A few weeks ago, I ordered printer cartridges from Office Depot. Simple enough. But the payment didn’t go through correctly. So, I called, fixed it, and moved on with my day. Or so I thought.
A few hours later, I got another email: “Urgent issue with your billing address. Please call.” So, I called again. Same confusion. Same runaround. After the second call, I canceled the order and had Amazon deliver my cartridges the next day.
That’s not a story about rude reps or failed tech. It's a story about automation that can’t think. If they’d had Agentic AI: adaptive and context-aware technology, the issue would’ve resolved itself.
Agentic AI is the next phase of the evolution of AI. This is AI that not only follows rules but makes decisions. It pulls from multiple systems, recognizes past interactions, and takes action based on what it knows and not just what it’s told.
In a contact center, that could mean:
No more repeat calls for the same issue
No more “let me look that up” delays
No more friction that drives customers away
Agentic AI is able to take routine tasks from human agents and gives them time to focus on more complex, high-value interactions. For instance, AI can manage data entry and initial customer queries, while agents are freed up to provide more personalized support. This type of collaboration is great for efficiency and customer satisfaction.
I was recently asked how agentic AI differs from generative AI. The below table breaks down to nuances.
Where generative AI is great for brainstorming and content creation (at least at a very basic level – and hey – case-in-point: you still need humans to make the content sound...human), agentic AI is great for complex automation and adaptive problem solving. You don’t need to give agentic AI the exact workflow. With certain inputs, it can determine its own answers by looking at the information that exists and finding patterns.
Going back to my Office Depot example, this scenario highlights the limitations of traditional automation and underscores the potential of agentic AI. Traditional approaches – even with an generative AI interface - would not have the capability to resolve the underlying issue or adapt based on the context of previous interactions, alone.
An agentic AI system, on the other hand, could have recognized the repeated issue, possibly solved the issue from my transaction history or understood that I had already contacted support, and taken proactive steps to resolve the problem without requiring me to make multiple calls. It could have autonomously verified the billing information, corrected any discrepancies, and made sure the order was processed smoothly.
Those who have been reading my newsletters for a while know that I am all about tech integration and ensuring consistency across platforms, something that agentic AI makes possible. Whether a customer reaches out via phone, email, or chat it keeps a unified and consistent approach across channels.
This technology and its uses are not hypothetical – it’s already here and will soon (or already are) define the difference between brands that retain loyalty and those that lose it to Amazon.
Blue Orbit Consulting has been transforming contact centers for over 15 years. Interested in implementing new technology or AI tools into your customer service operation? Let’s talk.
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