Week 1: measure, then fix what is broken
Start with the baseline: run your customers' twenty most common questions through ChatGPT, Google AI Overviews, Gemini and Perplexity, in English and Arabic, following the method in checking what AI says about your brand. Record who gets named and every factual error about you. Then spend the rest of the week on corrections, because wrong facts are the fastest win available: fix your website's outdated pages first, then work the correction path for wrong AI information for anything engines are actively repeating. A wrong price or a closed branch location in AI answers costs you buyers every day it survives, and it is usually traceable to a page you can change this afternoon.
Week 2: align your profiles and directories
Write one master fact sheet with your name, address, phone, hours, services and a one-line description, and copy it exactly into your Google Business Profile, then into the five to ten directories that matter for your category and market. Search your old phone numbers and addresses to surface forgotten listings, and request corrections on the pages you cannot edit. This work is not exciting, but it makes a real difference, because consistency across sources is one of the strongest signals engines use when deciding whether to name a business at all. A clinic whose trade name, licence name and directory listings all differ looks like three different businesses to an AI system, not one. That confusion costs you recommendations.
Weeks 3 and 4: publish what engines can quote
Take the five questions from your baseline where you were absent and competitors were named, and publish one clear page for each: the answer in the first two sentences, plain language, specific details an AI system can pull directly. Add schema markup to your site so your identity and services are declared rather than inferred. If you serve Arabic-speaking customers, publish the Arabic versions as real pages, not just quick translations, since Arabic answers draw on a thinner pool of sources and clear Arabic content stands out faster. By day 30, rerun your baseline questions and compare against week 1: fact corrections and profile alignment often show inside the month on platforms that browse live sources.
What a month cannot buy
Honesty about the limits protects your budget. Review volume only grows as fast as real customers leave reviews. Press coverage, directory roundup placements and the earned mentions that swing competitive shortlists take a quarter or more of steady work. And answers on platforms that lean on older training data update on their own timeline, which you cannot speed up. The 30-day sprint clears errors and builds the foundations; the compounding gains come from repeating the measurement monthly and working the slower sources with patience. A structured AI visibility baseline shows you two things: what changed this month, and what to target next quarter.