Is Artificial Intelligence Really a Threat to the Value of the World's Leading Marketplaces?
- 10 hours ago
- 5 min read
After a record-breaking year for M&A in 2025, the global classifieds sector came to an abrupt halt toward year-end. The inflection point was sharp share price corrections at two industry benchmarks, UK-listed Rightmove and Auto Trader, driven by investor fears over AI-led disruption. Deal activity has since stalled, and C-level executives at leading platforms face mounting pressure to articulate a credible response. The question for both operators and investors is the same: are these fears justified, or is this the latest chapter in a long history of disruption threats that never quite materialized?
The contrast with earlier in the year is striking. 2025 saw some of the largest marketplace transactions ever: Adevinta's Spanish operations sold for over $2 billion, France's second-largest automotive platform to La Centrale for more than $1 billion, Boats Group at a ten-figure valuation. These deals reflected genuine confidence in a sector with double-digit revenue growth and EBITDA margins consistently above 30–40%. Assets like mobile.de, leboncoin.fr, Zoopla, and AVIV Group's European platforms were widely expected to follow. By late 2025, that pipeline had largely frozen.
AI as a Potential Structural Disruptor
Rightmove's November 2025 sell-off said a lot about where investor sentiment had moved. The company announced plans to invest tens of millions of pounds in AI while guiding for operating profit growth of just 3–5% in 2026 — well below expectations. The stock dropped 25–28% intraday. Auto Trader followed with a 10–11% correction on softer guidance, and found itself tarred with the same brush.
Rightmove PLC Share Value Evolution
Source: London Stock Exchange, data from Jan 1, 24 to March 28, 26
Autotrader Group Share Value Evolution
Source: London Stock Exchange, data from Jan 1, 24 to March 28, 26
The underlying fear is disintermediation. If AI assistants and aggregators increasingly own the search and discovery experience — sourcing listings, comparing options, guiding decisions — platforms risk becoming invisible infrastructure rather than destinations. For anyone running a marketplace, the implications are familiar and uncomfortable: weaker pricing power, higher customer acquisition costs, margin pressure, and a gradual erosion of the network effect that makes these businesses so valuable in the first place.
Both stocks have partially recovered, but valuations remain below prior highs. The market is, in effect, asking platform leaders a direct question: what's your plan for staying relevant in an AI-mediated world?.
A Familiar Narrative of Overestimated Disruption?
Before drawing conclusions, it's worth taking a step back. This sector has faced serious disruption threats before, and has a surprisingly strong track record of absorbing them.
Google tested direct listing integrations in real estate and automotive in the US and Australia in the early 2010s, then walked away. Facebook launched Marketplace globally in 2018 with real ambition, gained traction in peer-to-peer, but never cracked professional listings monetization and faded into a secondary role in most markets. Amazon is now making noise in automotive, but its focus on new vehicle partnerships touches only a small slice of a market still dominated by used transactions
The one genuinely transformative moment was the mobile shift in the late 2000s, which gave rise to app-native challengers like Letgo, Shpock, and Wallapop. Even then, none displaced the incumbents at scale. The platforms that did find durable footing — Wallapop refocusing on Spain, Vinted growing from fashion into a broader European marketplace — got there through vertical focus, local depth, and patience. Not by outspending incumbents on technology.
The pattern is consistent: incumbents that defended their positions did so by going deeper, not broader. That lesson hasn't aged.
Are the Barriers to Entry Still Too High for AI?
So will AI leaders — OpenAI, Google DeepMind, Anthropic — actually prioritize classifieds? Honestly, it seems unlikely to be their primary focus. Compared to digital advertising, enterprise software, or productivity, classifieds is fragmented, local, and relatively modest in addressable scale. The opportunity cost of sustained focus here is real for global AI players.
The structural barriers are also more significant than they might appear from the outside. Classifieds — especially in real estate and automotive — aren't just data businesses. They're deeply embedded in physical, high-touch economies. Car dealerships have forecourts. Estate agencies have high streets. Transactions involve viewings, test drives, negotiations, and face-to-face relationships. The leading classifieds platforms have spent years building real, human relationships with these clients — account managers who know their dealers personally, sales teams embedded in local markets, support structures built around the rhythms of physical businesses.
That relational layer is genuinely hard to replicate. It's not in the data. It's not in the algorithm. And it's not something a well-funded AI entrant can shortcut.
The operational complexity compounds this. Take mobile.de and leboncoin.fr — widely expected to be the most significant classifieds assets to come to market in the next two years. Mobile.de aggregates listings from hundreds of heterogeneous dealer management systems. Leboncoin's automotive vertical still relies partly on manual uploads from professional sellers, and its real estate data flows involve dozens of agency networks and over a hundred different software providers. For an AI entrant, this isn't a product challenge — it's a sustained operational commitment that runs against the asset-light, scalable models AI companies are built around.
For incumbents, this complexity isn't a problem. It's the moat. The strategic implication is to lean into it: deepen integrations, strengthen those real-world client relationships, and make the platform progressively harder to bypass.
On disintermediation specifically, the legal picture is also more protective than current market sentiment suggests. European, UK, and US frameworks generally require aggregators to redirect users to source platforms. Platforms can restrict indexing. Evolving case law is increasingly recognizing database rights that limit how listings data can be commercially exploited. Proactively reinforcing these protections — through terms of service, API access policies, and scraping monitoring — is quietly becoming a strategic priority for the sharpest platform teams.
What Should Operators Do?
For classifieds executives, the right response to AI isn't panic — and it isn't complacency either. It's a clear-eyed dual agenda: defend the moat, and selectively use AI to extend it.
On defense:
Double down on professional lister relationships. Invest in the account management and local presence that no AI entrant can easily replicate. Strengthen data infrastructure to make proprietary listing content richer and harder to commoditize. And get ahead of the legal framework around data rights rather than reacting after the fact.
On offense:
AI can genuinely improve the core experience — smarter search, better matching, more personalized recommendations — in ways that deepen platform engagement rather than eroding it. Rightmove's strategic pivot, whatever the short-term market reaction, reflects a real recognition that standing still isn't an option. The goal is to deploy AI in ways that reinforce structural position, not undermine it.
Disclaimer: This article was written using Joreca’s data, public information, and expert opinion. Under no circumstances does this article constitute a solicitation, offer, opinion, approval nor recommendation by Joreca, to buy or sell any company share, nor does it provide legal, tax, accounting or investment advice, nor services regarding the profitability or suitability of any security or investment.
