My oh my, LLMs are getting good. Have you seen GPT5? It delivers the latest and greatest capabilities, but an even more powerful model will surpass it within months.
LLMs are still relatively new, despite the power and opportunity they provide. It is completely understandable to find yourself in a position where you have a strong feeling that you should be able to leverage them but are unsure of how to do so. How can you use LLMs and AI to differentiate your business?
The answer is surprisingly human for a technical topic.
It’s a matter of knowledge and taste. Domain expertise and how it is expressed.
What does your business provide to its customers and why? Why would a customer prefer you over other options? What knowledge, best practices, and preferences does your business have that establishes your place in the market? Given your expertise and knowledge, why does your business make the choices it does, the way it does?
With AI, you can leverage knowledge and preferences to turn them into an engine for action tailored to your business. Those actions that the engine drives, whether customer-facing or internal tooling, are going to provide differentiation not from functionality or from the ‘what’ it does, but from the ‘how’ being aligned to your business. You gain advantages by moving quickly and putting soon-to-be-ubiquitous technology in place, but generic functionality won’t set your business apart. It is vital that the functionality be an extension of your specific understanding and approach.
This simple alignment of your specific domain expertise with your AI will ensure that you both obtain the maximum benefit from AI and that, as models improve, your functionality will improve proportionately.
But! Simple does not mean easy. That alignment requires understanding how AI works and how to best pair it with domain expertise and at what scope. Going too wide can be costly, slow, and ineffective. Going too narrow can mean not being able to scale with newer models. You’ll need to put in the time and see where the balance is, but the returns are well worth it. If your AI doesn’t express your expertise, you reduce it to a ChatGPT wrapper — and wrappers have no moat.
To build a moat, you need more than tools. You need translation. Translation of your people’s judgment, your processes, your subtle tradeoffs, and your “why” into something that an AI system can consistently express and scale. That does not mean hard-coding every decision. It means deliberately shaping the feedback loops, datasets, and guardrails so that the AI reflects your way of operating, not a generic default.
Think about it this way: every competitor can spin up a chatbot, automate a workflow, or deploy a recommendation engine. But when your AI consistently embodies the instincts of your top experts, delivers recommendations that reflect your risk posture, and responds to customers in a way that feels like you, that is when the technology stops being a commodity and starts being a moat.
The organizations that succeed here will treat AI not as a bolt-on feature but as a living extension of their strategy. They will continuously refine it as they learn, pair it with strong governance, and ensure the “taste” encoded into their AI stays sharp and distinct.
So, the question is not if you should use AI, it is whether you will invest the time and care to make it truly yours. Those who do will find themselves with an enduring competitive advantage, one that scales with every new model yet always flows from a foundation that only they possess.
At 7Rivers, we help organizations transform their domain expertise into AI-driven differentiation, building real moats, not wrappers. If you are ready to align AI with what makes your business unique, connect with us and let us start building your competitive edge.
