ARK Investment Management LLC predicts that AI agents will influence up to $9 trillion of global online sales of consumer goods and services by the end of the decade.
This number is almost negligible today.
In their recent research, "Generative AI: A New Consumer Operating System" they shared valuable insights into the future of AI in consumer technology.
One key insight is the potential for search engines to ban AI-led traffic from specific operating systems, and likewise, for marketplaces to ban traffic from certain search engines due to competitive concerns.
"If consumers come to rely on AI engines instead of manual research, search engines, marketplaces, and independent websites will lose significant traffic and ad impressions as AI agents take control of the most valuable ad impressions during the transaction process."
However, the blog also suggests that, in the long run, "AI agents at the operating system level will aim to maximize consumer utility, encouraging most marketplaces to offer their inventory through these agents."
Yes, it's no secret that a significant portion of our consumption decisions will be influenced by AI agents in the future.
But, how will these agents shape the way we are influenced and make purchasing decisions?
Personalization is no longer just a buzzword, nor is it limited to changing the color of a landing page based on predictive user anaysis.
Now, let's break down the mechanisms of AI agents in advertising, as illustrated by the authors:
Traditional Online Shopping Experience:
Awareness Phase:
The user initiates the process with a search query, typically typed into a search engine.
Discovery + Research Phase:
The user explores the search results, often clicking on links to marketplaces or merchant websites.
This phase can involve multiple iterations, with the user navigating back and forth between the search engine and various merchant sites.
Ad Opportunities:
During this process, the user encounters numerous ads, both on search engines and merchant websites, providing abundant opportunities for digital ad impressions.
Checkout:
Once the user finds their desired product, they proceed to checkout.
AI-Agent Powered Online Shopping Experience:
Awareness Phase:
The user initiates the process with a text or voice command to their personalized AI agent, integrated into their device or operating system.
Autonomous Discovery + Research Phase:
The AI agent takes charge, querying multiple search engines and marketplaces simultaneously.
Curated Results:
The AI agent compiles and presents refined results, reducing the user's active involvement in discovery and research.
Checkout:
The user reviews the curated results and proceeds to checkout, similar to the traditional process.
So, what are the key differences and implications?
First, efficiency:
The AI agent-powered process offloads the discovery and research burden from the user to the agent, enhancing efficiency and saving time.
Ad Opportunities in the Traditional Model:
The user is exposed to multiple ads throughout their journey across search engines and merchant sites.
Ad Opportunities in the AI Model:
More limited and concentrated within the AI agent's curated results, reducing ad impressions.
In the traditional model, the user actively engages in each step, requiring more effort and time.
The AI-powered model offers a streamlined process where the user delegates most tasks to the AI agent, potentially improving the overall user experience.
The digital advertising ecosystem is indeed poised for substantial disruption due to the increasing role of AI assistants.
This will result in a reduction of advertising opportunities in search results, on marketplace platforms, and on independent websites.
To maintain user trust, AI agents will need to curate advertising content that is natural, unobtrusive, and respectful of user privacy.
Two anticipated forms of AI agent advertising are:
- Retrieval-based ads: Targeted ads presented alongside organic curation, similar to today's search ads.
- Active intent-generation ads: Personalized recommendations based on user-authorized data from various sources.
With these developments, the influence of AI agents in consumer spending will grow, and AI-facilitated ad spend is projected to reach an astonishing $9 trillion globally by the year 2030.
AI agents are estimated to extract more than $800 billion in intermediation revenue from this massive ad spend.
Now, let's turn our attention to another valuable insight from the blog: Voice and Natural User Interfaces (NUIs).
Voice-centric NUIs, coupled with real-time data from AI wearables, will take personalization to the next level, transforming hardware into predictive assistants.
Voice is becoming the new medium obviously.
However, voice and AI wearables are expected to augment rather than replace smartphones, as privacy concerns and the need for audiovisual entertainment will likely maintain the demand for screens.
Lastly, let's consider the potential category winners and platform strategies brought to us by ARK researchers.
The shifts in market share between PC and mobile operating systems suggest that winning consumer hardware platforms will employ varied strategies.
Vertical integration has proven more successful than licensing models, as evident by the dominance of Apple, Google, and Microsoft in terms of market share and ecosystem profits.’
Established tech giants like Apple, Google, Microsoft, and Meta possess significant advantages, including their vast ecosystems, data and AI capabilities, and extensive distribution networks.
"By strategically incorporating AI, these companies could further strengthen their moats. Apple could enhance user experiences with more personalized and intuitive interactions. Google could make its services even more indispensable by leveraging its data and AI expertise. Microsoft could solidify its leadership in both consumer and business markets by boosting productivity and enterprise solutions with AI. Meta could revolutionize user engagement and experiences across its social platforms and VR environments with AI-driven content, advertising, and immersive interactions."
However, the paper also highlights the potential for new entrants, such as Humane Ai Pin and Rabbit R1, to disrupt the market by focusing on consumer-centric innovations that extend beyond the ecosystems of the current leaders, offering user-friendly designs that cater to unmet needs.
It's super exciting to consider the role of AI agents in our purchasing decisions and how this might evolve in the near future.
AI agents will save us time, provide personalized recommendations, and even negotiate better deals.
So, what do you think?
Are you open to the idea of AI agent-powered spending, or do you prefer to maintain control over your purchases?
Have you had any positive or negative experiences with AI-assisted shopping thus far?
