When talking about AI, I often hear the same question:
“Which model should we standardize on?”
But model choice is the least durable part of your AI strategy.
On any given week, I’m rotating between ChatGPT, Claude, Gemini, Grok, and Copilot. Different models are better at different tasks, but that’s only the reality today.
This advantage is temporary.
The models are slowly creeping up toward each other. In a couple of years, any of the major models will likely be “good enough.”
So if your strategy is “bet the company on a model,” you’re betting on something that won’t stay true long enough to matter.
The model isn't the differentiator. The workflow you've built around AI is.
Thanks for reading,
Robbie Allen
Founder & Managing Director
Automated Consulting Group
PS: If you’re thinking about rolling out AI across functions, hit reply with one workflow you want to automate. I’ll share the evaluation and guardrails pattern we’re using with clients to ship safely and avoid tool churn.
Key Takeaways:
• Model advantage is temporary. Today, different LLMs perform differently by task. Over time, performance converges and “best model” matters less.
• The moat is workflow, not vendors. Data access, governance, and repeatable processes compound. Model choice does not.
• Strategy shifts from prompts to processes. The winning org can swap models without rewriting how work gets done.
The Problem with Model Chasing
There’s a real reason people keep asking which LLM is best.
Right now, the differences can be felt. You can get a slight edge by routing the right task to the right model, but edge is not the same thing as strategy.
Model chasing gets you:
Procurement debates
Constant retraining
Teams building one-off prompt tricks
A fragile stack that breaks every time the vendor landscape shifts
It turns AI into a recurring distraction instead of a compounding capability.
And when leadership treats “pick the model” as the plan, the organization gets stuck in a loop:
Choose → Pilot → Switch → Rebuild → Repeat.
That’s not transformation. That’s tool churn.
What Actually Compounds: Your Workflow
The real moat is "boring." What actually compounds is:
1. Data access that doesn’t depend on heroics
If your AI workflow can’t reliably pull the right context, you’ll get junk output no matter how good the model is.
Models don’t fix missing data. They just sound confident while guessing.
2. Governance people can live with
Not “we wrote an AI policy once.”
I mean structured guidelines:
What data is allowed
What isn’t
What gets logged
Who reviews outputs
How you handle mistakes
If you can’t explain it to an auditor or your board, you don’t have governance.
3. Repeatable workflows
The goal isn’t “AI can do X.” The goal is “this process runs every day with predictable quality.”
That’s the shift that builds your AI moat: from prompts to processes.
Start with One Workflow
If you’re leading technology, data, or the business, here’s the practical move:
Pick one workflow with 3 traits:
It happens frequently (weekly or daily)
It has a clear output (a decision, a document, a ticket, a summary)
A human already reviews it (built-in safety net)
Then do the unglamorous work:
Define the input sources (what systems, what data, what permissions)
Define the guardrails (what’s off-limits, what must be logged)
Define the quality bar (one metric: speed, accuracy, cycle time, cost)
Design the loop (where a human approves, edits, or escalates)
Once that’s solid, just plug in the model. When it becomes outdated, plug it out, plug the new one in, and your workflow won't change.
The Takeaway for Leaders
The path forward isn’t picking the “right” model, but redesigning how work gets done so the model becomes interchangeable.
That means you build workflows with: reliable data access, clear guardrails, and a repeatable loop.
If you do that, model convergence stops being a threat and becomes a benefit: you can swap vendors without rewriting your operating system.
And with that in mind, I’m curious:
If model selection becomes a rounding error, how does that change what you prioritize this year - procurement decisions or workflow redesign?
Let me know if you're stuck on the fence between a new model and workflow restructuring.
– Robbie