Coca-Cola, Volvo air AI ads; $2K NBA spot in 3 days

Major consumer and tech brands have quietly begun airing commercials made entirely or substantially by AI, marking a shift from experimental testing to mainstream adoption. Coca-Cola used AI to reimagine its holiday campaign, building wintry, atmospheric cityscapes without a traditional shoot. Volvo created fully AI-generated spots designed to localize campaigns quickly for regional markets, including Saudi Arabia. Toys "R" Us generated an origin story video about its founder and the brand's mascot, Geoffrey the Giraffe, using synthetic storytelling. Most strikingly, Kalshi, a prediction market platform, aired a surreal AI-made commercial during the NBA Finals featuring cowboys and aliens that cost roughly $2,000 and took just three days to produce—a timeline and budget that would be impossible with a traditional crew and location shoot.

The technology is not monolithic in its results. Some AI-generated ads are polished enough to run on television next to traditionally shot spots without standing out. Others deliberately embrace their algorithmic strangeness; the Kalshi spot, for example, gets shared specifically because it looks a little off, and that oddness functions as a hook on social media. Many AI commercials have developed their own genre of surreal, slightly-off humor that performs well on platforms like TikTok and Instagram even though they might not pass a traditional creative review. At the same time, the article warns that a surge of low-quality "AI slop" promoting dropshipped goods has eroded audience trust, and some highly polished AI spots have drawn backlash for lacking emotional warmth.

For marketing teams deciding whether to adopt AI, the stakes of the ad matter more than the technology itself. A 30-second product demo for paid social testing carries far less risk than a national TV spot tied to core brand identity. High-volume performance ads, social tests, and localized variations are where AI saves the most money for the least risk. The production workflow typically flows through four stages: concept and script (defining audience, hook, and shot list before generating), footage generation (using tools like Runway's AI video generator to turn text or image prompts into scenes), adding voice and sound (with AI voiceover tools generating narration in multiple languages and AI music tools building custom scores), and editing and assembly (using text-based or AI-assisted editors to cut and resize for every platform). Teams must decide between in-house production—which makes sense for high volume and rapid testing but requires internal skill development—and agency work, which is better for campaigns where creative direction and legal review matter more than speed. Many production companies now build AI into their workflows rather than treating it as a threat, using it to generate more concepts while reserving human crews for shots AI cannot yet handle.

The regulatory environment is crystallizing. In the US, the FTC applies existing deceptive-advertising and endorsement rules to AI-generated content and in 2026 clarified a "double disclosure" requirement: brands must disclose both a paid partnership and AI involvement when both apply. New York requires disclosure of AI-generated synthetic performers in advertising, and other states are expected to follow. The EU AI Act adds its own disclosure requirements for AI-generated content starting in August 2026. Looking forward, the article identifies two major shifts: first, personalization at scale, where brands will generate dozens of versions of a single hero spot tailored to region, platform, or even individual viewer—something production budgets could never support with traditional shoots but that AI makes economically viable. Second, AI-generated work is starting to clear the same broadcast-ready bar and compliance standards as other professionally produced content, embedding it deeper into mainstream advertising workflows.