The Contact Center Is Dead: Long Live the Operations Layer
We have been lying to ourselves since, well, basically since forever. We placed customer support agents into a padded room called the “contact center,” handed them a ticketing system, and told them to keep the angry people away from the rest of the business. We tracked average handle times; we cheered when a routing algorithm saved a fraction of a second; and we pretended that managing an interaction was the same thing as solving a problem. Deflecting an issue was the holy grail. That era is over. The walls of the contact center have been blown wide open, and the debris is currently raining down on the CRM and operations landscapes. The market is shifting from asking the question “who can capture the ticket best?” to “who can actually resolve the problem fastest?” Which is an entirely different category of question. And far more meaningful. And as Cameron Marsh from Nucleus Research so accurately pointed out in our recent CRMKonvo, that is a much nastier, much more complex place to compete. TL;DR If you want to watch the full CRMKonvo, please go ahead here (optimized for smartphones) or here (optimized for tablets/computers). Else, be my guest and continue to read. Or feel free to do both … The Illusion of the “Smart Ticket” Let’s just be absolutely clear from the start: nobody wants a ticket. A ticket is simply a formalized receipt of failure. It is documented proof that a product broke, a service failed, or a user interface was too clunky to navigate. For years, many vendors, including specialists like Zendesk, Freshworks, and others have built success around...
Agentic Commerce: A Genuine Paradigm Shift or Just Another Vendor Pitch?
The e-commerce industry has been pushing the exact same shopping cart down the exact same digital aisle for the better part of two decades. We have endlessly debated the optimal color for a checkout button. We have deployed massive Customer Data Platforms (to track users across the web. We have implemented traditional Customer Relationship Management tools and a full-on MarTech stack to send personalized emails that usually find a direct way into the spam folder. Yes, despite all this expensive digital plumbing, the average conversion rate stubbornly hovers around a meager two percent. Enter the industry’s latest shiny toy: agentic commerce. The vendor pitches are certainly alluring. We are moving away from the tedious “click and wait” era into a frictionless “talk and buy” reality. On the surface, it sounds like a massive leap forward. However, any technology analyst worth a grain of salt must ask the difficult questions. Is this actually revolutionary, or is it just a database update with a new coat of paint? Are we solving a genuine consumer friction point, or is this just a solution looking for a problem to help a vendor’s stock price? TL;DR If you rather want to watch the CRMKonvo, find the mobile optimized version here and the tablet/laptop version here. Or feel free to read on. Or do both. The Death of the Traditional Search Bar Raj Balasundaram, founder and CEO of agentic Commerce vendor Bayezon AI identifies a fundamental shift in consumer behavior. The traditional search engine model is dying. For years, the standard consumer journey has been a repetitive four-step process. You type a query into a...
The Uncomfortable Truth About Enterprise AI in 2026: It’s Not Intelligence, and That’s a Problem
As enterprises scramble to deploy AI, the Great AI Debate’s eighth installment reveals a widening gap between what vendors are selling and what actually works at scale. Dr. Michael Wu and Jon Reed spent this episode cutting through the hype around language models, domain expertise, and the financial reality of building sustainable AI systems; and they didn’t pull punches about where the field is failing. TL;DR If you want to watch the full CRMKonvo, please go ahead here (optimized for smartphones) or here (optimized for tablets/computers). Else, be my guest and continue to read. Or do both … The Domain Expertise Imperative: Correlation is Not Causation One of the most dangerous, and frankly lazy, narratives pushed by AI maximalists is the idea that artificial intelligence negates the need for deep domain expertise. This is a fundamental misunderstanding of how these models work. As Dr. Michael Wu frequently points out, almost all machine learning and AI systems today are built using supervised or reinforcement learning. They are, at their core, sophisticated correlation engines. They do not understand causality. They can surface 50 variables that move together, but they cannot tell you whether A causes B, B causes A, or if a hidden confounding variable C is responsible for both. If an LLM correctly states that smoking causes cancer, it is not because it understands the biological mechanisms of cellular mutation; it is because it has been fed enough human-generated text asserting that relationship. It creates the illusion of causal reasoning without the substance. This is precisely why domain experts, whether in healthcare, supply chain logistics, or financial services, are more vital...