Agentic AI
Jun 19, 2025
Deepak Singla
IN this article
In this blog, we break down the difference between "AI agents" and "agentic AI," why it matters for tech leaders, and how to identify true agentic systems vs. glorified chatbots. We also explore how companies like Fini are quietly leading the way with agentic AI that actually works at scale.
Introduction: Beyond the Buzzwords
AI is evolving fast, and so is the terminology. One of the most misunderstood distinctions in 2025 is between AI agents and agentic AI. While many vendors use the terms interchangeably, there's a crucial difference CIOs, CTOs, and customer experience leaders must grasp to avoid overpaying for basic automation and underinvesting in systems that actually scale.
The TL;DR:
AI Agents = Tools that execute tasks based on narrow instructions
Agentic AI = Systems that autonomously reason, learn, and orchestrate tasks across multiple tools and goals
Let’s unpack this with real-world implications.
AI Agents: The Specialized Task Runners
AI agents are essentially point solutions. Think of them as glorified macros or rule-based workflows powered by large language models (LLMs). They're good at:
Resolving a specific type of ticket (e.g., password reset)
Fetching data from a backend system
Responding to pre-trained FAQs
But they're limited because:
They don’t have persistent memory
They don’t self-reflect or improve
They can’t chain actions intelligently
Example: A Shopify AI plugin that answers "Where is my order?" by querying the shipping API. It’s helpful, but rigid.
Agentic AI: The Autonomous Reasoners
Agentic AI, on the other hand, is a framework for building goal-oriented systems. It combines memory, reasoning, tool orchestration, and policy enforcement to:
Decompose goals into subtasks
Decide which tools or APIs to invoke
Sequence and adapt actions in real-time
Improve via self-reflection
Think: Not just answering “Where is my order?” but also checking for delays, issuing refunds, reordering products, and notifying the customer automatically.
Companies like Fini are building real agentic AI experiences that don’t just talk — they act.
Real-World Use Case Comparison
Scenario | AI Agent | Agentic AI (e.g., Fini) |
|---|---|---|
Refund request | Looks up policy, returns canned answer | Checks order status, triggers refund, updates ticket |
Multi-intent message | Confused or replies to one query only | Splits intents, executes each flow |
Escalation | Sends user to human | Tries fallback steps, then escalates with full context |
Feedback improvement | Manual reprogramming | Learns from flagged cases and updates flow logic |
Tool orchestration | One-to-one API use | Chooses from multiple APIs, executes in sequence |
Why This Matters for CIOs and CX Leaders
1. Don’t Buy a Chatbot in Disguise
According to CIO.com, vendors often sell basic chat agents wrapped in fancy words like "agentic." The reality? Most tools claiming autonomy are just calling a database or summarizing documents via RAG.
2. You Need Traceability and Safety
If your AI can initiate actions (e.g., send refunds, change user details), you need to:
Log decisions
Set policy constraints
Audit outputs
Agentic AI platforms like Fini offer these safeguards out of the box, with ISO 42001 readiness and built-in escalation layers.
3. The Future is Autonomous, But Incremental
Agentic AI doesn’t mean full Skynet autonomy on Day 1. Mature teams deploy in steps:
Start with read-only flows
Monitor and set guardrails
Gradually unlock autonomy per use case
That’s why Fini supports hybrid modes: observation, suggestion, confirmation-based action, and full autonomy.
Key Features of Agentic AI Systems
Persistent Memory: Remembers user history, preferences, and decisions
Goal-Oriented Reasoning: Not just reacting but solving problems
Multistep Planning: Executes subtasks across tools without human input
Self-Reflection: Learns from outcomes and adjusts behaviors
Autonomy Levels: Fine-tuned control over what the agent can or cannot do
Fini’s agentic loop enables all of this.
Vendor Checklist: How to Evaluate Claims
Feature | AI Agent | Agentic AI |
Task automation | ✅ | ✅ |
Autonomous planning | ❌ | ✅ |
Multi-API orchestration | ❌ | ✅ |
Feedback-based learning | ❌ | ✅ |
Memory beyond single chat | ❌ | ✅ |
Escalation with context | ❌ | ✅ |
No-code configuration | ✅ | ✅ |
Subtle, Real-World Agentic AI in Action: Fini
Fini is already deployed in 100+ enterprises. It doesn't just answer questions — it:
Detects intent ("cancel my account")
Checks policy compliance (eligibility)
Updates backend (Stripe, HubSpot, Zendesk)
Sends confirmations and logs actions
This is real agentic AI. And it works.
Final Thought: Don’t Get Washed
Much like "greenwashing" in sustainability, "agent-washing" is rampant in AI. Ask questions. Dig deeper. Demand:
Memory
Reasoning
Guardrails
Goal decomposition
And if your AI doesn’t do things? It’s not agentic.
Next Step: Book a Demo with Fini to see agentic AI in your stack.
Conceptual Understanding
1. What is the difference between AI agents and agentic AI?
AI agents are narrow-purpose tools designed to follow predefined instructions—like answering FAQs or pulling data. In contrast, agentic AI refers to systems that can dynamically reason, plan multi-step tasks, and act autonomously across tools. Agentic AI is defined by its ability to orchestrate actions, not just respond.
2. Are AI agents and agentic AI the same thing?
No. AI agents are parts of a system, typically built to complete a specific action. Agentic AI refers to an end-to-end architecture that uses these components intelligently to pursue broader objectives. For example, Fini’s platform leverages both—but the power lies in its agentic orchestration, not just the agents.
3. Why is agentic AI considered a more advanced form of AI?
Agentic AI combines multiple key capabilities: memory, planning, dynamic reasoning, orchestration, and feedback loops. These allow it to operate independently and improve over time, unlike reactive agents that require continuous manual configuration.
4. Can AI agents become agentic over time?
Not inherently. Turning an AI agent into a truly agentic system involves architectural upgrades like persistent memory, dynamic reasoning modules, tool orchestration frameworks, and compliance-aware execution—all of which are complex and foundational.
5. What makes an AI system truly ‘agentic’?
A system is agentic if it autonomously sets sub-goals, orchestrates tools, learns from outcomes, reasons across contexts, and operates with safety guardrails. Fini is an example of a system built with these principles in mind.
Technical Capabilities
6. Does agentic AI use memory differently than AI agents?
Yes. AI agents are usually stateless and don’t remember user interactions. Agentic AI uses persistent memory to track past interactions, recognize returning users, and maintain continuity, which is essential for personalization and auditability.
7. How does agentic AI perform multi-step reasoning?
It dissects user requests into logical components, plans sub-tasks in the right sequence, chooses tools to complete them, and adapts based on tool responses or user signals.
8. Can agentic AI personalize responses across users and journeys?
Absolutely. Agentic systems like Fini can access user attributes (e.g., subscription plan, last purchase, preferred language) and shape replies, escalation logic, and automation paths accordingly.
9. Is agentic AI better at handling multi-intent queries?
Yes. For example, if a user says “I want to cancel and get a refund,” agentic AI will split the request into two actionable flows, determine eligibility, and act—whereas traditional agents may miss the second intent entirely.
10. Does agentic AI support self-reflection or learning loops?
Yes. Systems like Fini analyze failed sessions, review escalation triggers, and update workflows or prompts automatically—closing the loop between execution and continuous improvement.
Tool Orchestration & Autonomy
11. How does agentic AI orchestrate tools across platforms?
It identifies which APIs or integrations are needed, triggers them sequentially or in parallel, evaluates the outcome, and chooses the next best step. This allows for autonomous resolution of tasks spanning multiple systems.
12. Can agentic AI act without human intervention?
Yes—but safely. Most platforms like Fini offer configurable autonomy levels: read-only, suggestive, confirmation-based, or fully autonomous. You can choose what level of trust to assign per workflow.
13. Is agentic AI compatible across different platforms?
It should be. Fini’s system, for example, integrates with Zendesk, HubSpot, Intercom, Shopify, Salesforce, and even internal APIs, allowing it to operate cross-stack.
14. Can agentic AI replace rigid automation workflows?
Yes. Instead of writing if-this-then-that logic for each edge case, agentic AI learns how to navigate workflows dynamically and adapts to inputs in real time.
15. Can agentic AI trigger backend systems conditionally?
Yes. Based on user profile, business logic, or previous responses, agentic AI can trigger one or more backend APIs and adapt its plan if something fails or requires escalation.
Trust, Guardrails & Security
16. Is agentic AI more error-prone than scripted agents?
Not if implemented with strong safety measures. In fact, agentic systems can reduce errors by understanding nuance and adapting when rigid flows break. Fini enforces 40+ guardrails to minimize hallucination and data risk.
17. How does agentic AI ensure policy compliance?
It operates with real-time constraints like input filtering, output validation, PII redaction, and scope-based execution. All decisions are logged and auditable.
18. What types of guardrails are standard for agentic AI?
Input sanitization, output filters, confidence thresholds, escalation rules, content classifiers (for offensive language), and access controls are all standard guardrails in systems like Fini.
19. Can agentic AI assist with ISO 42001 or GDPR compliance?
Yes. It logs all actions, supports reversible redaction, handles consent flows, and can surface explanations for automated decisions—helpful for audits and regulators.
20. Who controls the level of autonomy in agentic AI?
You do. Admins or CX leads can define exactly what agentic AI can or cannot do across different flows, customers, and even language regions.
Use Cases & Benefits
21. What are some high-value use cases for agentic AI?
Password resets, refund claims, subscription changes, loyalty credit errors, address updates, fraud checks, and onboarding flows are all high-volume use cases where agentic AI can deliver 80–90% automation.
22. How does agentic AI improve customer satisfaction (CSAT)?
By responding instantly, acting contextually, reducing misfires, and resolving without escalation—CSAT tends to increase by 20–40% in agentic deployments.
23. Can agentic AI scale to handle enterprise-level support?
Yes. Fini supports clients with over 50k+ monthly tickets, distributing logic across chat, email, and in-app channels using the same underlying reasoning engine.
24. What’s a real example of agentic AI in action?
Fini detects a failed card update intent, checks eligibility via your payment API, sends a secure link, verifies confirmation, and notifies the CRM—all in under 10 seconds.
25. Can agentic AI handle vague or ambiguous queries?
Yes. It will clarify meaning, prompt for missing information, or reroute to a fallback plan. If still unclear, it escalates with full context to a human agent.
Vendor Evaluation
26. How can I evaluate if a vendor really offers agentic AI?
Ask about persistent memory, tool orchestration, autonomous planning, safety guardrails, and configurability. If the system can’t perform all five, it’s likely just a chatbot.
27. What vendor claims are red flags?
Watch for vague language, lack of clear architecture, and overuse of terms like “agentic” when the system is really just querying a document database.
28. Why do some companies misuse the term ‘agentic AI’?
To ride the hype wave. CIO.com has reported on “agent washing”—marketing bots as autonomous systems when they’re not. Always ask for live demos and failure mode explanations.
29. Does agentic AI replace your support team?
No. It complements them by handling repeatable, rules-based queries and freeing up humans to focus on edge cases, retention, and escalation flows.
30. Is integration complex for agentic AI platforms?
With modern systems like Fini, integration is straightforward—requiring only API credentials and knowledge base access. Deployments often complete in less than a week.
Strategy & Future Outlook
31. Is agentic AI becoming the industry standard?
Yes. As complexity rises and user expectations grow, brands are moving away from linear workflows and toward adaptive, resilient systems like agentic AI.
32. Will agentic AI continue to evolve?
Definitely. The next generation includes multi-agent collaboration, real-time decision arbitration, and even outbound action-based workflows (e.g., upsells, reminders).
33. Will it replace customer support jobs?
No—but it will redefine roles. Expect AI to handle Tier 0–1, while humans step into coaching, QA, and complex customer advisory roles.
34. How does agentic AI learn post-launch?
It ingests feedback, detects repeat escalations, tracks flow fallbacks, and uses all this to self-improve—often weekly.
35. What’s next after agentic AI?
We’ll likely see collaborative multi-agent ecosystems with dynamic delegation, goal sharing, and negotiation. Fini is already investing in this direction.
Deployment & Maintenance
36. How quickly can a system like Fini go live?
Within 3–7 days for most teams. You connect your stack, choose flows, review the AI’s draft logic, and go live via a no-code builder.
37. Can I control which flows are autonomous?
Yes. Fini allows per-flow, per-user, and per-channel autonomy settings—so you stay in control of sensitive cases or segments.
38. What channels can agentic AI operate in?
Chat, email, SMS, mobile apps, and web widgets are all supported. Memory and logic persist across channels.
39. Do I need prompt engineers to manage it?
Not with a modern platform. Fini includes no-code prompt editing, flow logic settings, and prebuilt templates to launch confidently.
40. Where can I see agentic AI live in production?
Book a Fini demo and watch a live refund, password reset, or account closure flow run start to finish—without human input.
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