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Most British businesses have started asking the right question — why isn't our brand appearing in ChatGPT, Perplexity, or Google's AI Overviews — but they have not yet done the work to answer it. The AI Visibility Roadmap gives your team a structured, sequenced plan to change that: a 90-day sprint for immediate wins, a 12-month programme for sustained visibility, and a resource framework that maps work against your actual capacity. This is not a presentation deck full of vague recommendations. It is a working plan your team can execute from day one.
**In-house marketing and SEO teams at mid-market UK companies** who have seen AI search cannibilise their organic traffic and need an approved, resourced plan to respond — not a theoretical overview of what AEO is.
**Head of Digital and Chief Marketing Officers** who need to make an internal case for investment in AI visibility work and require a structured business document with milestones, success metrics, and resource scoping that will survive procurement and board scrutiny.
**Professional services firms — legal, financial, consulting, and accountancy practices** operating in sectors where AI citations carry significant authority. When a prospective client asks an AI which firm handles a particular area of law or which accountancy practice works with manufacturing businesses, your firm either appears or it does not. The roadmap sequences the work to make sure it appears.
**Growth-stage UK technology companies** preparing for Series B or scaling into new verticals, where AI visibility directly influences how analysts, journalists, and potential partners discover and describe the business. Getting entity accuracy right at this stage is significantly easier than correcting it later.
Most teams have a general sense that they need to do something about AI search, and individuals within those teams may have strong views, but there is no agreed sequencing, no resource allocation, and no success metrics. Everyone is doing adjacent work without a shared plan. The result is duplicated effort, missed dependencies, and no way to measure whether anything is working.
They are not. Answer Engine Optimisation, Generative Engine Optimisation, and Large Language Model Optimisation each address a different mechanism, require different types of content, and produce results on different timelines. Running all three simultaneously without understanding their dependencies wastes resource. Running only one leaves significant visibility gaps. The order in which you sequence the work matters considerably.
Many organisations have commissioned an AI visibility audit — either internally or through a third party — and the findings are sitting in a document that nobody has acted on. The gap is not understanding; it is the absence of a structured plan that converts findings into a prioritised programme of work with owners, timelines, and milestones.
AI systems learn from published, structured, and cited content. Every week your competitors publish authoritative content that gets cited, every structured data markup they deploy, and every high-quality link they earn from credible sources compounds into AI visibility that will be very difficult to displace later. The cost of waiting is not zero.
a 10-point diagnostic of your AI visibility position covering entity accuracy, citation presence across major AI platforms, content structure and AEO readiness, structured data coverage, and authority signals
ranked list of AEO, GEO, and LLMO opportunities mapped against effort, timeline, and expected impact, with the reasoning behind each prioritisation decision made transparent
a week-by-week execution schedule for the first phase of work, covering quick wins that can show measurable results within the first 30 days, foundation-building work in weeks four through eight, and the first wave of content and authority work in weeks nine through twelve
a full-year plan structured across three tracks: content and AEO (question-targeted content, structured data, featured snippet optimisation), authority and GEO (publication strategy, link building, citation building in AI-training sources), and entity and LLMO (Knowledge Graph management, entity disambiguation, brand description standardisation across the web)
breakdown of what the work requires in terms of internal headcount, tooling, and external support, with cost estimates and options for different levels of investment
the KPIs your team will track, how each is measured, and the dashboard structure that gives leadership visibility into progress without requiring deep technical knowledge
The roadmap is a complete strategic planning document comprising a current-state assessment, a prioritised opportunity register, a week-by-week 90-day sprint plan, a 12-month plan across three execution tracks, a resource scoping document, and a reporting framework with defined KPIs. It is produced as a working document — editable, ownable, and ready for internal distribution and approval.
An existing audit is useful but not required. If you already have AI visibility audit findings, we incorporate them directly into the situation assessment stage, which shortens the process. If you do not, we run a rapid 10-point current-state assessment as the first step of the roadmap engagement. The roadmap is designed to work either way.
The standard engagement runs over three to four weeks from kick-off to final delivery. The situation assessment and prioritisation workshop take place in the first week, the 90-day sprint plan is delivered at the end of week two, and the full 12-month roadmap and reporting framework are delivered at the end of week three or four depending on the volume of the opportunity register and the complexity of the resource scoping.
Pricing starts from £4,800 for a single-market roadmap and varies based on the number of markets covered, the depth of the competitive analysis, and whether the situation assessment requires a full audit or can draw on existing findings. Multi-market engagements covering additional regions are available at combined rates. We provide a fixed-price quote following an initial scoping call.
Both options are available. The roadmap is designed as a standalone deliverable that your internal team can execute independently, with clear task ownership and milestones. If you would prefer Ignited Nepal to take on execution — managing the sprint work, producing content, handling authority-building outreach, or managing technical implementation — we offer retained execution programmes that run alongside the roadmap. The two engagements are scoped and priced separately so that you are not obliged to purchase both.
Results are measured against the four KPIs built into the reporting framework: AEO citation rate, GEO mention share, LLMO accuracy score, and entity health score. Baseline measurements are taken during the situation assessment, and each quarterly milestone in the 12-month plan includes specific numerical targets for each metric. Progress is reviewed at each quarterly milestone point, and the plan is adjusted where targets are being exceeded or missed. We also track leading indicators — content published, structured data deployed, citations built, entity corrections confirmed — so that you have visibility into activity before outcome metrics move.
Not a black box. Real specialists you can call, with their names on the work.
AI search is not a future consideration for UK businesses — it is the mechanism through which a growing proportion of high-intent discovery is already happening. Every week without a structured plan is a week your competitors' AI visibility compounds and yours does not. The roadmap takes three to four weeks to produce and gives your team everything required to execute a year of focused, measurable AI visibility work.
The best time to plan this work was six months ago. The second best time is now.
Ignited Nepal
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