OPINION: If Maya has changed, your strategy must change too (Part #2)
Written by: Phoebe Keates, Enterprise Account Director at Choir Digital
When we met Maya, nothing overly dramatic had happened.
She did not consciously adopt artificial intelligence.
She did not decide to change how she researches brands.
She simply asked questions and moved on with her day.
This creates a new strategic question: What do AI systems currently believe about your organisation?
For most companies, the honest answer is simple. They don’t know.
Traditional analytics cannot see it.
Media monitoring does not capture it.
SEO reporting was never designed for it.
And internally, ownership is unclear. So, nothing happens.
At Choir Digital, we have been working with clients to respond to the growth of LLMs.
This isn’t a technology problem. Most organisations already have tools. They already have dashboards, data and platforms promising visibility.
What they lack is an operating model for a world where AI interprets their brand before a customer ever encounters it.
No single platform fixes that.
No dashboard changes perception on its own.
And treating AI visibility as a one-off experiment simply recreates the same gap months later.
The real challenge is organisational. Companies need a structured way to move from curiosity to business impact. From observing AI behaviour, to deliberately shaping it.
That realisation is what led Choir Digital to design a blended approach that combines strategy, execution and governance rather than relying on technology alone.
Phase One: Analysis (AKA understanding how AI currently sees you)
The first step is to gain clarity, so we begin by exploring:
If Maya asked AI about your organisation, brand or products today, what would it say?
Phase 1 establishes a measurable baseline across leading AI platforms such as ChatGPT, Gemini and Google Answers. We analyse how the organisation’s products and brands are described, when they are recommended, which competitors appear alongside it and what are the signals that models rely on when forming answers.
But this Phase goes beyond diagnostics. Together with stakeholders, we define something more important:
Which products / brands are your most strategic for growth?
What should AI systems say?
Which strengths must be surfaced?
Which credentials must be recognised?
Rather than attempting to optimise everything, we focus deliberately on a small number of priority areas where inclusion truly matters.
Phase Two: Remediation (AKA turning strategy into measurable change)
Once direction is clear, execution begins. This stage looks less like marketing and more like systems design.
We refine how authority signals appear across your priorities. We adjust narrative structure, evidence, digital architecture and external references so AI models consistently interpret the organisation in line with agreed positioning.
The objective is simple: Measurable improvement in how AI engines interpret, describe and recommend the organisation.
Over time, progress becomes visible not through traffic spikes, but through inclusion, sentiment, accuracy and competitive positioning within AI-generated answers.
Phase Three: Maintenance (AKA moving to organisational ownership and internal capability)
The final focus is cultural. AI visibility cannot remain a project. Models evolve, narratives shift, and competitive positioning changes continuously. Organisations therefore need governance, ownership and early warning signals.
Phase 3 transforms optimisation into an operational capability. Monitoring runs across agreed priority prompts, reporting aligns to governance structures, and decision rights and response pathways become crystal clear.
For the first time, organisations gain visibility into how AI narratives change over time and how quickly action should be taken when they do.
The organisations that benefit most are not those trying to chase technology trends.
They will be the ones who understand that customer experience has shifted upstream. Maya no longer discovers brands herself. AI discovers them for her. And by the time a customer arrives, reputation, positioning and trust have already been confirmed.
Because the change underway is not about artificial intelligence replacing marketing, communications or strategy. It is about a new interpretive layer sitting between organisations and the people they serve.
At Choir Digital, our role is to help organisations understand that layer, influence it responsibly and build the internal capability to manage it long after the initial engagement ends. If you are exploring how AI systems influence customer discovery, feel free to connect with me to discuss how your organisation can strengthen its visibility within AI-generated answers.