In a recent video from Monetizely titled "What is Agentic AI: The Future of Autonomous Workflows," Akhil, the presenter, offers a comprehensive explanation of agentic AI, distinguishing it from other forms of artificial intelligence and highlighting its practical applications for businesses. The video cuts through the jargon to deliver essential insights for executives and business leaders.
Beyond Jargon: Understanding Agentic AI
Agentic AI has become the latest buzzword in boardrooms and tech conferences, but what exactly does it mean? According to Akhil, the definition is refreshingly straightforward: "Agentic AI is artificial intelligence that can act on its own, not just give you information, but actually take action to help you accomplish a goal."
This distinction is crucial. While generative AI can create content or provide suggestions, agentic AI takes autonomous action. As Akhil puts it: "You are no longer just getting suggestions from AI. You are able to delegate real tasks."
The analogy he uses clarifies this evolution perfectly:
- Traditional software is like a calculator: input numbers, get results
- Generative AI is like a brilliant assistant who can write or explain things when asked
- Agentic AI is like "hiring a virtual employee. You give it a goal, it figures out how to get it done, and it keeps working in the background while you focus on something else."
How Does Agentic AI Work?
The functionality of agentic AI follows a four-step process that Akhil outlines:
- Perceive: The AI gathers information from systems it has access to—"calendars, emails, CRM, websites, APIs, databases, wherever the data lives."
- Reason: It breaks down your request into actionable steps. For example, "reschedule the meeting becomes: check who's invited, find new times, send messages, and track replies."
- Act: This is where agentic AI truly differentiates itself—"The AI doesn't stop at suggesting what to do, it actually executes. It makes changes, sends messages, updates records, triggers workflows."
- Learn: "Finally, it observes what happened. Did the action succeed? Was there an error? Did people respond positively? It adjusts next time based on what it learned."
This cycle creates continuous improvement, with the AI becoming more effective through experience. As Akhil notes, it "gets smarter, not just by reading more, but by doing more."
Real-World Applications Across Industries
Agentic AI is already transforming operations across multiple sectors:
Customer Service: "Agents can now go beyond chat responses. They can process returns, issue refunds, update the CRM, and notify customers all without human involvement."
Legal: "Companies like Harvey AI have built agents that draft contracts, manage redlines, research legal precedents, and even recommend negotiation points."
Finance: "Agents can review transactions, flag anomalies, and prepare audit-ready reports, reducing weeks of manual work to minutes."
HR: "Agentic AI can onboard new employees, schedule sessions, send policy documents, track form submissions, and escalate any delays."
The key difference in all these applications is that "we're not talking about tools that help humans work faster. We are talking about AI that does the work itself."
Strategic Implications for Business Leaders
For executives, agentic AI represents a fundamental shift in management approach. As Akhil explains, "You are not just managing people anymore. You will soon be managing teams of AI agents alongside people."
This raises several strategic questions:
- What tasks should be delegated to agents?
- How do you monitor what they're doing?
- What's the ROI of replacing manual processes with digital labor?
- How do you ensure agents follow rules and regulations?
"These are strategic questions," Akhil emphasizes. "They are not about choosing a tech vendor. They are about reimagining your operations. Agentic AI is not a plugin. It is truly a paradigm shift."
Identifying Genuine Agentic AI Solutions
With the inevitable marketing hype surrounding any new technology, Akhil provides five criteria to identify truly autonomous AI:
- Goal-oriented: "Real agents operate towards clear objectives, not just prompts."
- Multi-step capability: "They can plan and execute sequences, not just single actions."
- Tool use: "They can't just talk. They integrate with APIs, databases, and other softwares."
- Statefulness: "They remember what's happened so they can adjust, retry, and even optimize."
- Autonomy: "They don't wait for you to tell them every step within the boundaries you have set."
If a solution meets these criteria, "it is definitely worth a deeper look."
Why Now? The Technology Has Finally Caught Up
The current surge in agentic AI development is no coincidence. As Akhil explains, "Large language models gave us reasoning. Open APIs gave us access. Now businesses are realizing they can build autonomous workflows, not just dashboards."
The benefits are compelling: "Faster operations, lower costs, 24/7 execution, and in some cases, entirely new business models." He points to a particularly striking example: "Deploying 50 AI agents for the cost of one employee. Not science fiction, already happening in legal research and real estate."
Major tech companies are all moving in this direction:
- "Salesforce launched its agent platform in 2024"
- "Microsoft is embedding agents into Office and Teams"
- "Google's Gemini 2.0 is built for what they call the agentic era"
Getting Started with Agentic AI: A Five-Step Approach
For executives looking to implement agentic AI, Akhil recommends a methodical approach:
- "Pick one process in your business that is repetitive but rule-based."
- "Ask yourself, if an employee could do it with access to tools and instructions, could an agent do the same?"
- "Pilot a solution. Test one agent in one workflow."
- "Measure the result, not just speed, but reliability, cost, and satisfaction."
- "Build governance from the start. Who supervises the agent? How it logs its actions and what it can and can't do."
The key is starting small but deliberately. As Akhil warns, "Soon your competitors will have digital workers on their teams, and they will be moving faster with lower overhead and 24/7 execution."
The Future of Work: Augmentation, Not Replacement
Akhil concludes with an important perspective on the role of agentic AI: "Agentic AI is not about replacing everyone. It is about scaling capability. It is about delegating to digital workers what doesn't need to be done manually anymore, so your human team can focus on what truly matters."
For business leaders, understanding and adopting this technology now puts you "ahead of the curve, and that curve is coming very fast." As Akhil concludes, "if this is your first time hearing about agentic software, it won't be your last."