To get high-quality, on-brand output from AI, teams must invest more time in the initial strategic phase. This means creating highly precise creative briefs with clear insights and target audience definitions. AI scales execution, but human strategy must guide it to avoid generic, off-brand results.

Current AI ad tools are highly effective at generating strong, platform-specific copy, especially for text-heavy formats like Google Search Ads. However, they struggle with visual elements, often producing generic imagery, incorrect logos, and poor layouts that require significant human iteration and refinement.

To maximize efficiency and control costs, treat AI ad generators as a starting point, not a final solution. Use them to create initial concepts and copy. Once an ad is "close enough," export it and perform final visual edits in a dedicated design tool like Canva, avoiding expensive AI credit usage for minor tweaks.

To get consistent results from AI, use the "3 C's" framework: Clarity (the AI's role and your goal), Context (the bigger business picture), and Cues (supporting documents like brand guides). Most users fail by not providing enough cues.

To get high-quality output, prompt AI as if it has zero prior knowledge. This means providing comprehensive context including target personas, business challenges, strategic goals, and even raw data like ad performance reports. More input yields better output.

Instead of accepting an AI's first output, request multiple variations of the content. Then, ask the AI to identify the best option. This forces the model to re-evaluate its own work against the project's goals and target audience, leading to a more refined final product.

AI-generated text often falls back on clichés and recognizable patterns. To combat this, create a master prompt that includes a list of banned words (e.g., "innovative," "excited to") and common LLM phrases. This forces the model to generate more specific, higher-impact, and human-like copy.

GM's CMO warns that AI in creative often produces average results because it finds the "most likely next answer," reflecting the category norm, not a distinctive brand voice. Simple edits can also trigger a full re-render, introducing new errors and creating more work.

Instead of using AI to generate final creative work, use it as a tool for anti-inspiration. Figma's CEO asks generative AI for the "10 cliche ways to say this" so he can consciously push beyond the obvious and predictable. This technique helps creators find novel angles and maintain a unique voice.