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Sai Vijayendra Madiga, Global Practice Lead AI

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“Agentic AI isn’t about replacing people. It’s about removing the bottlenecks around them so decisions move faster, outcomes get better, and the business runs smarter.“

Sai Vijayendra Madiga, Global Practice Lead AI, Roboyo

Every day, we hear questions like:

• “What’s the actual difference between RPA, AI Augmented Workflows, AI Agents, and Agentic Automation?”
• “Can this actually do what people say it can?”
• “Where do I start to see real ROI, not just more dashboards?”
• “If a human still has to review it, does it even save time?”

This guide will break down what each technology is (in plain language), where it fits in the real world, and when you should use it.

We’ll also walk through a real case study to show how everything works together, step by step.

First, What Are We Even Talking About?

RPA – Robotic Process Automation

What it does: RPA automates repetitive, rule-based tasks. It clicks, types, copies, and pastes just like a human but faster and without getting tired.
How it works: You tell it exactly what to do, and it follows that script perfectly. No thinking, no guessing.

Example:
Every time an invoice comes in, someone downloads the PDF, pulls the numbers, opens the finance system, and enters the data.
With RPA, a bot does all of that automatically.

Best for:

• Manual tasks
• Forms processing
• Data migration
• “Click-heavy” work across systems

Artificial Intelligence

What is it?

Artificial Intelligence (AI) is when machines are designed to think and learn like humans.

It allows systems to analyze data, recognize patterns, make decisions, and continuously improve performance just like humans do.

Why use AI in your business?

AI helps organizations save time, reduce costs, and make smarter decisions by automating repetitive tasks and uncovering insights from data.

It also empowers the workforce by acting like an intelligent assistant taking over redundant, manual work so teams can focus on strategic initiatives, creative problem-solving, and faster execution.

We use AI in our day today activities: –

• ChatGPT – An AI-powered conversational assistant that helps with writing, brainstorming, coding, learning new topics, and answering questions in natural language
• Google Maps – Uses AI to suggest the fastest routes by analyzing real-time traffic.
• Voice Assistants (e.g., Siri, Alexa, Google Assistant) → Understand and respond to spoken commands using natural language processing.
• Netflix / YouTube Recommendations – AI suggests shows or videos based on your viewing habits.

AI Augmented Workflows

What it does: AI looks at data, spots patterns, and makes predictions in the process automations, thereby augmenting the processes.

This means AI helps systems work smarter by identifying what needs attention, where it should go, and how quickly it should be handled, leading to better decisions and faster outcomes so your business runs more efficiently.

Example:
A company wants to know which customers might leave soon. AI looks at past behavior like logins, support tickets, and buying trends, and flags the ones most likely to churn.
But a human still needs to decide what to do about it.

Best for:

• Image or text recognition
• Forecasting
• Recommendations
• Risk scoring

AI Agents – The “Decision-Maker”

What it does: AI Agents are a piece of software that autonomously acts (takes action on its own) based on a goal. It decides what to do based on what it sees and follows through. It can coordinate multiple steps across systems without waiting for human approval at every turn.

Example:
Let’s say AI predicts a customer might churn.
Agentic AI doesn’t just flag it. It creates a tailored retention offer, sends it automatically, and updates the customer’s journey in your CRM.
If the customer responds, the agent updates the plan. If they don’t, it escalates to a human.

Best for:

• Workflows with frequent decision points
• Processes that need constant adjustment
• “If this, then that” logic with variation
• Scaling expert-like decisions without human involvement at every step

Agentic Automation – Agentic AI Put into Action at Scale

What it does:
Agentic Automation is when AI Agents, Robots and Humans come together to solve real challenges for customers. It doesn’t just make a decision, it also carries it out and adjusts based on what happens next.

Think of Agentic AI as the brain that says, “Here’s what we should do.”
Agentic Automation is the system that says, “It’s already done, and I’ve adjusted it based on what changed.”

Example:
Agentic AI decides a delivery will be late and needs rerouting.
Agentic Automation sends the updated shipping request, notifies the customer, adjusts the delivery window, and logs the changes in the system.

Key difference:

• Agentic AI is about smart decisions
• Agentic Automation is about smart decisions and smart execution

Best for:

• Complex workflows with lots of moving parts
• Tasks where timing and response are critical
• Situations where human involvement slows things down unnecessarily

Real Talk: Do I Actually Need Agentic AI or Automation?

If your business is drowning in manual work and no one has time to think, RPA helps. If your team struggles to turn data into action, AI helps. If your processes slow down because decisions are stuck in people’s inboxes, Agentic AI and Agentic Automation bring the real value.

They help speed up human decision-making by automating the steps between thinking and doing. They don’t remove people. They remove the bottlenecks around them. A human is still in the loop, but now they’re overseeing and guiding, and not clicking and chasing. That’s the real unlock.

Where Do You Start?

Not all AI fits every problem and that’s the point. The diagram above maps where AI Agents deliver the most value based on complexity and risk. If the task is repetitive and predictable, rules-based automation (like RPA) is still the best option. But if the use case requires constant decision-making without high risk, that’s where AI Agents shine. For complex, high-stakes scenarios, a cautious, research-driven approach is essential. The chart below translates this into a simple decision guide to help you choose the right starting point based on your business pain points.

Here’s a simple guide based on your pain points:

Use Case Walkthrough: RPA, AI, Agentic AI, and Automation in Action

Company: Global Retail Manufacturer
Problem: Forecasting cash flow was slow and unreliable. Manual steps, disjointed data, and outdated reports led to poor planning and delayed action.

Step 1: RPA
Pulled financial data from multiple systems daily. Standardized and fed into a central dashboard. Manual effort dropped by 85 percent.

Step 2: AI Augmented Workflows
Analyzed trends, flagged risks, and predicted shortfalls. Forecast accuracy improved from 65 to 93 percent.

Step 3: AI Agents
Identified actions to prevent forecast issues, such as delaying payments. Created action plans and escalated only key decisions to finance leadership.

Step 4: Agentic Automation
Ran the entire forecasting process. It pulled data, analyzed it, took action, and adjusted in real time as new data came in.

Results:

• Over 20 hours saved per week
• Forecasting variance dropped from 35 percent to 7 percent
• Real-time visibility, faster decisions, and no more last-minute fire drills

Final Thought: You Don’t Need to Automate or Build AI All at Once

Start where the pain is real. Automate what slows you down, then grow from there. This is not about replacing people. It’s about helping them do what they do best while smart systems handle the rest. Start small, prove the value, and scale with confidence.

Need a Clear Roadmap?

If you’re unsure where to begin or want someone to assess your AI & Automation readiness, let’s connect.

Need advisory or someone to assess your transformation needs to drive growth and remain competitive? Contact us today.

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