The Future of RPA is Not a Better Bot. It’s No Bot at All.

For the past few years, the promise of Robotic Process Automation (RPA) has been seductive: a digital workforce that works 24/7, never makes mistakes, and costs a fraction of a human employee. IT and Finance leaders bought into this vision by the millions (if not billions).

But the reality has been different. Instead of a set-it-and-forget-it workforce, organizations found themselves bot-sitting. They discovered that bots are brittle- breaking every time a web portal changes its CSS or an API updates. They found that scaling was exponentially difficult, leading to a maintenance nightmare where every dollar saved in labor was spent on technical debt.

Now, legacy vendors are selling a new vision for the future of RPA. They argue that by adding more layers- OCR tools, IDP add-ons, and separate AI chatbots- they can patch the holes in the sinking ship. This is the Frankenstack approach: a complex, expensive, and fragile web of technologies glued together to keep yesterday’s bots alive.

This article explores a different vision. The real future of robotic process automation isn’t about making bots slightly smarter; it’s about moving past bots entirely. We are entering the era of Agentic Process Automation.

Agentic automation, powered by Generative AI and managed in plain English, delivers what RPA promised but never achieved: true end-to-end process autonomy. It eliminates the brittleness of scripts and turns the future of RPA from a maintenance headache into a resilient, accessible reality available today.

The Frankenstack Fallacy: Why Patching RPA Won’t Work

To understand where we are going, we have to look at why current RPA trends are misleading. Major vendors are predicting a future where RPA is hyperautomated or cognitive.

• The IBM View: They argue that traditional automation has reached its limit and the future lies in autonomous enterprises driven by decision velocity.
• The Blue Prism View: They suggest the future is about orchestration and unified workforces, combining human and digital workers.
• The NICE View: They focus on attended automation, effectively admitting that bots can’t work alone and need constant human hand-holding.
• The Hyland View: They position RPA as merely a feature of content services, burying it deep within document management silos.

While these RPA predictions sound advanced, they all rely on the same flawed foundation: the script-based bot.

When you buy a legacy RPA tool today, you aren’t just buying a bot. You are often told you also need an IDP tool to read documents, a separate NLP tool to understand emails, and a Python script to handle the logic. This Frankenstack is inherently fragile. If one piece updates, the whole chain breaks.

The future of RPA technology cannot be built on this house of cards. It requires a unified platform where the brain (the AI that understands) and the “hands” (the automation that acts) are one and the same.

Enter Agentic Process Automation: The True Future of RPA

If RPA is the digital hands and AI is the digital brain, the industry has historically kept them severed. You had smart AI that couldn’t do anything (like a chatbot) and dumb bots that could click things but couldn’t think.

The true future of RPA is Agentic Process Automation. An agent is not a bot. It is an intelligent, autonomous entity that can plan, reason, and execute complex workflows from start to finish.

1. English as Code: Eliminating the Translation Gap

The biggest failure of RPA was that it required low-code or proprietary scripting languages. This meant business users (Finance, Accounting) had to rely on developers to build automations. When the process changed, the business had to wait for IT to update the script.

In the Agentic future, the interface is plain English. Kognitos pioneered the concept of English as Code.

• Old RPA Script: Click element ID #btn-submit > Wait 500ms > If Error Throw Exception.
• Agentic Future: “Log into the portal. Find the invoice ending in ’99’. If the amount is under $500, approve it. If not, ask the CFO for approval.”

Because the automation is written in the language of the business, there is no “translation loss.” The future of RPA technology is transparent. The code is the documentation.

2. Resilience by Design: The End of Bot-Sitting

RPA bots are deterministic but dumb. If a button moves five pixels to the right, the bot crashes. This brittleness is why maintenance costs consume up to 50% of total automation budgets.

Agentic automation uses Generative AI to handle exceptions. It doesn’t look for pixel coordinates; it looks for intent.

• Scenario: A vendor changes their invoice format.
• RPA Bot: Fails immediately. Process stops. Ticket opened for IT.
• Agentic Automation: The Agent realizes the format changed. It pauses and asks a human: “I see the ‘Total’ field has moved. Is this the new total?” The human says “Yes.” The Agent proceeds and learns this for next time.

This turns the future of robotic process automation from a brittle, static script into a dynamic, learning system that gets stronger over time.

3. Unified Brain and Hands

In the legacy model, you needed OCR to read a document and a bot to type the data. In the Agentic model, the platform is unified. The same AI that reads the invoice understands the context, makes the decision, and executes the keystrokes.

This unification eliminates the Frankenstack. You don’t need five different licenses for five different tools. You need one platform that acts as a digital employee.

Use Cases- What the Future of RPA Looks Like Today

This isn’t science fiction. Agentic automation is already replacing legacy RPA in the most complex enterprise environments.

The Future of RPA in Banking and Finance

RPA in banking has traditionally been limited to simple data transfer tasks. The future of RPA in banking is about autonomous financial controls.

• The Old Way: A bot copies transaction data from a spreadsheet to a fraud detection system. If the data format changes, the bot breaks.
• The Agentic Way: An Agent reviews a suspicious transaction report. It logs into the customer’s account, reviews their history, compares the signature on a check to the one on file, and makes a preliminary judgment call to flag or clear the alert. It acts like a junior analyst, not a script.

Claims Processing and Insurance

• The Old Way: A bot waits for a standardized form. If a customer sends a handwritten letter or a blurry photo, the bot fails.
• The Agentic Way: The Agent reads the handwritten letter, understands the sentiment, cross-references the policy number with the mainframe, and drafts a response email for the adjuster to approve.

Supply Chain and Logistics

• The Old Way: Bots are scheduled to run at 2:00 AM to process orders. If a supplier sends an email saying “We are delayed,” the bot ignores it and processes the order anyway, causing a downstream disaster.

The Agentic Way: The Agent reads the incoming email about the delay. It understands the implication, pauses the order processing, and suggests an alternative supplier to the logistics manager.

The Strategic Pivot: How to Exit the Legacy Trap

For CIOs and Finance leaders, the question is no longer How do I fix my bots? but “How do I migrate to Agents?”

The transition requires a shift in mindset. You must stop thinking in terms of tasks (clicks and keystrokes) and start thinking in terms of processes (outcomes and decisions).

1. Stop Buying Point Solutions: Do not purchase separate IDP, Chatbot, and RPA tools. Look for unified Agentic platforms.
2. Demand Auditability: If the AI is a black box you can’t trust it. Demand English as Code so you can verify exactly what the automation is doing.
3. Focus on Exception Handling: The value of automation isn’t in the happy path (which RPA does fine); it’s in the exceptions. Choose platforms that handle exceptions gracefully through human-in-the-loop collaboration.

The RPA trends are clear: the era of the script is over. The era of the AI Agent has begun.