Throughout 2022, digital marketers evaluated their carbon footprint, looking for ways to reduce the environmental impact of ad campaigns. But as financial uncertainty grew, many sustainability initiatives were moved to the back burner.

Then ChatGPT was released, and suddenly everyone was experimenting with the new AI technology, looking for ways to reduce costs and improve efficiency and performance. Many marketers are already using AI technologies to create and optimize social media ads.

The industry now has the opportunity to use emerging AI technologies to not only create digital ads more efficiently, but to make them more sustainable. Here’s how:

Start with ChatGPT

Advertisers are accustomed to brainstorming ideas with agency and client teams across geographies. Instead of flying in people or connecting via Zoom, why not run brainstorming simulations on ChatGPT? It can save time and reduce your carbon footprint for initial brainstorming and idea sessions—running relevant queries based on what would have been your team meeting agenda, drilling down deeper based on the results generated.

Many marketers and agency teams are going beyond ChatGPT, turning to solutions including Seenapse for a range of marketing queries including copywriting and idea generation. Others rely on AI tools for market research such as Scholarcy to summarize articles and Bearly for research. Beyond research, some agencies use ChatGPT to automate their social media marketing including writing, scheduling and analysis.

Target media channels with a lower carbon footprint

If your research has proven that TV ads during the Olympics are the most effective for your brand, no one will tell you to stop advertising on TV because it results in a higher carbon footprint. But marketers can analyze the relevant carbon footprint of the various media channels they use and employ sustainability best practices to optimize carbon footprint across channels.

 Advertisers can make sure that most of their advertising has a lower carbon footprint. Strategies include running targeted ads to reduce ad-serving waste, by reducing the number of bidding partners at auctions and by serving ads during non-peak hours and days.

Tap into AI technology for ad production

There are technology-based tools that can help with the creation of ad texts and images for search, display, email and social media. These include Copy.AI, Jasper, Omnekey, Persado, Surfer SEO and Reply.io.

Such technology pulls data from a marketer’s various ad platform dashboards to evaluate the relative performance of the ads, ranking the best and worst-performing ad variables (images, videos, texts). Based on this analysis, the technology will create new ad units that should optimize ad performance according to the marketer’s KPIs. 

Marketers seeking sophisticated image creation and video ad campaigns can utilize technologies, including DALL·E 2, Mid Journey and Runway. Companies such as HourOne.ai and HeyGen specialize in the creation of presenter-led videos with virtual presenters in minutes. With video production a major contributor to increasing the carbon footprint of advertising campaigns, these technologies can significantly reduce a marketer’s carbon footprint while saving time, budget and other resources spent going on location for the shoot.

Recently, vegan food company NotCo used AI technology to show images of farm animals—including cows, pigs and chickens—at their natural life expectancy. By showing how these farm animals would look if they were allowed to age, NotCo is hoping to raise awareness for the company and a vegan diet.

Last year, Nestlé reframed Johannes Vermeer’s “The Milkmaid” painting, utilizing DALL-E2’s “outpainting” function to add new characters and details to the 360-year-old image in a campaign by Ogilvy Paris for the company’s La Laitière yogurt. Nestlé has long used milkmaid imagery to promote La Laitière, but the advancement in AI technology enabled re-envisioning the painting by including new, imagined background characters and settings.

Last summer, AQKA created an eight-minute video for Nike using AI technology to produce a match between 1999 Serena Williams, the year she won her first Grand Slam title, and 2017 Serena Williams, the year she won her record-breaking 23 Grand Slam title. The AQKA team used machine learning to model Serena’s playing style from 1999 and 2017 including decision-making, shot selection, reaction times, recovery and agility based on archived footage. The models were then re-rendered into the embedded video, playing and responding to each other’s shots.

Such implementations of AI technology serve as a reminder that these technologies can enhance creativity in advertising. While many creative and account people will lament going on fewer location shoots to exotic locales, AI technology will take ad creativity to places that the original Mad Men never dreamed of going. And if we can do it while making our industry more sustainable, then it’s a real win-win.