This is not a roundup of every AI tool a marketer could theoretically use. It is the short list of tools I am actually running, the problems each one solves, and why I think they matter for marketing leaders trying to build a real practice instead of a PowerPoint slide about AI strategy.
AirOps
The problem with most content operations is that quality is trapped in the heads of whoever writes best. AirOps gets that thinking into a repeatable system. I use it to build AI workflows that run on actual company data: positioning documents, competitive research, ICP definitions, past-performing content. The output sounds like the company because it is trained on the company.
What I actually use it for: generating first drafts of case studies and sales one-pagers at scale, running content briefs through a consistent editorial filter, and building internal knowledge tools that let sales and CS answer product questions without pinging the marketing team. It closes the gap between “we have AI” and “AI is doing useful work.”
n8n
Most automation tools are designed for IT teams. n8n is something a technically-minded marketer can actually operate without a developer. I use it to connect tools that would otherwise require manual handoffs.
What I actually use it for: routing inbound leads through enrichment and scoring before they hit CRM, building internal alerts when pipeline changes hit a threshold, and connecting content performance data into reporting without a BI request. Good marketing operations should not require an engineering ticket.
Cursor
Cursor is a code editor built for people who are not developers. Building modern marketing infrastructure increasingly requires writing code — lightweight landing pages, custom attribution scripts, data pulls from APIs. Cursor makes that accessible.
What I actually use it for: building pages quickly in Vercel v0 and then refining the code, writing Python scripts to clean and analyze data, and building lightweight internal tools that would otherwise sit on a backlog. The marketers who learn to build in this environment will have a structural advantage over those who stay on the request side of every technical task.
Vercel v0
v0 turns a well-written prompt into a working web component. I built the first version of this site using it. It does not replace a designer or developer for complex work. What it does is compress the distance between idea and testable reality. This website was built with v0.
What I actually use it for: rapid prototyping of landing pages before committing to design and engineering time, building internal tools and dashboards, and testing positioning in a live environment without waiting for a production deployment.
Pinecone
Pinecone is a vector database — the infrastructure layer that makes AI systems useful when they need to work with your specific data rather than general knowledge. It belongs on this list because it makes the other tools significantly more powerful.
What I actually use it for: building internal knowledge bases that AI tools can query accurately, powering search experiences that return relevant results instead of keyword matches, and enabling AI workflows that can pull from large repositories of company content without hallucinating. If you are building serious AI workflows, you will eventually need a vector database.
My take on AI in marketing
Most marketing teams are using AI for the same three things: writing first drafts faster, cleaning up copy, and generating images. That's fine and probably saves a good chunk of time. But it is table stakes, not a strategy.
The teams building a real advantage are using AI to instrument things that were previously too slow or too expensive to instrument: attribution models, competitive intelligence that pulls from live data, onboarding sequences that adapt to what a prospect has actually done, reporting that does not require human time to compile.
The tools above are where I have found value. They are not the only tools worth knowing, and some may be outdated in a matter of months. But they are the ones I would start with if I were building a modern GTM function from scratch today.