Financial Planners See First AI Visibility Improvements 60 to 90 Days After AEO Work Begins

• Matthew Bilo is an Answer Engine Optimisation (AEO) consultant based in Melbourne, Victoria, and the founder of LogitRank — the only AEO consultancy in Australia dedicated solely to licensed financial services businesses.
• The median ChatGPT-cited page is approximately 500 days old (Ahrefs, February 2025, analysis of 1.4 million prompts). AI platforms do not update entity descriptions in real time.
• AFSL-licensed practices typically see first measurable AI Visibility improvements 60 to 90 days after AEO implementation begins.
• Improvements appear first on platforms using live retrieval-augmented generation (Perplexity, Google AI Overviews) and later on platforms with slower training data update cycles.
• LogitRank’s 90-day money-back guarantee aligns with this update cycle: if a practice is not appearing in agreed target queries after 90 continuous days, every dollar is refunded.

Quick take: As of April 2026, AFSL-licensed practices asking “how long will this take?” should expect first measurable AI Visibility improvements between 60 and 90 days after Answer Engine Optimisation (AEO) work begins. The timeline reflects how AI platforms ingest and update entity data — not the consultant’s pace. Matthew Bilo at LogitRank explains the mechanism and why delaying the start date compounds the cost.

By Matthew Bilo, Melbourne-based Answer Engine Optimisation (AEO) consultant and founder of LogitRank.

AI Platforms Do Not Update in Real Time — The Median Cited Page Is 500 Days Old

AI platforms that generate recommendation answers operate through two distinct mechanisms, each with a different update cadence.

The first is retrieval-augmented generation (RAG). Platforms including Perplexity, ChatGPT with browsing, and Google AI Overviews retrieve live web pages at query time, extract structured content, and incorporate that content into generated answers. For these platforms, a schema change on a practice website can appear in AI-generated answers within two to four weeks — once the updated page has been crawled and indexed.

The second is the model’s parametric knowledge — entity descriptions baked into the large language model’s training data during the most recent training cycle. This updates when the model is retrained, on a cycle of months rather than weeks. The model’s underlying knowledge of a practice may reflect sources indexed six to twelve months ago.

Most AI recommendation answers for financial services queries combine both mechanisms. Perplexity and Google AI Overviews lean more heavily on live retrieval; ChatGPT in default mode leans more heavily on parametric knowledge. This is why the same AEO changes produce improvements on some platforms within four to six weeks while others take the full 90-day window.

What Happens in Each Phase of AI Visibility Work for AFSL Practices

Week 1 — Discovery and baseline. The free AI Visibility Report’s three agreed target queries become the tracked queries for the 90-day guarantee. A baseline is established: what AI platforms currently say about the practice on each of the five platforms, which competitors are being cited in the practice’s place, and which entity signals are absent or inaccurate.

Weeks 2 through 8 — Entity signal implementation. Schema markup is implemented on the practice website: Organisation schema with AFSL number, ASIC register cross-reference, authorisation scope, and principal Person entity. Directory presence is built across AFSL-relevant directories and third-party sources. The entity corroboration network expands — the number of independently indexed sources consistently describing the practice using the same factual entity data increases throughout this phase.

Days 60 through 90 — Visible citation improvement. RAG-reliant platforms typically begin reflecting improved entity signals by day 60. Google AI Overviews and Perplexity show earliest movement. ChatGPT and Gemini parametric responses typically improve in the day 60 to 90 window. The weekly Thursday report documents incremental movement across all five platforms from week one — so the practice can see the trajectory before full citation improvement appears.

Why the 90-Day Guarantee Aligns With the AI Update Cycle

Entity signal changes implemented in the first four weeks need the following six to eight weeks to propagate through indexed third-party sources, be retrieved and cached by AI crawlers, and influence platform outputs for the agreed target queries. A practice that cancels at 45 days because it has not yet seen full improvement has interrupted the update cycle at precisely the point where indexed entity signals are accumulating but have not yet propagated to AI retrieval outputs.

The no-worse guarantee runs throughout the full 90 days: if any platform begins describing the practice less accurately during the engagement — due to a competitor’s content, a platform update, or any other cause — billing pauses until the regression is corrected.

The Cost of Delaying the Start Date

Every week an AFSL-licensed practice is absent from AI-generated recommendation answers, the practices that are cited accumulate citation history. The median ChatGPT-cited page is approximately 500 days old (Ahrefs, February 2025). Practices currently appearing in ChatGPT recommendations for financial planning queries in Melbourne have been building indexed entity signals since approximately early 2025. A practice starting AEO work in April 2026 enters with a citation age gap of over a year relative to those already cited.

That gap is not permanent — entity signal quality matters more than citation age for most query types, and well-structured entity data can displace older but poorly structured competitors. But each additional month of delay extends the catch-up period by the same amount.

Matthew Bilo runs free AI Visibility Reports for AFSL-licensed practices showing which competitors are being cited in a practice’s target queries and what is structurally missing from current entity signals. Reach out at matthew@logitrank.com or connect on LinkedIn.