- A team can use AI to draft category language, audience descriptions and tone options within minutes, which gives its strategists a wide set of starting points.
- Research on generative AI finds better individual output and narrower collective output, a pattern with a clear implication for positioning.
- The Delegation Test (Exhibit 1) sorts six strategy tasks into those AI can draft and those that need a person’s decision.
- Positioning is a decision about what an organisation gives up, and it rests on internal, customer and competitive evidence.
- A strong working model puts AI in the breadth work and people in the choices, then checks the result with one question: could a competitor say it?
What does it mean for AI to create a brand strategy?
A brand strategy is a set of decisions: who the brand serves, what it promises, why customers should believe it and which ground it leaves to others. Writing the strategy down is one task. Making the decisions is another.
A general-purpose AI model is skilled at the first task. It has read a very large amount of published brand language, so it describes a category fluently and produces plausible positioning statements for it. The output reads as competent because it reflects the category’s existing language.
The second task depends on facts held inside the organisation and its market. These include margins, customer behaviour, leadership appetite and competitive position. Teams that supply those facts get more from AI, and teams that skip them get the category average.
A model drafts the category’s shared language, and a strategy adds the claim the category has yet to make
Consider the sentences that fill most positioning drafts: customer-focused, innovative, trusted, high quality. A model produces them easily because thousands of organisations have published them. Each is accurate and each is shared.
A distinctive strategy adds a claim that competitors have yet to make, with proof behind it. That claim comes from a decision. The organisation chooses one customer group over another, one promise over another, one place to be best.
AI is useful on the way to that decision. It maps the category, lists the claims competitors make and offers a dozen ways to phrase an option. A strategist then selects, tests and commits.
Research on generative AI shows better individual output and narrower collective output
Two peer-reviewed studies of creative work show the pattern. They concern creative writing and ideation. Applying them to brand strategy is Vantage’s reasoning, and neither study examined strategy itself.
Anil Doshi and Oliver Hauser published an online experiment in Science Advances in 2024. Three hundred writers wrote short stories, and some received story ideas from ChatGPT. Six hundred evaluators rated the stories. Stories written with AI ideas scored higher for novelty and usefulness, and the gains were largest for less creative writers. The AI-assisted stories were also more similar to one another than stories written without AI. The authors describe a social dilemma: each writer gains, and the range of ideas across writers narrows.
Barrett Anderson, Jash Shah and Max Kreminski reached a similar finding in a study of 36 participants, presented at the ACM Creativity and Cognition conference in 2024. People who used ChatGPT generated more ideas, and their ideas were less semantically distinct than those of people who used another creativity tool.
Each team that uses the same model for the same question gains speed, and the category gains sameness.
For a brand team, the implication is practical. When several organisations in one category ask a model for a positioning, the drafts converge. The team that brings its own evidence to the model, and makes its own choices from the options, ends up with the distinctive answer.
Published evidence on AI-led branding outcomes is still early, and the studies measure creativity and attention
A search for this article found no published case study with measured business results for an AI-led brand strategy. The closest research examines perception.
A 2025 study in Frontiers in Communication by Wen Guan and colleagues compared eight grayscale logos, four generated with ChatGPT and Midjourney and four created by people. A questionnaire of 434 respondents and an eye-tracking test of 54 participants measured attention and evaluation. The results show how people attend to logos when they know who made them. The study measured attention and perception, and it reports no brand or commercial outcomes.
Readers should treat claims of large gains from AI-led branding as hypotheses until a disclosed method and a baseline back them. Rung 1 of the Brand Evidence Ladder, described in our article on whether branding drives revenue, applies here.
Exhibit 1: The Delegation Test sorts six strategy tasks by what each one needs
The test lists the tasks in a brand strategy and shows where AI contributes and where a person decides. It reflects Vantage’s professional judgement. It is a working model and reports no measured result.
| Strategy task | AI can draft it | Who decides | Evidence the decision needs |
|---|---|---|---|
| 1. Category and audience scan | Yes, as a fast first read | A strategist verifies | Public sources, checked against current data |
| 2. First-draft positioning options | Yes, several variants | A person selects the shortlist | Customer and competitor research |
| 3. Messaging and tone variants | Yes | A person approves | The chosen positioning and the audience’s language |
| 4. The sacrifice decision: the brand’s exclusions | Can list candidates | Leadership | Margins, customer behaviour, capabilities, leadership commitment |
| 5. Proof and evidence selection | Can suggest types of proof | A person verifies each claim | The organisation’s own records and results |
| 6. Final choice among territories | Can compare options | Leadership, after customer testing | Test results and the willingness to commit |
Exhibit 1. The Delegation Test. Vantage framework, offered as professional judgement.
Tasks 1 to 3 reward speed and breadth, so AI adds the most value there. Tasks 4 to 6 carry the strategy, because each one commits the organisation to something. Those tasks stay with people.
Positioning is a decision to give something up, and it rests on evidence the model does not hold
Vantage’s brand positioning framework treats positioning as a sacrifice decision. A brand that wins one customer group accepts that it will serve another group less well. A brand that is known for one strength accepts that others fade.
Positioning is the decision to give something up, and a model holds no evidence of the cost.
The evidence for that decision sits in places a model does not reach. Interviews with leaders reveal the limits of the organisation’s capacity. Customer data shows where margin lives. Competitor behaviour shows which claims are crowded. A brand audit gathers this evidence, and it is the strongest input a team can give an AI tool.
A quick data scan and a research-based audit solve different problems. The scan summarises what is public and returns in minutes. The audit gathers what is private: stakeholder interviews, customer records and internal performance. Strategy decisions draw on both.
A workable division of labour puts AI in the breadth work and people in the choices
Teams that use AI well follow a consistent pattern. They give the model their own evidence, ask it for many options and keep the decision in the room with the people accountable for it.
In practice, that means four steps. Gather the audit findings and customer evidence first. Ask AI for a wide set of positioning options, then for messaging variants on the two or three that survive. Test the survivors with customers or sales teams. Choose, and record the exclusions.
The sequence protects the speed benefit and the distinctive result. It also keeps one person accountable, because a strategy that nobody chose is difficult to defend to a board.
Singapore and Southeast Asian organisations choose market by market
A Singapore organisation selling into Malaysia, Indonesia and Vietnam makes positioning choices for each market: which markets lead, which claims travel and which customer groups to serve first. Customer evidence from each market informs those choices. An AI tool holds that evidence only when the team supplies it.
AI tools are inexpensive and available to every organisation in the region, so the first draft is no longer a differentiator. The differentiator is the quality of the evidence and the clarity of the choices that follow. For the wider effect of AI on how brands look alike in answers, see our analysis of brand distinctiveness and AI sameness.
Exhibit 2: Ask whether a competitor could say it
One question tests any AI-drafted strategy. Read each statement and ask whether a competitor could publish it unchanged. If the answer is yes, the statement needs a choice added.
| Invented generic statement | Could a competitor say it? | The choice that makes it specific |
|---|---|---|
| "We deliver innovative solutions that put customers first." | Yes, word for word | Name the customer group served first and the problem solved |
| "A trusted partner for your growth journey." | Yes | State the proof of trust: the record, the certification, the named outcome |
| "Quality and service you can rely on." | Yes | Name the one strength the organisation holds above its category, and the trade-off that strength costs |
Exhibit 2. The competitor test, applied to three invented statements. They are generic examples and match no real organisation.
A statement that survives the test names a customer, a promise and a proof that only this organisation can claim. The test takes five minutes and suits a board paper as well as a workshop.
Related Vantage insights
- For how AI engines make brands look alike in their answers, see brand distinctiveness and AI sameness.
- For the broader view of AI and branding, see how AI is changing branding.
- For the strategic foundation, see our brand positioning framework.
- To gather the evidence a strategy needs, see how to conduct a brand audit.
- For a related view on evidence, see does branding drive revenue.
About Vantage Branding
Vantage is a Singapore brand consultancy specialising in brand research, strategy, and identity design for ambitious organisations across Southeast Asia, with particular depth in healthcare, finance, government, and cultural-institution branding. Vantage builds fewer, stronger brands, pairing research rigour with senior craft across strategy, identity, experience and activation. PMC-certified, with EDGE grant support for overseas expansion. For a conversation about how we could help your brand, get in touch.