Incentives > Intelligence: The Real Barrier(s) to Agentic AI
A few days ago, I came across this reels through which I got to know about Amazon’s new “Buy For Me” feature. This feature, however, created some controversies. From Modern Retail:
“Amazon’s “Buy For Me” feature allows users to purchase products from third-party websites without leaving Amazon’s app or site. (Amazon also has a “Shop Direct” button that links out to brands’ third-party websites for customers to complete a purchase.) When products appear on Amazon through “Buy for Me,” they are shown alongside standard Amazon search results but are clearly labeled as coming from “other brands,” with a prominent button that says “Buy for Me.”
“Buy For Me” uses “agentic AI capabilities” to provide third-party websites with shoppers’ encrypted payment and shipping information, according to Amazon. Still, several merchants said that, to shoppers accustomed to scrolling Amazon’s marketplace, the listings can resemble a typical Amazon product page, potentially giving the impression that a brand is selling directly on Amazon, even if the transaction ultimately happens elsewhere.”
Amazon’s stance on agentic shopping does seem a little disingenuous albeit quite clever; on one hand, they are sending “cease and desist” letter to Perplexity preventing them to browse Amazon’s own marketplace whereas Amazon is automatically opting in all the individual third-party websites in their own search results unless those sellers email Amazon directly to opt out of the program. Amazon can perhaps still claim that they’re following the “golden rule” i.e. they’re treating others the same they would like to be treated. Just as they let anyone opt out of the program once they let Amazon know, Amazon also asks other AI agents to respect their wishes of not “trespassing” in their marketplace. Economically, Amazon’s position seems coherent. Amazon wants to remain the primary interface to shopping, which means resisting any external agent that weakens its control of the customer relationship and data. At the same time, Amazon also wants maximum selection which means reaching beyond its own inventory and pulling the rest of the web into Amazon’s interface. The key here is, of course, aggregating demand. Even Amazon’s position can be malleable to third-party agents if they start suspecting they’re losing a rising fraction of sales by not allowing 3P agents.
Such “disingenuous yet clever” strategy is actually a good glimpse of the barrier to agentic AI’s adoption. While most of us focus too much on technical capabilities of AI, we may still be underestimating the challenges related to (lack of) incentives of incumbents as well as legal frameworks for agentic AIs to flourish. “Ghosts of Electricity” had a very good piece explicitly laying out couple of real headaches:
“we highlight two main obstacles that stand in the way of AI agents becoming true digital partners. The first has to do with the design of the internet itself–the interface of nearly every website was meticulously optimized for humans. But what works for humans does not necessarily work for AI agents. Until AI can truly emulate every aspect of a human being, we will likely need to design a parallel internet for agentic commerce to work. But there’s reasons to suspect that this will not happen soon: some firms have little to gain, and potentially much to lose, from investing and facilitating a machine-readable web. This leads us to the second obstacle, which is even simpler: many use-cases for AI agents are illegal, or at least legally ambiguous. The rights around AI agents need to be clarified and developed in order for agents to participate meaningfully in economic transactions and interactions.”
In the piece, they substantiated these headaches with a couple of examples. Some excerpts below:
“Let’s say you tell your favorite AI tool (ChatGPT Atlas, Perplexity Comet, Claude, Gemini Antigravity) to purchase a concert ticket for you or to shop on Amazon. Take seat selection. The agent reaches the seat map and gets stuck because it can’t tell what’s actually available or what counts as a “good” choice. The map isn’t a simple list: seats change color when you hover, prices only appear after clicking, and availability updates every second as other people buy tickets. While the agent pauses to figure out what to do, the seat disappears, the page refreshes, and it loses its place. Every pause, waiting for pages to load, retrying after errors, handing control back to you, adds friction. What takes a human a few minutes to do turns into a brittle, ten-minute ordeal
…Imagine you deploy an AI agent to shop for you. The agent logs into your Booking.com account using your credentials, stored locally on your device. It browses hotels, compares prices, and completes a purchase—all at your explicit direction, acting solely on your behalf.
Have you done anything wrong? Has your agent?
The answer is surprisingly unclear, and the current legal framework is not favorable to agents. The core question is whether a BYO agent inherits your rights to access a website. You, as a human, can browse Booking. You agreed to their Terms of Service. Does your agent automatically have the same permission?”
Some of these may seem trivial issues that will be ironed out over time, but remember these are not just technical questions which would indeed probably be solved via more compute, data, and better algorithm. But solving incentives when every incumbent is hyperaware of their share of profit pool can delay your AI timeline to an extent that can surprise most AI researchers.
In addition to “Daily Dose” (yes, DAILY) like this, MBI Deep Dives publishes one Deep Dive on a publicly listed company every month. You can find all the 65 Deep Dives here
Current Portfolio:
Please note that these are NOT my recommendation to buy/sell these securities, but just disclosure from my end so that you can assess potential biases that I may have because of my own personal portfolio holdings. Always consider my write-up my personal investing journal and never forget my objectives, risk tolerance, and constraints may have no resemblance to yours.
My current portfolio is disclosed below: