Which AI Tool Is Best for Marketing Strategy? Start With the Work, Not the Model.

The short answer

For an experienced strategist working on an occasional, well-defined problem, a general-purpose assistant such as ChatGPT or Claude may be all that's needed. Gemini can be particularly relevant when the work and its source material already live in Google's ecosystem. For research-intensive questions, use a tool and workflow that can retrieve sources, show where claims came from and let you challenge the evidence. If your agency regularly develops brand positioning, integrated campaign strategy and creative briefs, the question changes: you may need a connected strategic process rather than another good answer in another chat window.

There is no single model that wins every strategic job. Even when one appears stronger in a particular test, the quality of the brief, the available evidence and the strategist's judgement still matter. Decide which strategic tasks AI should support before deciding which assistant to use.

First, decide what kind of strategic work you need help with

Interrogating a brief

A client brief is often a confident description of a problem that hasn't been properly defined. General-purpose AI can help expose assumptions, contradictions and missing information. Ask it to distinguish facts from claims, identify what would change the recommendation and draft questions for the client. Test whether it helps you notice what the brief leaves unanswered. A summary alone may leave those gaps intact.

Researching the market

Research assistants can gather and organise material much faster than someone manually opening dozens of tabs. ChatGPT’s deep research and Gemini’s Deep Research are examples of research-oriented capabilities. But a polished report is not evidence that its claims are right. Follow the citations. Check dates, samples and the distinction between evidence and model inference. If a finding will influence a major positioning decision, read the original source.

Understanding people

AI can help organise interview material, compare behaviours, suggest tensions and challenge an audience hypothesis. It cannot turn invented consumer reactions into research. A synthetic persona that sounds convincing is still not a substitute for evidence about real people.

Developing positioning

A chatbot can explore territories, articulate alternatives and act as a useful opponent. The difficult part is deciding which territory the brand has the credibility and appetite to own. Positioning is a choice. A tool that produces fifteen plausible options has helped with exploration, not necessarily with the decision.

Developing campaign strategy

This is where isolated answers begin to cause trouble. The audience insight needs to inform the strategic idea. The positioning needs to constrain what the campaign can credibly claim. The communication objectives need to connect to the behaviour the agency is trying to change. A clever output at one stage can be useless if the next stage quietly ignores it.

Writing the creative brief

AI can help translate strategic decisions into a more concise and useful document. It can also produce an immaculate brief with no real point of view. The relevant test is whether creatives understand the problem, the choice and the opportunity. Better framing gives AI-assisted creative work a better chance.

Where ChatGPT, Claude and Gemini fit

The familiar assistants are a sensible place to start. They are flexible, relatively accessible and capable of useful strategic dialogue. Their specific features change frequently, so treating any one of them as the permanent winner is a poor buying strategy.

ChatGPT

ChatGPT can help interrogate a brief, explore hypotheses and challenge a strategic argument. Deep research can gather information into a report with source links. Follow those links and check whether the evidence supports the recommendation.

Claude

Claude is worth testing for reviewing documents, critiquing arguments and developing written strategic material. Projects let teams provide shared documents and instructions; Artifacts support editable outputs. The agency still needs to decide which evidence and strategic choices should guide the work.

Gemini

Gemini deserves consideration when an agency already works in Google Workspace. Deep Research can draw on eligible Workspace sources and the public web, reducing the work of assembling context. Availability depends on the account, plan and permissions.

When a chatbot stops being enough

Imagine a strategist develops a good audience insight in one session. A positioning territory in another. A campaign direction in a third. Each looks convincing. Together, they don't quite add up.

The campaign solves a different problem from the one identified in the brief. The positioning depends on a consumer assumption the research never established. The creative brief contains a sharp line that has little to do with the chosen strategy.

Nothing necessarily went wrong inside any single chat. The failure happened between them.

That is why a capable assistant still needs a strategic process. It also helps explain what an AI strategy platform means. By AI strategy platform, we mean a system that supports connected stages of strategic development, carries relevant context and decisions forward, and gives people a structured way to evaluate and revise the work. A marketing prompt on its own does not provide those connections.

Not every agency needs one. A senior strategist working occasionally on a specific question may get excellent value from a general-purpose assistant. An agency repeatedly developing brand positioning, cross-channel campaigns and creative briefs has a different problem: it needs coherence across the work and its handoffs. Strong individual outputs still need to form a useful strategy.

The agency's work matters more than the strategist's seniority

It's tempting to assume that junior strategists need structured tools while experienced people need none. That gets the question wrong.

A junior can benefit enormously from being guided through a disciplined process and being shown what good work must establish before the next decision. An experienced strategist may use the same structure to avoid repetitive groundwork and concentrate on difficult choices. Conversely, a senior strategist with a well-established method may prefer a general-purpose assistant for occasional projects.

The more important distinction is the nature and frequency of the work.

For agencies specialising in Amazon retail media, SEO, highly tactical performance marketing or social-first execution, a dedicated specialist tool or a carefully built internal workflow may provide better value. An agency doing relatively little positioning or substantial campaign strategy may struggle to justify a platform designed around those disciplines. A cross-channel creative agency developing brand and campaign strategy repeatedly is a much more natural fit.

How to choose without buying another expensive chatbot

Take a real client brief and follow it all the way through to a usable creative brief. Then ask a few awkward questions.

Did the tool identify gaps in the original brief? Did it distinguish evidence from speculation? Could you see why it proposed a particular audience or positioning? Did strategic choices survive the journey into campaign development? Could a human change a decision without rebuilding everything? Was the final brief genuinely useful to creatives? And what work did the team still have to do outside the system to make the pieces fit?

If you're comparing general assistants, those questions tell you whether your prompting and review process is good enough. If you're evaluating a connected strategy platform, they tell you whether the platform actually connects strategic thinking rather than merely producing a series of attractive documents.

The best AI for marketing strategy is the one that improves the strategic work you actually do. Start there. Choose the software afterwards.

For agency owners choosing tools across several disciplines, map the wider agency AI stack before adding another subscription.

Apply the same criteria to Mirel’s strategic workflow. A useful demonstration should show what happens when the evidence changes and a person revises a decision.