How to create AI advertising texts for Google Ads

Creating effective ad copy remains one of the biggest challenges in PPC marketing. It is a time-consuming, costly process that often involves trial and error—especially when scaling campaigns across different audiences and formats.

Generative AI offers new opportunities, already reshaping how brands develop and optimize Google Ads across text, video, and display formats. Its benefits are clear: faster production, deeper personalization, and improved performance. However, automation alone does not guarantee success—careful strategy and active involvement of marketers are essential.

What Generative AI Can Do in Google Ads Copywriting

Generative AI is no longer just an auxiliary tool—it has become a true “engine” for creating Google Ads copy. Its capabilities cover the entire process, from initial ideation to large-scale personalization and optimization.

Accelerating Ideas and Drafts

Instead of spending hours brainstorming and manually crafting ad copy, AI can generate dozens of headline and description variations in seconds.

It can:

• Change the approach (informational, emotional, humorous, etc.)
• Work with different tones—from formal to friendly
• Suggest a variety of calls to action (“Learn more,” “Try for free,” “Order today”)

This not only saves time in the initial creative phase but also allows marketers to quickly explore multiple ways to present the same offer.

Personalization at Scale

One of the biggest challenges of traditional copywriting is adapting messages for different audience segments. Generative AI solves this by leveraging user data:

• Demographics (age, gender, location)
• Behavioral data (purchase history, page views)
• Interests and intentions

For example, a single product like running shoes can have two completely different messages:

• For beginners—focus on comfort and injury prevention
• For experienced runners—emphasize lightweight design and advanced cushioning technologies

Improving Ad Strength and Quality Score

Google favors ads that are unique, relevant, and diverse. AI can quickly generate a large number of variations:

• Including relevant keywords
• Avoiding repetition and template-like phrasing
• Offering diverse messages across ad groups

This can significantly impact Ad Strength and Quality Score, thereby improving visibility and lowering cost per click.

More Efficient A/B Testing

Traditional A/B testing requires creating multiple copy versions manually. AI enables:

• Instant generation of dozens of variations
• Rapid test deployment
• Quick identification of the best-performing combinations

This is especially valuable in highly competitive niches where speed and adaptability are crucial.

Overcoming Language Barriers

For brands running campaigns in multiple markets, AI serves as a “translator and localizer in one.” It can adapt copy while considering:

• Cultural nuances
• Local expressions
• Audience-specific language styles

For instance, a slogan that works well for an English-speaking audience can be reformulated for Ukraine while maintaining natural phrasing and emotional impact.

The Key to Success: High-Quality Prompts

The effectiveness of AI-generated copy depends directly on the quality of prompts. Think of yourself as a conductor, and the AI as the orchestra—the more precise the “sheet music,” the better the result.

• Experiment: Rarely does the perfect copy come on the first try. Test different prompt structures, add context, and refine instructions based on AI outputs.
• Be specific: Instead of a general “Write ad copy for shoes,” use:
  “Generate 5 headlines and 3 descriptions for lightweight running shoes aimed at beginner runners, highlighting comfort and injury prevention. Use an encouraging, energetic tone. Include keywords like ‘lightweight running shoes,’ ‘beginner runner comfort,’ ‘injury prevention.’”
• Provide examples: Feeding existing high-performing ads helps AI understand your brand voice and style.
• Set constraints: Specify character limits, mandatory calls to action, or disclaimers to ensure outputs are ready for Google Ads.

Human Oversight Is Non-Negotiable: The Editor’s Touch

Generative AI is a powerful assistant, but not a replacement for human creativity and judgment. Every AI-generated ad copy should undergo thorough review.

• Maintain brand voice: AI can drift from your established style. Adjust wording to align with your tone and guidelines.
• Verify accuracy: AI can “hallucinate” or use outdated information. Double-check all claims, prices, and product details.
• Ethics and bias: Review content for stereotypes, manipulative language, or discriminatory phrasing.
• Emotional nuance: AI can generate compelling copy, but understanding subtle emotional triggers gives a competitive edge.
• Legal compliance: Ensure adherence to advertising laws, Google Ads policies, and intellectual property rules.

Strategic Integration: AI as Part of Your Workflow

Generative AI should be seamlessly integrated into your Google Ads workflow rather than treated as a standalone tool.

• Use Google’s built-in AI features: Leverage automatic campaign ideas, headline, and description suggestions based on landing page content.
• Leverage performance data: Connect AI tools with Google Ads analytics to optimize copy based on real-world results.
• Focus on Responsive Search Ads (RSA): These ads are ideal for the multiple variations AI can produce.
• Consider the full user journey: Ensure AI-generated copy aligns with landing page content to maintain relevance and maximize conversions.

Continuous Learning and Adaptation

The AI landscape evolves rapidly, and your strategy should too.

• Monitor performance: Track CTR, conversion rates, and Quality Score for AI-generated copy to refine prompts and optimization strategies.
• Stay updated: Keep up with new AI models and features to enhance campaigns further.
• Experiment responsibly: Test different tools and methods to determine what works best for your brand.

Ethics: Responsible Use of AI in Advertising

Responsible AI usage is crucial to protect brand reputation, user trust, and comply with legal standards.

• Transparency: Disclose if AI significantly influenced ad copy. This builds trust, especially in B2B marketing.
• Data protection: Use only legally collected data in compliance with GDPR, CCPA, and other regulations.
• Bias mitigation: Regularly review AI-generated content to avoid stereotypes and discriminatory language.
• Social responsibility: Avoid harmful or misleading content and consider the psychological impact on the audience.
• Continuous improvement: Update internal policies and workflows to align with evolving AI standards and best practices.

The Future of Google Ads: AI Under Human Control

Generative AI opens new horizons for Google Ads, enabling faster creation, deeper personalization, optimized A/B testing, and international scalability.

Its effectiveness, however, depends on human oversight—ensuring accuracy, brand consistency, ethical standards, and legal compliance. AI complements marketers, allowing them to focus on strategic decisions and creative approaches.

Responsible use of AI, combined with transparency, data protection, and bias mitigation, is essential for building trustworthy campaigns.

Marketers who learn to harness AI power while applying human judgment will gain a competitive edge, creating ads that are not only effective but also trusted by their audiences.

Ultimately, the future of Google Ads is a synergy of AI and human guidance, where technology works for people, not instead of them.

This article available in Ukrainian.