The AI Revolution No One Wants to Talk About
The enterprise software world is buzzing with AI promises. Every B2B vendor’s website proudly proclaims how their AI agents will boost productivity and enhance worker efficiency. But there’s an uncomfortable truth lurking beneath the surface—one that sales pitches carefully dance around.
Let’s be real: AI isn’t just about making workers more efficient. It’s about eventually replacing them.
Imagine being able create and then dismiss “employees” as needed throughout the quarter, the week or even the day. No more worries about over or under staffing because you always have the right number of agents on hand to handle the workload.
A Thought Experiment
Here’s a scenario to consider. Let’s suppose for a moment that it costs the same to employ a human order taker and an AI order taking for a given month. Most managers are still going to choose the human. Let’s throw in some variables. What if the AI agent can process orders with a marginal error rate that is 50% less than the human? That makes the decision more difficult. A human worker, at the top of his game is still roughly 25% more inefficient due to distractions, meetings, double checking work, sick days, etc. We are used to that as just as just a cost of doing business.
What if the AI agent could process twice as many orders in the same period as the human? Does the decision to replace that worker get easier? What if you can replace a whole call center of order takers with AI agents while maintaining just a few humans for those edge cases the AI can’t account for?
The Reality Check
As someone deeply embedded in the B2B space; having developed enterprise software and as a high-level executive in non-tech industries (CPG, business equipment), I’ve watched the narrative unfold. The current marketing speak is careful, calculated, and completely misleading. No software vendor wants to walk into an executive’s office and say, “Hey, implement our AI solution, and you’ll be able to fire half of your team!” But that’s exactly where we’re headed.
However, the real transformation will begin when AI can replicate human judgment at a high level—when it can think like an owner or key managers. And here’s where it will get interesting for your workers. But that’s not what your Salesforce, Oracle and SAP AI agents are designed to do today.
The Problem with Current Enterprise AI
Most enterprise software developers have a blind spot. They’ve never run multi-million dollar operations outside of software. They haven’t lived through the daily chaos of:
- Managing inventory in real-time
- Allocating orders based on unwritten customer preferences
- Making strategic decisions with imperfect information
Just to name a few.
Let me share a real-world scenario that highlights this complexity.
The Free Shipping Dilemma
Imagine this (non-enterprise software company): Your top salesperson comes to you with a request from a key account—they want free shipping on one particular order. Sounds simple, right? Wrong.
This single decision branches into multiple scenarios:
- If it’s a marquee customer, you might have to eat the cost regardless
- If you know they need the product more than you need the sale, you might hold firm (interesting: how would you know their need level?)
- If it’s month-end and you’re below target, you might cave but try to upsell
- If cash flow is tight, you might offer free shipping in exchange for faster payment
There are probably another dozen branches, but you get the picture. Each scenario involves dozens of unwritten variables that most AI systems today can’t begin to comprehend.
The Knowledge Gap
Current enterprise AI solutions proudly advertise their ability to “generate quotes with a few keystrokes.” But here’s what they’re missing: in most sales quote approvals, there are countless additional factors that exist nowhere else in the company’s knowledge base. They live exclusively in the heads of owners and key managers.
This is what we call “institutional knowledge,” and it’s the missing piece that makes current AI solutions inadequate for true decision-making.
The Path Forward
At CRSTBL, we’re tackling this challenge head-on. We’ve mapped out more than 200 variables that influence B2B decision-making, but identifying them was just the start. Our breakthrough comes in the form of “decision” agents—AI specifically designed to capture and replicate the collective wisdom locked away in our clients’ teams. Think of it as digital DNA sequencing for business knowledge—we’re not just recording decisions, we’re capturing the intuition, experience, and unwritten rules that drive them. These agents learn to think like your best performers, matching both the practical knowledge and the subtle instincts that make your team exceptional. These decision agents will sit on top of workflow agents to truly complete any business workflow.
Building AI that can handle this complexity isn’t just a technical challenge—it’s a data science mountain to climb, made even steeper by a crucial talent gap. The reality is that you need people on your product design and engineering teams who have actually sat in those high-level executive chairs, who have made million-dollar decisions under pressure, who have felt the weight of quarterly targets on their shoulders. Look around at the major ERP and CRM software companies today—how many of their product teams are staffed with former COOs, Operations VPs, or Supply Chain executives? Not many. And that’s the missing technological link that most enterprise software vendors will have a hard-time bridging.
The Inevitable Choice
Here’s the stark reality: AI will soon automate most day-to-day functions. As an owner or executive, you have two choices (and a third non-choice):
- Spring it on your team at the last minute to pick the survivors (picture Heath Ledger’s Joker throwing weapons on the ground for an “audition”).
- Plan a thoughtful transition, repositioning people toward tasks AI won’t immediately replace.
- Nothing. Don’t invest in AI and hope your competition won’t either.
The Bottom Line
The AI revolution in enterprise isn’t just coming in the next few years—it’s here. Once CRSTBL releases our first production AI “decision” agents before the end of this year, the only questions are when and how you will handle this transition.
As business leaders, we need to start having honest conversations about this reality instead of hiding behind marketing speak about “enhanced productivity.”
The choice is coming, and it’s coming soon. How will you prepare?
This article is based on real-world B2B experience and observations from the enterprise software industry. The views expressed reflect the current state of AI adoption and its implications for the future of work.