If a buyer asks an AI system for a recommended law firm in San Francisco for a complex litigation, technology, IP, competition, or investigations issue, the page does not make the decision any easier.
It lists services, but it does not position them.
It mentions sectors, but it does not define the buyer.
It has proof, but the proof is not tightly attached to the office, the lawyers, the practice areas or the problems being solved.
It has recognitions, but it does not explain why those recognitions matter to the person choosing a firm.
It has a key contact, but no strong commercial route.
And there is almost no comparison value.
No “when to choose us”.
No “what we are strongest at”.
No “who we are best suited for”.
No “how we differ from other firms”.
No decision criteria.
No problem-led sections.
No clear recommendation argument.
This matters because AI systems do not just need to retrieve pages.
They need to reduce uncertainty.
They need to understand:
What category are you in?
Who exactly do you serve?
What problems do you solve?
What proof supports that?
How are you different?
Can you be compared?
Can you be trusted?
Can you be safely recommended?
