AI-enabled advertising to form 90% of total ad revenue and reach $1.3 trillion by 2032: GroupM study

GroupM has published a new study titled “The Next 10: Artificial Intelligence”.

According to the report, artificial intelligence-enabled advertising is estimated to become more than $370 billion this year and is likely to form the vast majority of media by 2032, reaching $1.3 trillion, or more than 90% of total ad revenue.

This study examines how the media landscape and consumer behaviour will shift over the coming decade, in large part due to AI-enabled advertising that likely already accounts for nearly half of all advertising revenue, or more than US$300 billion.

Some major implications emerging with the rise of AI

• The declining reach of linear TV and less tolerance of irrelevant, interruptive ad pods.
• The growth of audio-first devices with digital assistants (e.g. earbuds and smart home speakers) means that voice search will overtake text-based search.
• Data will most often be managed on-device and will be increasingly obfuscated or anonymised by AI and privacy services.

Takeaways from the report across a few categories:

• Advances in AI and these evolving media channels could result in marketers increasingly tying together products, consumer experiences and advertising experiences:
• Automotive: The use of generative AI and digital twins will enable greater personalisation of advertising in the sector—i.e.: a custom colour model shown driving in the buyer’s own city.
• CPG: Machine learning paired with genomic sequencing will make personalised nutrition and personal care products increasingly possible.
• Apparel: Computer vision, machine learning algorithms and generative AI could disrupt the apparel and retail industry by creating a vast grey market of copycat goods or user-generated designs competing for image searches.
• Entertainment: Personalised storytelling could become a reality as ads and IP are customized based on audience data and/or selections.

The Next 10 also raises “Ethical and responsible AI” questions such as:

1. How do we protect at-risk users and all consumers from AI that exploits dark patterns or behavioural “hacks”?
2. What are the ways we can protect against the weaponisation of AI in advertising tools and platforms used to amplify misinformation, deep fakes, fraud and abuse?
3. What is our level of comfort with what remains hidden in the black box of machine learning?
4. Should people be notified when they’re speaking or chatting with an AI chatbot and not a human?
5. How do we build safety and accountability into algorithmic incentives?
6. How should disclosures about the use of AI in advertising work?

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