AI adoption in marketing
How marketing teams can move beyond isolated prompting and experimentation toward workflows people understand, trust, and use.
Using AI for marketing
Turning AI experiments into repeatable marketing workflows.
I’m Eduard Dziak, a growth marketing leader with more than eight years of experience across paid acquisition, SEO, content, lifecycle, conversion, and measurement. I write about using AI for marketing to improve the way work gets done without losing judgment, quality, or accountability.
AI becomes useful when it becomes part of the work.
A promising experiment is only the beginning. For AI to create lasting value in marketing, it needs a clear place in the workflow, an owner, reliable inputs, human review, and a way to measure whether it actually improved the outcome.
The goal is not to add AI everywhere. It is to understand where it helps, where it does not, and how a team can use it consistently.
What I explore
My writing sits at the intersection of practical AI adoption and the wider marketing system around it.
AI-supported marketing workflows
Practical applications across content, paid acquisition, SEO, research, analysis, reporting, and marketing visibility, with human judgment built in.
Growth systems and measurement
How paid, organic, content, lifecycle, conversion, attribution, and reporting work better when they are connected around shared outcomes.
Built from marketing work, not AI theory.
My perspective comes from more than eight years working across SaaS growth and demand generation, including paid acquisition, SEO and AEO, content, lifecycle, websites, conversion, attribution, and reporting.
More recently, I have been building AI-supported workflows and helping a marketing team decide where AI improves the work, where it does not, and what people still need to own. That combination shapes everything I write here.
About me
I’m a growth marketer interested in how useful change actually happens.
I’m Eduard, a growth marketing leader based in Kuala Lumpur. I have spent my career connecting channels, data, systems, and people to make marketing work better.
I am especially interested in the gap between testing AI and making it genuinely useful to a team. I prefer practical systems over novelty, clear judgment over hype, and lessons grounded in the work itself.
Let’s compare notes.
If you are thinking seriously about how AI is changing marketing work, I would be glad to hear what you are learning, questioning, or building.