The AI tools I actually use in paid search and how

My test for an AI tool is simple: does it make me faster or better without introducing more problems than it solves? A lot of AI marketing tools fail this test. Some pass it comfortably. Here is where I have found genuine value.

Ad copy drafting

AI is genuinely useful for generating a first draft of ad headlines and descriptions. I provide context - the product, the audience, the key value propositions, the tone - and ask for 20 to 30 headline options. I then review them, discard the generic or inaccurate ones, and use the best as a starting point for refinement. The AI output is never final but it accelerates the drafting process significantly and sometimes produces angles I would not have thought of.

Keyword research and clustering

AI tools help with clustering existing keyword lists into logical ad groups - a task that used to take hours in spreadsheets. I paste a raw keyword list and ask for logical groupings based on intent. The output needs checking but it is a strong starting point. For initial keyword ideation I still use traditional tools like Google Keyword Planner, but AI helps me think about adjacent terms and question-based queries I might have missed.

Reporting narratives

Writing the narrative commentary for client reports is time-consuming. I use AI to draft the first version based on the data points I provide. The draft is edited significantly before it goes to a client - the AI does not know the nuances of the client relationship, the context behind specific performance changes, or how that client prefers to receive information. But it removes the blank page problem.

Research and summarisation

When I need to get up to speed on an industry I am less familiar with - understanding the buyer journey, the terminology, the competitive landscape - AI tools accelerate the research phase considerably. I verify what I learn through primary sources but the AI summary gives me a foundation to build on.

What I do not use AI for

Strategic recommendations to clients. Account auditing. Interpreting performance data to identify root causes. Anything where the quality of judgment directly determines the quality of the outcome. These stay human. The AI tools are supporting work, not lead work. That distinction matters.