Status Quo Won't Help Your Business Survive AI

When everyone runs the same model and ships the same deck, the only advantage left is the one you own.

Cookie-cutter Can Work, Within Limits, and with Enough Runway

We've been here before. Every wave of "everyone must adopt this now" technology starts by making companies look identical, and ends by rewarding the few who used that sameness as a floor, not a ceiling.

To see how this plays out, look at what happened the last time a technology promised to standardize the entire enterprise.

What we learned with ERPs

With the advent of ERP systems, every company temporarily looked the same.

Whatever functional area modules were purchased had the same screens, the same forms, the same back-end processing.

The beauty was the ease of flowing from one system to the next: marketing into sales, orders into inventory management and shipping then to receivables.

Every business’s functional area started out the same.

The differentiator was in the dropdown setups and the customizations.

Certain of the functional areas were so clumsy that standalone systems survived: Salesforce was one of them, Peachtree was not.

To earn efficiency, the price was a bit of commoditization and the cost of building customizations that preserved business value while capturing the benefits of "off-the-shelf."

Back then you had years to build those customizations. Now the window may be measured in months.

Commoditization was survivable because you could still build advantage on top of the standard — if you kept moving. The companies that died weren't the ones who adopted the standard. They were the ones who assumed the standard would protect them forever.

Statis is not a Business Strategy

Blockbuster thought its core business could not be touched. So did Blackberry. I still miss the haptic feel of my Blackberry, and the screen did not burn letters into it. But that is not enough to allow a product to survive.

Now the equivalent of ERPs is the armies of Big Four consultants with their reseller agreements with the proprietary LLMs, armed with the same LLM-generated decks, charging hundreds of thousands of dollars to homogenize and ship your business logic to the LLM vendors they are simultaneously commissioned by.

This is the Time to Figure Out What Makes Your Business Proposition Distinct

This is a good time for each business to really think about the value it creates for customers, what differentiates it, and how easy it would be to replicate that advantage.

If each consulting group uses the same LLMs and the same methodology and the same LLM-generated deck, what is there to differentiate your firm to give it the market advantage.

Do you know what that even is? If you don’t, someone is coming for your lunch. And the consensus, status quo, cookie cutter approach that works at the beginning cannot provide the strategic and tactical advantages without conscious thought and positioning.

The Solution

If sameness is the disease, ownership is the cure. You don't beat commoditization by buying the same tools faster than the next firm. You beat it by owning the four things no one can hand you: what your persistent and differentiated business offering is, where your intelligence runs, what your data means, and who it answers to.

Vested (and suited) interests won’t tell you. But I will.

Here's where I'd start.

1. Define your mission and your differentiator and how you'll defend it. Before you touch a model or sign an engagement, answer the hard question: what does this business actually do better than anyone else, for whom, and why? If you can't say it in a sentence, no LLM is going to say it for you. Your differentiator is not your tech stack. Everyone will have the same stack. It's the thing that would be genuinely hard for a competitor to copy: your relationships, your proprietary knowledge, your judgment, your data. Name it. Then decide, deliberately, how you will keep it. A differentiator you can't articulate is one you've already started losing.

2. Run sovereign AI, not rented cognition. Stop shipping your proprietary business to a frontier vendor and calling it a strategy. The moment your code, your customers, and your competitive logic leave the building, you've handed your differentiation to a model that will serve it back to everyone else. Sovereign AI, that is, private models running in a controlled, non-shared environment, means the intelligence works on your data without your data becoming someone else's training set. If it's truly your advantage, it doesn't belong on someone else's platform.

If you must choose frontier, make sure you can swap out to protect against the risk of a wayward model taking down your system in unexpected ways.

3. Own your semantic layer and your governance harness. This is the part nobody selling you a deck wants to talk about, because it's work. Your semantic layer is what your data means: the definitions, the entities, the business logic that makes "revenue" or "active customer" mean the same thing across Snowflake, Databricks, Salesforce, and your ERP. If you don't own that, you don't own your business; you're renting an interpretation from whoever built the pipeline. Pair it with a governance harness that controls what the data means, who can act on it, and what decisions it's allowed to support. It’s no longer a cost center. It’s no longer unquantifiable overhead. That's decision provenance, and it's the only thing that makes AI output auditable instead of merely confident.

4. Own your RAG and your structured data outside the cloud you don't control. Retrieval is where your real advantage gets encoded. If your RAG corpus and your structured data live inside a vendor's environment, then the thing that makes your answers yours is sitting on someone else's balance sheet. Bring it home. Keep the retrieval layer and the structured data that feeds it in an environment you govern, so the model reaches into your knowledge, under your rules, and the output can't be quietly reassembled somewhere else.

Notice what these four have in common: they are the things a reseller cannot resell. Anyone can license the same LLM. Anyone can generate the same deck. Nobody else can own your meaning, your provenance, and your retrieval, unless you give it away.

So before you sign the next engagement, ask the uncomfortable questions. Where does our intelligence actually run? Do we own what our data means, or does a pipeline own it for us? If we removed the vendor tomorrow, what would be left that's still ours? If you can't answer those cleanly, you don't have a differentiation problem, you have an ownership problem, and it's fixable.

This isn't about rejecting AI. I use it, I build with it, and I believe in it. It's about refusing to let the tool that's supposed to create your advantage quietly become the reason you no longer have one. Own your business differentiator, own the layer, govern the meaning, keep the retrieval. That's the difference between being the business everyone copies and being one of the five identical suits standing in line.