AI tools have quickly gone from “nice to have” to a core part of most marketing teams’ workflows. But with so many options available, the bigger question isn’t whether to use AI — it’s which tools actually deliver value.
A recent LinkedIn poll asked marketers a simple question: What’s the best overall AI tool for marketing?
The results were telling:
- 57% said Claude
- 25% said Gemini
- 10% said ChatGPT
- 7% said Other
At a glance, Claude stands out as the clear favorite. But the why behind that result is more interesting than the numbers themselves.
Why Claude Is Gaining Momentum
Across Reddit and marketing communities, Claude consistently comes up in conversations around depth, structure, and workflow integration.
Many marketers are using it for:
- Research and synthesis
- Strategy development
- Long-form content creation
- Turning unstructured information into usable assets
One marketer running GTM and growth programs said they rely on Claude daily for client work across research, copy, and campaign development.
Another noted that Claude gets them to a usable output faster, especially when working with longer or more complex inputs.
There’s also a growing trend of using Claude beyond basic prompts. Some teams are:
- Connecting it to tools like Google Ads, GA, and LinkedIn Ads
- Building reporting scripts and workflows
- Managing full content systems (calendars, brand voice, drafts)
In those cases, Claude becomes less of a writing tool and more of a central operating layer for marketing execution.
Where ChatGPT Still Stands Out
Even with Claude leading the poll, ChatGPT isn’t going anywhere.
Marketers still lean on it for:
- Copywriting
- Ideation
- Quick-turn content
- Up-to-date general knowledge
Some users actually prefer ChatGPT as a “marketing collaborator”, especially for brainstorming and refining messaging.
There’s also a practical reason many teams continue using it alongside other tools: cost and usage flexibility.
Gemini’s Role in the Stack
Gemini’s strength shows up most often in ecosystem integration and data access, particularly for teams already working within Google’s tools.
It’s commonly paired with:
- Google Ads
- Analytics
- Workspace tools
And while it didn’t top the poll, a quarter of respondents choosing it suggests it’s becoming a serious part of the marketing stack — especially for data-heavy workflows and reporting.
The Real Takeaway: It’s Not About One Tool
One of the most consistent themes across real user feedback is this:
The biggest gains aren’t coming from switching tools — they’re coming from building better systems.
Marketers seeing the most success are:
- Defining repeatable use cases (not just prompting randomly)
- Structuring content and data so AI can reuse context
- Using multiple tools depending on the task
- Treating AI as part of a workflow, not a one-off solution
In some cases, teams are even managing marketing like a codebase — storing content, strategy, and brand rules in structured systems that AI can continuously learn from.
Where Most Teams Should Start
If you’re evaluating AI tools for marketing, the most practical approach isn’t choosing a “winner.”
Instead:
- Pick 2–3 core use cases (content, reporting, research, etc.)
- Test tools against real work, not demos
- Focus on consistency and repeatability
- Build simple workflows before scaling
Because in most cases, one well-built workflow will outperform constantly switching between tools.
