Beyond The Script: How Agentic AI Is Making Customer Support Feel Human Again
Most people still associate AI in customer support with clunky chatbots and keyword-based replies. Agentic AI is something else entirely.
By Apurv Agrawal
A decade ago, customer conversations looked and felt very different. Contact centres were centralised, scripts were printed on paper, and long hold music was played for "customer experience." That era was built for efficiency, not for humans. But over the years, something shifted.
Across millions of minutes of support and sales calls and observing the arc of how service technology evolved, it became clear: the best experiences aren’t scripted, they’re contextual, natural, and quietly effective. That belief eventually led us to what’s now referred to as agentic AI.
For businesses, this means more than cost savings or faster turnarounds. It means consistently delivering service that feels informed, intentional, and surprisingly human, even at scale.
What Is Agentic AI, Really?
Most people still associate AI in customer support with clunky chatbots and keyword-based replies. Agentic AI is something else entirely.
Think of it not as a tool but as a virtual team member. It works across systems, detects context, executes entire workflows, and learns from every interaction. In practice, that means fewer transfers, resolutions at a pace and conversations that make sense.
Consider this: A traditional chatbot might escalate a billing issue. A basic AI assistant might pull up the transaction history for a human to review. But Agentic AI? It not only verifies the charge but also identifies the mistake, processes the refund, updates the CRM, and confirms the fix. Also, all of these tasks are executed autonomously.
Why Going Agentic Matters
As AI has matured, three benefits of this approach have stood out:
- Proactive care: Agentic systems don’t just respond. They anticipate. A delay in shipping can trigger a real-time ETA update. A failed payment can prompt a retry suggestion before the customer even asks.
- Single-touch ownership: Nobody likes repeating themselves. Handing over the entire workflow, from context to resolution, removes the need to escalate or retell the story. Average resolution time drops, satisfaction improves.
- Humans focus on nuance, not routine: When repetitive tasks are handled by machines, human agents get to do what they’re best at: solving edge cases, showing empathy, and retaining frustrated users. It's better for the customer, and better for morale.
What It Takes to Make Agentic Work
It’s easy to underestimate how much infrastructure sits behind a seamless AI interaction. Three foundational layers keep surfacing:
- Unified data layer: AI is only as good as the context it can see. Fragmented order systems, CRMs, and ticketing platforms lead to shallow responses.
- Human-in-the-loop feedback: Even the best models hit edge cases. A structured way for human agents to intervene and feed learnings back is critical to improving accuracy and trust.
- Guardrails for tone and compliance: Agentic AI can act, but it must also sound right and behave responsibly. Real-time policy checks, tone guidelines, and approval workflows ensure consistency.
Scaling Support Without Losing the Human Touch
According to the McKinsey report, firms can expect productivity gains of up to 45 per cent by integrating generative AI in customer care. However, the real impact of agentic AI isn’t just in cost savings. It’s in maintaining service quality while scaling operations.
Leading organisations now use agentic AI to:
- Triage incoming queries and route them accurately.
- Handle repetitive issues like order tracking or account updates.
- Surface insights that improve product and service offerings.
- Support teams with historical data and response templates.
The outcome is a system where customers feel heard and supported, and agents are freed up to focus on strategic plus high-empathy tasks.
Is It the End of Human Support? Not Even Close
One of the most common misconceptions is that agentic AI will replace human agents entirely. But the most successful implementations prove the opposite by following a simple maturity ladder:
- Assist: AI suggests actions or drafts responses; humans approve.
- Automate: AI handles repetitive tasks end-to-end.
- Agentic: AI owns the full workflow and only pulls in humans when needed.
The New Standard for Customer Support
Legacy systems are optimised for efficiency; agentic AI is designed for experience. As customer expectations evolve, so too must support models.
In a world where 35 per cent faster resolution and 50 per cent lower support costs are possible, the question isn’t whether to adopt agentic AI but about how quickly it can be integrated without losing the brand’s voice. It's not about replacing people. It's about removing the grunt work, so humans can do what only humans can.
Support that once felt like an afterthought now has the power to become a competitive edge. And in the end, that’s what smarter tech and kinder calls are really about: making every interaction count.
(The author is the Co-Founder & CEO of SquadStack)
Disclaimer: The opinions, beliefs, and views expressed by the various authors and forum participants on this website are personal and do not reflect the opinions, beliefs, and views of ABP Network Pvt. Ltd.
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