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Appen says seven of eight top AI labs now use it

Tom Mercer by Tom Mercer
October 31, 2026
in Enterprise
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Photo: MDRX / Wikimedia Commons (CC BY-SA 4.0)

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For most of the past five years, Appen has been a cautionary tale rather than a growth story. The Sydney-based data-services company, listed on the ASX under the code APX, rode the first wave of machine learning to a share price above $40 in 2020, then watched almost all of that value evaporate as its biggest technology customers pulled spending and built more of their own data pipelines in house. So when the company says it now supplies seven of the eight leading artificial intelligence laboratories in the world, it is worth pausing to ask whether the recovery is finally grounded in something durable.

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The claim comes via financial commentary site Stocks Down Under, which framed the development as a test of whether Appen’s long-promised turnaround is at last real. The headline figure, that Appen counts seven of the top eight AI labs among its customers, speaks to a business that sits quietly behind the generative AI boom. Appen does not build the large language models that power tools like chatbots and image generators. Instead it supplies the human-labelled data and human feedback those models are trained and refined on, the unglamorous but essential raw material of modern AI.

From near-death to relevance

To understand why this matters, it helps to recall how far Appen fell. The company’s model was built on collecting and annotating data for a handful of very large customers, with a heavy reliance on the biggest American technology platforms. When those platforms tightened their advertising budgets and reduced outsourced data work, Appen’s revenue collapsed. There were capital raisings, cost cuts, a scrapped takeover approach from Canada’s Telus in 2023, and persistent questions about whether the business could survive as an independent entity. The share price spent long stretches below a dollar, and the company was dropped from major indices.

The generative AI surge has changed the backdrop. Training a frontier model and keeping it useful requires enormous volumes of carefully prepared data, and increasingly it requires skilled humans to rate model outputs, write ideal responses and catch errors, a process known as reinforcement learning from human feedback. That work has grown more specialised and higher value than the simpler image-tagging tasks that once dominated the sector. Appen has repositioned itself towards this generative AI data work, and management under chief executive Ryan Kolln has pointed to that pivot as the engine of its recovery.

The bull case and the sceptics

Supporters of the stock argue that being embedded with almost every leading lab is exactly the position you would want in an industry pouring tens of billions of dollars into model development. If demand for high-quality training data keeps climbing alongside AI investment, a trusted supplier with existing relationships should benefit regardless of which lab ultimately wins the model race. On that reading, Appen has quietly become a picks-and-shovels play on the entire sector rather than a bet on any single customer.

The sceptics are not hard to find, and their caution is well earned. Serving seven of eight labs is impressive as a logo slide, but it says little about how much each of those labs actually spends, how sticky the contracts are, or how exposed Appen remains to a small number of very large clients that could again cut back without warning. The company has been badly burned by customer concentration before. There is also a structural question hanging over the whole data-labelling industry: as models grow more capable, some of the work of generating and checking training data can be automated by the models themselves, which could compress the very margins Appen is trying to rebuild. A list of marquee clients does not by itself prove that revenue and profit are following.

Why Australia should watch

For Australian readers, Appen is more than one volatile small-cap among many. It is one of the very few homegrown companies with a genuine, long-standing foothold in the global AI supply chain, and its fortunes have become a kind of barometer for whether an Australian firm can carve out a defensible niche in an industry dominated by American capital and American labs. The company’s recovery, if it holds, would be a rare local success in applied AI infrastructure rather than in flashy consumer apps.

It also lands at a moment when Australian policymakers and investors are openly debating the country’s place in the AI economy. There is heavy local attention on data centres, sovereign computing capacity and the risk of Australia becoming a pure consumer of overseas technology. A company that sells the human-in-the-loop services the world’s top labs depend on offers a different template for participation, one built on expertise and trusted data operations rather than on raw capital spending. For ASX investors who have watched offshore AI names run hard, Appen is also one of the few ways to get direct local exposure to the theme, which is part of why every update on its client base draws outsized interest.

There is a sovereignty angle too. The quality, provenance and labour conditions behind AI training data are becoming regulatory and ethical issues in their own right, and having a listed, locally governed player in that supply chain gives Australia a seat at a conversation that is otherwise happening almost entirely overseas.

What’s next

The real verdict will come in the numbers rather than the narrative. Investors will be watching Appen’s next financial update for evidence that the client wins are translating into sustained revenue growth, improving margins and, eventually, consistent profitability rather than a single good quarter. Guidance on customer concentration, the mix between legacy data work and higher-value generative AI projects, and cash generation will matter more than any count of logos.

For now, Appen has reclaimed a genuine seat at the table of the AI boom, serving almost all of the labs building the technology that is reshaping the global economy. Whether that translates into a durable turnaround, or proves to be another false dawn for a company that has had several, is the question that will define its next year. After half a decade of disappointment, the burden of proof sits firmly with management.

Sources: Stocks Down Under.

Tags: AI training dataAppenASXenterprise AIgenerative AISydneyTurnaround
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Tom Mercer

Tom Mercer

Tom covers enterprise AI adoption, government and policy for FluentSea.

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