The generative AI boom should have been Appen’s time to shine. Here’s what went wrong
Jonathan Raa | Nurphoto | Getty Images
Mike Monegan saw the writing on the wall in January. For weeks, he’d had difficulty sleeping.
As vice president of product management for Australian artificial intelligence software vendor Appen, Monegan and many of his colleagues had been doing their best to keep things afloat as tech behemoths slashed their spending on the company’s AI training data.
Five customers — Microsoft, Apple, Meta, Google, and Amazon — accounted for 80% of Appen’s revenue, and this was supposed to be the company’s moment to shine. Across the industry, companies were committing to hefty investments in generative AI, trying to ensure they weren’t left behind in the sudden race to embed the latest large language models into all of their projects.
Appen has a platform of about one million freelance workers in more than 170 countries. In the past, it’s used that network of people to train some of the world’s leading AI systems, working for a star-studded list of tech companies, including the top consumer names as well as Adobe, Salesforce and Nvidia.
But just as AI’s big moment was arriving, Appen was losing business — and fast. Revenue declined 13% in 2022, a drop the company attributed in part to “challenging external operating and macro conditions.” Former employees, who asked not to be named for fear of retaliation, told CNBC that the company’s current struggle to pivot to generative AI reflects years of weak quality controls and a disjointed organizational structure.
In mid-December, Appen announced a change at the top. Armughan Ahmad, a 25-year veteran of the tech industry, would be taking over as CEO, replacing Mark Brayan, who had helmed the company for the prior seven years. Upon starting the following month, Ahmad called generative AI “one of the most exciting advancements” in the industry and noted that he “was happy to learn that our team has already put the technology to work on our marketing content.”
Monegan wasn’t buying it. He told CNBC that after his first meeting with Ahmad he began looking for another job. Monegan had been watching Appen fall behind, and he didn’t see Ahmad, whose LinkedIn profile says he’s based in Seattle, presenting a realistic path out.
Monegan left in March to help start his own company.
The numbers seem to prove him right.
Despite Appen’s enviable client list and its nearly 30-year history, the company’s struggles have intensified this year. Revenue in the first half of 2023 tumbled 24% to $138.9 million, amid what it called a “broader technology slowdown.” The company said its underlying loss widened to $34.2 million from $3.8 million a year earlier.
“Our data and services power the world’s leading AI models,” Ahmad said on last week’s earnings call. “However, our results are far from satisfactory. They reflect the ongoing global macroeconomic pressures and continued slowdown in tech spending, particularly amongst our largest customers.”
In August 2020, Appen’s shares peaked at AU$42.44 on the Australian Securities Exchange, sending its market cap to the equivalent of $4.3 billion. Now, the stock is trading at around AU$1.52, for a market cap of around $150 million.
‘Resetting the business’
Along with its troubled financials, the company is dealing with a string of executive departures. Helen Johnson, who was appointed finance chief in May, left after just seven weeks in the role. Marketing chief Fab Dolan, whose departure was announced on the earnings call, spent just over two months in the position. The departure of Chief Product Officer Sujatha Sagiraju was also just announced.
“In the environment of a turnaround, we anticipate changes,” a representative for Appen told CNBC.
Elena Sagunova, global human resources director, left in April, followed by Jen Cole, senior vice president of enterprise, in July and Jukka Korpi, senior manager of business development for the Europe, Middle East and Africa Region, in August.
Still, Ahmad said on the earnings call that the company remains “laser-focused on resetting the business” as it pivots to providing data for generative AI models. He added that “the benefits from our turnaround have yet to show meaningful results” and that “the revenue growth does not offset the declines we are experiencing in the remainder of the business.”
Appen’s past work for tech companies has been on projects like evaluating the relevance of search results, helping AI assistants understand requests in different accents, categorizing e-commerce images using AI and building out map locations of electric vehicle charging stations, according to public information and interviews conducted by CNBC.
Appen has also touted its work on search relevance for Adobe and on translation services for Microsoft, as well as in providing training data for lidar companies, security applications and automotive manufacturers.
Depending on the data that a customer requires, an Appen freelancer could be sitting at a laptop to label or categorize images or search results or using Appen’s mobile application to capture the sounds of glass breaking or background noise in a vehicle.
During Appen’s growth years, that manual collection of data was key for the state of AI at the time. But LLMs of today have changed the game. The underlying models behind OpenAI’s ChatGPT and by Google’s Bard are scouring the digital universe to provide sophisticated answers and advanced images in response to simple text queries.
To fuel their LLMs, which are powered largely by state-of-the-art processors from Nvidia, companies are spending less on Appen and a lot more on competitive services that already specialize in generative AI.
Ahmad told CNBC in a statement that, while the company’s financials are being hurt by the economy and a reduction in spending by top customers, “I’m confident that our disciplined focus and the early progress we are making to turn around the business will enable us to capture value from the growing generative AI market and return Appen to growth.”
Cash-strapped
Ahmad said on the earnings call that there’s customer interest in niche types of data that’s more difficult to acquire. For Appen, that would mean finding specialists in particular types of information that can bolster generative AI systems. That also means it needs to expand its base of workers while simultaneously finding ways to preserve cash.
Appen’s cash on hand was $55 million as of June 30, thanks to proceeds from a $38 million equity raise. Prior to the new infusion, cash had been dwindling, from $48 million at the end of 2021 to $23.4 million a year later.
Even before the generative AI transition, wages for Appen’s data labelers were a sticking point. In 2019, Google said its contractors would need to pay their workers $15 an hour. Appen didn’t meet that requirement, according to public letters written by some workers.
In January, after months of organizing, raises went into effect for Appen freelancers working on the Bard chatbot and other Google products. The rates went up to between $14 and 14.50 per hour.
That wasn’t the end of the story. In May, Appen was accused of squeezing freelancers focused on generative AI, allotting strict time limits for time-consuming tasks such as evaluating a complex answer for accuracy. One worker, Ed Stackhouse, wrote a letter to two senators stating his concerns about the dangers of such constrained working conditions.
“The fact that raters are exploited leads to a faulty, and ultimately more dangerous product,” he wrote. “Raters are not given the time to deliver and test a perfect AI model under the Average Estimated Time (AET) model they are paid for,” a practice that “leads raters to spot check only a handful of facts before the task must be submitted,” he added.
In June, Appen faced charges from the U.S. National Labor Relations Board after allegedly firing six freelancers who spoke out publicly about frustrations with workplace conditions. The workers were later reinstated.
Appen employees who spoke to CNBC on behalf of the company in recent months said the rapidly changing AI environment poses challenges. Erik Vogt, vice president of solutions at Appen, told CNBC in May that the sector was in a state of flux.
“There’s a lot of uncertainty, a lot of tentativeness for experimentation, and new startups trying out new things,” Vogt said. “How to make new use cases a reality usually means acquiring unusual data – sometimes astronomical volumes of data, or highly rare resource types. There’s a need for specialists in a wide range of different capabilities.”
For recent projects, Vogt said Appen needed to enlist the help of doctors, lawyers and people with experience using project-tracking software Jira.
“People you wouldn’t necessarily think of as being gig workers, we had to engage with these specialists for these expert systems in a way there hadn’t been a huge demand for before,” Vogt said.
Kim Stagg, Appen’s vice president of product, said the work required for generative AI services was different than what the company has needed in the past.
“A lot of work we’ve done has been around the relevance of search for big engines – a lot of those are more, ‘Is this a hot dog or not,’ ‘Is this a good search or not,'” Stagg said. “With generative AI, we see a different demand.”
One focus Stagg highlighted was the need to find “what we would call really good quality creative people,” or those who are particularly good with language. “And another is domain experts: sports, hobbies, medical.”
However, former employees expressed deep skepticism of Appen’s ability to succeed given its tumultuous position and the executive shuffling taking place. Part of the problem, they say, is the organizational structure.
Appen was divided into a global business unit and an enterprise business unit, which were at one time made up of about five clients and more than 250 clients, respectively. Each had a separate team and communication between them was limited, creating inefficiencies internally, ex-employees said. One former manager said it felt like two separate companies. Appen said that in the last quarter, the company has integrated the global and enterprise business units.
The company’s plunging stock price suggests that investors don’t see the company’s business offerings transferring to the generative AI space.
Lisa Braden-Harder, who served as CEO of Appen until 2015, echoed that sentiment, telling CNBC that “data-labeling is completely different” than how data collection works in a ChatGPT world.
“I am not clear that their past experience of data labeling is a competitive advantage now,” she said.
Former Appen employees say the company has in recent years been dealing with quality control problems, hurting its ability to provide valuable training data for AI models. For example, one former department manager said people would annotate rows of data using automated tools instead of the manual data labeling required for accuracy, which is what clients thought they were buying.
Customers’ expectations of a “clean data set” were often not met, the person said, leading them to leave Appen for competitors such as Labelbox and Scale AI. When the manager started at the company, there were more than 250 clients in the enterprise business unit. Within 18 months, he said, that number had dwindled to less than 100.
Appen told CNBC that in the first half of the year it “secured 89 new client wins.”
Monegan recalled that many customer relationships were “hanging on by a thread.”
Following the earnings report, Canaccord Genuity analysts cut their price target on Appen by more than half to AU$1.56. One concern the analysts referenced was a 34% reduction in spending by Appen’s top customer, a number that Appen wouldn’t confirm or deny.
The more existential problem, the analysts note, revolves around Appen’s effort to win business while also looking to cut costs by 31% in fiscal 2023.
“That seems like a brutal level of cost reduction,” they wrote, as the company tries to stabilize its “core revenue base while growing a business around Generative AI.”
WATCH: AI is the next trend to watch when it comes to smartphones, says market research firm
Formula One F1 – United States Grand Prix – Circuit of the Americas, Austin, Texas, U.S. – October 23, 2022 Tim Cook waves the chequered flag to the race winner Red Bull’s Max Verstappen
Mike Segar | Reuters
Apple had two major launches last month. They couldn’t have been more different.
First, Apple revealed some of the artificial intelligence advancements it had been working on in the past year when it released developer versions of its operating systems to muted applause at its annual developer’s conference, WWDC. Then, at the end of the month, Apple hit the red carpet as its first true blockbuster movie, “F1,” debuted to over $155 million — and glowing reviews — in its first weekend.
While “F1” was a victory lap for Apple, highlighting the strength of its long-term outlook, the growth of its services business and its ability to tap into culture, Wall Street’s reaction to the company’s AI announcements at WWDC suggest there’s some trouble underneath the hood.
“F1” showed Apple at its best — in particular, its ability to invest in new, long-term projects. When Apple TV+ launched in 2019, it had only a handful of original shows and one movie, a film festival darling called “Hala” that didn’t even share its box office revenue.
Despite Apple TV+ being written off as a costly side-project, Apple stuck with its plan over the years, expanding its staff and operation in Culver City, California. That allowed the company to build up Hollywood connections, especially for TV shows, and build an entertainment track record. Now, an Apple Original can lead the box office on a summer weekend, the prime season for blockbuster films.
The success of “F1” also highlights Apple’s significant marketing machine and ability to get big-name talent to appear with its leadership. Apple pulled out all the stops to market the movie, including using its Wallet app to send a push notification with a discount for tickets to the film. To promote “F1,” Cook appeared with movie star Brad Pitt at an Apple store in New York and posted a video with actual F1 racer Lewis Hamilton, who was one of the film’s producers.
(L-R) Brad Pitt, Lewis Hamilton, Tim Cook, and Damson Idris attend the World Premiere of “F1: The Movie” in Times Square on June 16, 2025 in New York City.
Jamie Mccarthy | Getty Images Entertainment | Getty Images
Although Apple services chief Eddy Cue said in a recent interview that Apple needs the its film business to be profitable to “continue to do great things,” “F1” isn’t just about the bottom line for the company.
Apple’s Hollywood productions are perhaps the most prominent face of the company’s services business, a profit engine that has been an investor favorite since the iPhone maker started highlighting the division in 2016.
Films will only ever be a small fraction of the services unit, which also includes payments, iCloud subscriptions, magazine bundles, Apple Music, game bundles, warranties, fees related to digital payments and ad sales. Plus, even the biggest box office smashes would be small on Apple’s scale — the company does over $1 billion in sales on average every day.
But movies are the only services component that can get celebrities like Pitt or George Clooney to appear next to an Apple logo — and the success of “F1” means that Apple could do more big popcorn films in the future.
“Nothing breeds success or inspires future investment like a current success,” said Comscore senior media analyst Paul Dergarabedian.
But if “F1” is a sign that Apple’s services business is in full throttle, the company’s AI struggles are a “check engine” light that won’t turn off.
Replacing Siri’s engine
At WWDC last month, Wall Street was eager to hear about the company’s plans for Apple Intelligence, its suite of AI features that it first revealed in 2024. Apple Intelligence, which is a key tenet of the company’s hardware products, had a rollout marred by delays and underwhelming features.
Apple spent most of WWDC going over smaller machine learning features, but did not reveal what investors and consumers increasingly want: A sophisticated Siri that can converse fluidly and get stuff done, like making a restaurant reservation. In the age of OpenAI’s ChatGPT, Anthropic’s Claude and Google’s Gemini, the expectation of AI assistants among consumers is growing beyond “Siri, how’s the weather?”
The company had previewed a significantly improved Siri in the summer of 2024, but earlier this year, those features were delayed to sometime in 2026. At WWDC, Apple didn’t offer any updates about the improved Siri beyond that the company was “continuing its work to deliver” the features in the “coming year.” Some observers reduced their expectations for Apple’s AI after the conference.
“Current expectations for Apple Intelligence to kickstart a super upgrade cycle are too high, in our view,” wrote Jefferies analysts this week.
Siri should be an example of how Apple’s ability to improve products and projects over the long-term makes it tough to compete with.
It beat nearly every other voice assistant to market when it first debuted on iPhones in 2011. Fourteen years later, Siri remains essentially the same one-off, rigid, question-and-answer system that struggles with open-ended questions and dates, even after the invention in recent years of sophisticated voice bots based on generative AI technology that can hold a conversation.
Apple’s strongest rivals, including Android parent Google, have done way more to integrate sophisticated AI assistants into their devices than Apple has. And Google doesn’t have the same reflex against collecting data and cloud processing as privacy-obsessed Apple.
Some analysts have said they believe Apple has a few years before the company’s lack of competitive AI features will start to show up in device sales, given the company’s large installed base and high customer loyalty. But Apple can’t get lapped before it re-enters the race, and its former design guru Jony Ive is now working on new hardware with OpenAI, ramping up the pressure in Cupertino.
“The three-year problem, which is within an investment time frame, is that Android is racing ahead,” Needham senior internet analyst Laura Martin said on CNBC this week.
Apple’s services success with projects like “F1” is an example of what the company can do when it sets clear goals in public and then executes them over extended time-frames.
Its AI strategy could use a similar long-term plan, as customers and investors wonder when Apple will fully embrace the technology that has captivated Silicon Valley.
Wall Street’s anxiety over Apple’s AI struggles was evident this week after Bloomberg reported that Apple was considering replacing Siri’s engine with Anthropic or OpenAI’s technology, as opposed to its own foundation models.
The move, if it were to happen, would contradict one of Apple’s most important strategies in the Cook era: Apple wants to own its core technologies, like the touchscreen, processor, modem and maps software, not buy them from suppliers.
Using external technology would be an admission that Apple Foundation Models aren’t good enough yet for what the company wants to do with Siri.
“They’ve fallen farther and farther behind, and they need to supercharge their generative AI efforts” Martin said. “They can’t do that internally.”
Apple might even pay billions for the use of Anthropic’s AI software, according to the Bloomberg report. If Apple were to pay for AI, it would be a reversal from current services deals, like the search deal with Alphabet where the Cupertino company gets paid $20 billion per year to push iPhone traffic to Google Search.
The company didn’t confirm the report and declined comment, but Wall Street welcomed the report and Apple shares rose.
In the world of AI in Silicon Valley, signing bonuses for the kinds of engineers that can develop new models can range up to $100 million, according to OpenAI CEO Sam Altman.
“I can’t see Apple doing that,” Martin said.
Earlier this week, Meta CEO Mark Zuckerberg sent a memo bragging about hiring 11 AI experts from companies such as OpenAI, Anthropic, and Google’s DeepMind. That came after Zuckerberg hired Scale AI CEO Alexandr Wang to lead a new AI division as part of a $14.3 billion deal.
Meta’s not the only company to spend hundreds of millions on AI celebrities to get them in the building. Google spent big to hire away the founders of Character.AI, Microsoft got its AI leader by striking a deal with Inflection and Amazon hired the executive team of Adept to bulk up its AI roster.
Apple, on the other hand, hasn’t announced any big AI hires in recent years. While Cook rubs shoulders with Pitt, the actual race may be passing Apple by.
Tesla CEO Elon Musk speaks alongside U.S. President Donald Trump to reporters in the Oval Office of the White House on May 30, 2025 in Washington, DC.
Kevin Dietsch | Getty Images
Tesla CEO Elon Musk, who bombarded President Donald Trump‘s signature spending bill for weeks, on Friday made his first comments since the legislation passed.
Musk backed a post on X by Sen. Rand Paul, R-Ky., who said the bill’s budget “explodes the deficit” and continues a pattern of “short-term politicking over long-term sustainability.”
The House of Representatives narrowly passed the One Big Beautiful Bill Act on Thursday, sending it to Trump to sign into law.
Paul and Musk have been vocal opponents of Trump’s tax and spending bill, and repeatedly called out the potential for the spending package to increase the national debt.
On Monday, Musk called it the “DEBT SLAVERY bill.”
The independent Congressional Budget Office has said the bill could add $3.4 trillion to the $36.2 trillion of U.S. debt over the next decade. The White House has labeled the agency as “partisan” and continuously refuted the CBO’s estimates.
The bill includes trillions of dollars in tax cuts, increased spending for immigration enforcement and large cuts to funding for Medicaid and other programs.
It also cuts tax credits and support for solar and wind energy and electric vehicles, a particularly sore spot for Musk, who has several companies that benefit from the programs.
“I took away his EV Mandate that forced everyone to buy Electric Cars that nobody else wanted (that he knew for months I was going to do!), and he just went CRAZY!” Trump wrote in a social media post in early June as the pair traded insults and threats.
Shares of Tesla plummeted as the feud intensified, with the company losing $152 billion in market cap on June 5 and putting the company below $1 trillion in value. The stock has largely rebounded since, but is still below where it was trading before the ruckus with Trump.
Tesla one-month stock chart.
— CNBC’s Kevin Breuninger and Erin Doherty contributed to this article.
-
Sports3 years ago‘Storybook stuff’: Inside the night Bryce Harper sent the Phillies to the World Series
-
Sports1 year agoStory injured on diving stop, exits Red Sox game
-
Sports2 years agoGame 1 of WS least-watched in recorded history
-
Sports2 years agoMLB Rank 2023: Ranking baseball’s top 100 players
-
Sports4 years ago
Team Europe easily wins 4th straight Laver Cup
-
Environment2 years agoJapan and South Korea have a lot at stake in a free and open South China Sea
-
Sports2 years agoButton battles heat exhaustion in NASCAR debut
-
Environment2 years agoGame-changing Lectric XPedition launched as affordable electric cargo bike