Search Engine Journal has published a structured 90-day plan designed to make individual business locations visible in AI-driven search results, signaling how quickly local SEO practice is shifting toward generative engine optimization (GEO).

The core premise of the guide is that AI search systems — assistants and answer engines that synthesize responses rather than return ten blue links — now influence how consumers discover local businesses. A business with dozens or hundreds of locations cannot treat AI readiness as a one-off project, the publication argues. It requires a repeatable, location-by-location process.

What does the 90-day plan cover?

The plan breaks the work into a quarter-long sequence of tasks that a local search team can execute across an entire location footprint. Its defining feature is repeatability: the same audit-and-fix cycle applies to every storefront, branch office, or service area.

Key elements of the framework include:

• Assessing each location's current visibility in AI-generated answers
• Auditing and correcting the location data that AI systems draw on when composing responses
• Structuring on-site content so that answer engines can extract and cite it accurately
• Building consistency between the business's own pages and third-party sources that feed AI models
• Establishing an ongoing monitoring routine rather than a one-time cleanup

The publication frames the effort as making every location "AI-ready" — a standard that goes beyond traditional Google Business Profile optimization, because generative systems pull from a wider set of sources than the local pack alone.

Why does this matter for multi-location brands?

The timing reflects a broader industry shift. As AI assistants and answer engines increasingly handle consumer queries that once flowed through standard local search results, businesses that appear in synthesized answers gain visibility, while those absent from the underlying sources lose it.

For multi-location operators — franchises, retail chains, healthcare networks, and service businesses — the challenge scales linearly with the number of locations. Data errors, inconsistent naming, or thin location pages at even a subset of addresses can distort what AI systems say about the brand everywhere.

The guide positions the 90-day timeframe as realistic for this work: long enough to audit and remediate, short enough to keep pace with how quickly AI search behavior is changing.

Confirmed guidance versus interpretation

The 90-day plan itself is editorial guidance from Search Engine Journal, not an announcement from a search engine. It responds to observable behavior of AI search products, but no search platform has endorsed or mandated the specific steps in the framework.

Readers should treat the plan as practitioner strategy — a structured approach from an established industry publication — rather than a documented requirement from Google, OpenAI, or any other engine.

What should local search teams watch next?

The plan implies a continuing obligation rather than a finish line. Teams that complete the 90-day cycle should monitor whether their locations begin appearing in AI-generated answers over subsequent weeks, watch for changes in how engines cite local businesses, and repeat audits as generative search products evolve.