware that recording alone may not result in robust, enterprise-grade automation. Plan to refine recordings using other techniques.
When to Record RPA Workflows
Recording works splendidly when:
- You‘re new to RPA and want quick wins
- Your processes are simple and repetitive
- You want a kickstart on automation possibilities
- You can use recordings as templates for further development
For instance, recording shines for:
- submitting data in web forms
- transferring data between basic systems
- conducting simple application testing
- prototyping early bots as a starting point
Top Vendors With Recording Capabilities
Many RPA platforms incorporate recording capabilities, including:
- UiPath – UiPath Recorder feature
- Automation Anywhere – Bot Insight auto-recorder
- Blue Prism – Process Recorder
- WorkFusion – Smart Process Automation recorder
- Microsoft Power Automate – UI flows browser recorder
Recording is a fixture of most RPA tools nowadays. Let‘s level up to conversational AI bots.
Conversational AI RPA Bots
Conversational AI takes RPA programming to the next level by enabling natural language conversations to automate tasks.
Rather than coding or clicking around a visual interface, users simply describe automation needs in plain English. For example:
"When new expense reports come in, extract the total amount and send it to the accounting system."
Natural language processing (NLP) allows the bot to understand these instructions, then automatically build and execute the automation script.
Conversational AI makes RPA programming seamless and intuitive. But it does have some limitations currently. Let‘s analyze the pros and cons:
Pros
- Extremely user-friendly way to automate
- No coding or technical skills required
- Rapid bot programming with plain English
- Bots improve the more they converse
Cons
- May require cleanup of bot logic post-conversation
- NLP accuracy limits process complexity
- Security risks if exposed to external traffic
- Requires advanced AI capabilities
Conversational RPA removes virtually all user effort from bot building. The tradeoff is handling complexity beyond basic tasks may remain challenging until the technology matures further.
Where Conversational RPA Excels
Conversational AI for RPA works wonderfully when:
- You want business teams automating tasks independently
- Your processes follow simple rules and logic
- You value productivity and ease of use over advanced functionality
- You can start small while the technology evolves
It brings automation multiplying benefits for things like:
- Pulling customer data from a CRM
- Copying spreadsheet data to fill web forms
- Running reports and emailing the output
- Importing data from websites into centralized databases
Leading Conversational RPA Platforms
Some top vendors delivering conversational RPA capabilities include:
- Automation Anywhere – Bot Store actions driven via natural language
- UiPath – Assistant chatbot enabling conversational development
- Microsoft Power Automate – Natural language UI flows (preview)
- ServisBOT – Full conversational RPA platform
Over time, expect more RPA platforms to integrate conversational interfaces using the latest NLP and AI. This leads us to our fifth and final programming option – self-learning RPA.
Self-Learning RPA Bots
Self-learning RPA solutions take human effort out of bot programming using AI capabilities. These tools observe how employees work and derive automation opportunities on their own.
For example, a self-learning bot might shadow an employee for weeks as they process invoices. Using computer vision and OCR, the bot understands the steps to follow and data to extract to automate the invoicing.
This removes the need for coding, dragging, recording, or conversing to train bots. The bots essentially train themselves!
Let‘s examine the pros and cons of self-learning RPA:
Pros
- Fully hands-off automation identification
- Uncovers automation possibilities you may miss
- Analyzes processes to automate smarter
- Requires no human bot training effort
Cons
- Still an emerging technology
- Can suggest automating remediable inefficiencies
- May require large volumes of training data
- Security and control risks of self-directed bots
Self-learning RPA shows amazing potential to revolutionize how businesses automate. But the technology is still evolving with key challenges to overcome.
Where Self-Learning RPA Shows Promise
Self-learning RPA looks extremely promising for:
- Automating repetitive back-office processes
- Uncovering automation opportunities enterprise-wide
- Document processing and handling unstructured data
- Assisting human workers vs. fully automating
It could bring breakthrough benefits for:
- Processing forms and extracting information
- Reading emails and routing based on content
- Reviewing documents and redacting sensitive data
- Providing process recommendations to employees
Emerging Self-Learning RPA Vendors
Some leading RPA vendors with burgeoning self-learning capabilities:
- UiPath – Process mining and process advisor
- Automation Anywhere – IQ Bot auto-generating automations
- Microsoft Power Automate – Process advisor (preview)
- Roboyo – Digital workforce manager with process discovery
While nascent, self-learning RPA could redefine enterprise automation in the coming years.
Guide to Choosing the Right RPA Programming Approach
We‘ve covered the five main RPA programming approaches making waves right now. Let‘s distill some recommendations to identify the best option for your business needs:
Consider Your Developer Bandwidth and Skills
- If you have ample skilled developers, code-based RPA enables total customization
- With limited developers, low-code/no-code speeds automation and spreads RPA across the business
- No technical staff? Focus on recording and conversational RPA to start
Evaluate Your Process Complexity
- For intricate processes, code-based RPA provides the control needed
- Straightforward tasks play to low-code/no-code and conversational RPA strengths
- Recording works great for simple data transfers and UI interactions
Determine the Need for Customization vs Ease of Use
- Coding allows endless customization but demands technical expertise
- Low-code/no-code deliver out-of-the-box functionality with some constraints
- Conversational and self-learning RPA optimized for usability over configurability
Consider How Often Processes Change
- Coded bots require more maintenance with process changes
- Low-code/no-code makes iterating easier
- Recordings must be re-recorded when flows evolve
Compare Implementation Timelines
- Coding takes weeks of development but handles complexity
- Low-code/no-code offers viable bots in days/weeks
- Recording provides scripts in minutes/hours
- Conversational and self-learning are nearly instant but limited
Here is a summary comparison of the programming approaches:
| RPA Programming Approach | Implementation Timeline | Ease of Use | Customization | Handles Complexity |
|---|---|---|---|---|
| Code-Based | Weeks/Months | Hard | Full | Excellent |
| Low-Code/No-Code | Days/Weeks | Medium | Moderate | Good |
| Recording | Minutes/Hours | Easy | Low | Fair |
| Conversational AI | Near-Instant | Very Easy | Low | Fair |
| Self-Learning | Near-Instant | Very Easy | Low | Fair |
And this decision flowchart sums up expert recommendations on when to use each approach:
[Insert decision flowchart image]The right programming technique depends heavily on your specific automation goals, team skills, and problem complexity. Try different approaches and measure outcomes to determine the best fit.
Now let‘s recap the key takeaways.
Recap and Additional Resources
The five RPA programming options to know this year include:
Code-based – Mature approach for developers to customize complex automations
Low-code/No-code – Speed development and open RPA to non-technical users
Recording – Quickly generate scripts as a starting point
Conversational AI – Enable plain English automation conversations
Self-Learning – Discover and automate processes autonomously
Consider developer bandwidth, process complexity, needed customization, and more when deciding between options. Blend techniques like recording and conversational bots with coding and low-code tools as a powerful recipe.
To take a deeper dive into RPA programming and tools, I recommend exploring these additional resources:
- Top RPA Tools Compared – Detailed overview of leading RPA software
- Hyperautomation – The next level beyond RPA with AI and more
- 24 RPA Use Cases – Real-world examples across industries
- RPA Implementation Guide – Best practices for enterprise rollouts
I hope this guide provides a helpful starting point to choosing the right RPA programming approach for your organization‘s needs. Reach out if you need any guidance or have questions!
