When used strategically and targeted, AI-generated imagery tools offer marketers new opportunities for content personalization and campaign engagement.
Marketers, designers, and users are increasingly utilizing AI-generated imagery platforms such as Flux, Runway, and DALL-E. In spite of all the options available, it's sometimes difficult to understand where and how these tools are actually useful.
AI-Generated Images: 3 Key Obstacles
AI image generation holds tremendous potential, but adoption is not without challenges. Three challenges prevent widespread use, in particular:
1. Concerns about privacy and security
Employees hesitate to engage with AI tools due to concerns about privacy, data security, and AI's current limitations. Additionally, many feel that AI is not yet "good enough" for their needs. Addressing these concerns begins with clear communication about AI's strengths and limitations. As long as teams understand where AI can add value - and where it can't - they're more likely to engage with it realistically.
2. Inconsistency in expectation
Users expect AI to "do it all," resulting in frustration when it falls short, especially for tasks that require precision. By managing expectations and educating teams on how AI works best, marketers can shift focus toward practical, achievable applications.
3. Guardrails are necessary
AI has such broad potential that many people struggle to find the right applications for it. A defined, structured approach — such as clear AI prompts or targeted use cases — helps ease adoption by giving employees a clearer sense of purpose. It can also be easier for teams to explore AI without feeling overwhelmed by using guided prompts or simplified interfaces for specific tasks.
AI-Generated Images in Marketing: 3 Use Cases
Despite these challenges, AI image tools are capable of making a significant impact when applied to targeted use cases. Using AI-generated imagery tools, we have been able to:
1. Enhance ad performance
One of the most effective applications of AI-generated imagery is creating tailored ad variations. Marketing professionals can deliver a more personalized experience across different platforms by using custom images aligned with specific ad copy. This approach, which HubSpot has tested, significantly boosts conversions, making it an invaluable tool for scaling our campaigns efficiently.
2. Make email more engaging
AI can also increase engagement in email marketing by generating unique images tailored to each message.Combined with AI-generated text, these visuals create a curated and relevant experience for readers, adding a layer of personalization that keeps content fresh and increases the chance of connecting with audiences in a deeper, more memorable way.This approach works particularly well when you need to create distinct visuals for different segments or campaigns at scale.
3. Reducing editing time
A technology company may use AI to alter product screenshots by adding a client's logo or emphasizing specific features to fit different audience needs. AI is equally useful for image editing. Using this strategy, brands can create more customized visual experiences without having to spend time and energy making manual edits, making it a powerful tool for creating content tailored to specific audiences.
AI Image Implementation Best Practices
When it comes to maximizing the value of AI-generated images, it is important to understand where and how to use them. By following these pointers, you will keep your approach practical and results-driven.
Establish clear use cases
Instead of trying to apply AI universally, define specific applications (like customer support or ad variations) where it can succeed.
Prioritize volume over perfection
It is easier for AI to create multiple variations of an image than to create a single "perfect" image. Stick with traditional methods if you need one flawless image.
Educate teams about AI's strengths and limitations
Setting clear expectations and providing guidance on where AI is most beneficial, which can help address privacy and reliability concerns, can help improve adoption.
Authenticity is key
Do not use AI-generated images to represent real people or customers, as this could damage trust. Visuals that are focused on concepts or products should be avoided when using AI imagery.