How to Make AI Recommend Your Expertise to Potential Clients

In a recent LinkedIn post, IZA MONTALVO discusses how business leaders and experts can improve the odds that AI tools will identify them when clients ask whom to hire. This article covers Montalvo’s advice in that post; it is an independent report and analysis, not an article written by Montalvo.

Montalvo’s central argument is that visibility alone is not enough: AI systems need evidence that a person is credible and relevant to a field. As Montalvo puts it:

“AI needs evidence before it names you.”

Build a presence beyond LinkedIn

According to Montalvo, one part of that evidence is being mentioned in sources outside a person’s own social profiles. The post points to press features, podcasts, expert quotations, industry publications and guest articles as places where professional expertise may be recognized.

The logic is that broader coverage gives prospective clients—and the systems they consult—more material with which to assess someone’s work. Montalvo summarizes this step as “GET MENTIONED,” emphasizing presence in places where professional trust already exists.

Make expertise easy to find and quote

Montalvo’s second recommendation is to publish clear, searchable answers. The post advises professionals to address questions directly in LinkedIn content, put the answer near the beginning, and use language clients are likely to search for. It also suggests focusing recognition around three core topics rather than presenting an unfocused range of claims.

“Make your expertise easy to quote.”

That advice connects writing style with discoverability: concise answers can make a person’s knowledge easier to identify and reuse. Montalvo argues that consistently demonstrating subject expertise helps build recognition around those chosen topics.

Keep professional signals consistent

The third step in Montalvo’s framework is verification. A person’s name, biography, title and stated expertise should tell a consistent story across their website, LinkedIn profile and press coverage. In Montalvo’s view, alignment across these sources makes it easier for others to confirm who someone is and what they do.

“Your website, LinkedIn and press coverage should back each other up.”

The post then recommends a practical check: ask an AI tool who leads a particular field and see whether the person’s name appears. Montalvo also invites readers to share what they find. The test is presented as a way to gauge current visibility, while the broader playbook focuses on strengthening the evidence that supports a recommendation.

A visibility strategy built on evidence

Montalvo’s post frames AI recommendations as the result of a professional footprint built across multiple channels. Its three-part approach—being mentioned, being cited and being verifiable—offers a concrete way to think about that footprint. The article’s summary reflects Montalvo’s advice in the original LinkedIn post, rather than claiming that any single action guarantees an AI recommendation.