Who Gets the TikTok in the Divorce? The Messy Fight Over Valuable Social Media Accounts
When couples who make their living online split up, assessing the accounts’ future value and divvying them up fairly is a drag
4 min
When Kat and Mike Stickler filed for divorce, their lawyers had a math problem.
Among the couple’s biggest assets was MikeAndKat, a channel on TikTok and YouTube in which they shared their lives with about four million followers. No one knew how to evenly split MikeAndKat between Mike and Kat.
“The judge was like, ‘what?’” Kat said last month during a podcast interview with Northwestern Mutual. “It’s a whole new terrain.”
Social media pays the bills for millions of Americans. But making a living online is more financially complicated than working a 9-to-5. Influencers need an audience to win advertising deals, and changing what they post risks turning followers away. Couples who showcase their love life online face an existential threat to the family business when they split.
For the lawyers charged with pinning a dollar value to the accounts to divide them fairly, it’s way harder than assessing a house or car. Fortunes can swing depending on which ex has the keys to the account. That was Kat’s argument in fighting for control of the TikTok channel.
“If the TikTok account was left to me, it would keep growing, but if it wasn’t, it would stop,” said Kat, 29, in the podcast interview.
She was right.
Kat got the TikTok, changed that handle to KatStickler and now has almost 10.5 million followers. She has another three million across Instagram, YouTube and Facebook. The channels, where Kat posts skits impersonating her mother and snippets of her everyday life, have earned her enough to buy a condo and become a small business investor.
Mike ended up with the YouTube account, which is now defunct. He now works in sales and declined to comment.
There are 27 million paid content creators in the U.S., and 44% of them say social media is their full-time job, consultant The Keller Advisory Group found.
The big bucks don’t come from views or followers. Brands pay influencers to recommend a product or service to their audience. U.S. advertisers paid content creators $26 billion in 2023, according to Statista.
Once divorce specialists tally up how much money the accounts are raking in, the couple can divide them, or one partner can take more and buy out the other.
But there’s one elusive factor in a digital asset’s value: the account’s potential to keep making money. Both partners have to make a case for their role in that potential. How many pranks did they think of? How many hours did they spend editing videos?
“There’s typically one person in the relationship who is passionate about social media, who’s driving the business,” says Cameron Ajdari, who runs a talent management group with his wife representing some of TikTok’s most followed couples.
It’s not always clear who that person is by the time divorce rolls around. Social media success often evolves quickly, and couples may not be prepared to track finances and labour.
Reza and Puja Khan say everything they’ve done to amass about five million followers on shared channels has been a team effort. They started posting about their wedding in 2020 and, within months, Puja was able to quit her office job. Now, they estimate social media brings in about half a million dollars a year.
Almost all of that goes into a joint bank account. It was a little overwhelming to see their incomes jump so fast, far above what their parents made, say Reza, 28, and Puja, 27. They hired a financial adviser earlier this year, but the idea of dividing their empire has never crossed Puja’s mind.
“This is the first time we’re actually thinking about it,” she says. “If I really went public with a hypothetical split, that could create its own momentum.”
The way influencers rebuild their brands after breaking up can make or break their careers.
If the person got popular by posting memes or makeup tutorials, they probably won’t take much of a financial hit from a divorce. But there could be more damage if a lot of the videos feature family time.
“One could take it over and they just rebrand, which is risky,” says Nina Shayan Depatie, a divorce attorney in Los Angeles who has worked with influencers. “When you’re looking at the valuation, you would have to consider that.”
Ayumi Lashley, 34, started creating social media videos with her husband in 2017. They made it their full-time job in 2020 and the accounts paid for her car and house, she says.
When they divorced in 2023, they both tried to elevate their personal profiles, but their fan base is still attached to a nonexistent relationship. She says she chose not to share much about the split and lost a few thousand followers, while her ex posted more about the divorce.
“A lot of people were very upset with me for not talking about it,” Lashley says. “His career is doing amazing and mine is not.”
Many content creators don’t intend to make videos of their daily outfits forever, even if it isn’t divorce that ends their careers.
“I always joke we’re like NFL players. You get five or 10 good years, but you take one bad hit to the knee and you’re done,” says Vivian Tu, 30, who posts about financial literacy to roughly eight million followers. “You can’t control the algorithms. You can’t control what is in vogue and what’s not.”
Tu says she is preparing for a life away from social media by developing other streams of income, including writing a book and hosting a podcast.
She is also aware of what divorce could do to her business. Tu wrote up a prenuptial agreement that included all her social-media accounts before she got married in June.
“My social media is my résumé,” Tu says. “Why would I allow anybody else to put my work on their résumé?”
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Technology and semiconductor shares fell sharply as investors questioned the debt financing the AI infrastructure boom and confronted higher rates and Chinese competition.
Technology and semiconductor shares fell sharply as investors questioned the debt financing the AI infrastructure boom and confronted higher rates and Chinese competition.
4 minA sharp technology sell-off has exposed a new anxiety on global markets: whether the enormous borrowing behind the artificial-intelligence infrastructure boom can generate sufficient returns as interest rates rise and Chinese competition intensifies.
The artificial-intelligence investment boom has powered technology shares, semiconductor manufacturers and data-centre operators to extraordinary heights. Last week, investors were given a reminder that much of this expansion is being built with borrowed money.
The technology-heavy Nasdaq Composite fell 4.5 per cent over the week ended October 16, its weakest performance since late June. Semiconductor shares suffered an even deeper correction, with the Philadelphia Semiconductor Index losing about 11.4 per cent.
The selling spread quickly through global markets. Micron Technology fell 14.6 per cent over the week, while South Korea’s Samsung Electronics and SK Hynix dropped approximately 18 per cent and 24 per cent respectively.
This was more than a routine bout of profit-taking. Investors were reassessing three interconnected risks: higher interest rates, the rapidly expanding debt burden attached to AI infrastructure and the prospect of stronger competition from Chinese memory-chip manufacturers.
The debt behind the AI build-out
Artificial intelligence requires a physical infrastructure network of enormous scale. Data centres must be built, advanced processors purchased, power supplies secured and cooling systems installed before customers begin generating meaningful revenue from them.
Technology companies are increasingly supplementing their own cash with corporate bonds, syndicated loans, equipment leases, private credit and project-level financing.
JPMorgan describes the emerging funding model as a combination of conventional corporate borrowing and project finance tied to individual data-centre assets. In Australia, the Reserve Bank estimates that syndicated loans accounted for approximately three-quarters of data-centre financing during 2025 and 2026 to date.
The numbers are becoming large enough to affect broader credit markets. The Federal Reserve Bank of Dallas has cited Wall Street estimates suggesting AI-related investment-grade bond issuance could approach US$300 billion in 2026 alone.
That borrowing is not automatically problematic. Debt can be an efficient way to finance long-lived infrastructure when future revenue is sufficiently predictable. The concern is that AI technology, customer demand and computing economics are changing much faster than the repayment schedules attached to the assets.
A data centre financed today may carry debt for years. Investors must therefore make assumptions about future utilisation rates, electricity prices, chip performance, customer concentration and the amount businesses will ultimately pay for AI computing.
When interest rates rise, those assumptions become less forgiving.
Inflation changes the calculation
September’s US inflation data intensified the pressure. Consumer prices increased 3.7 per cent over the year, ahead of market expectations and up from 3.4 per cent in August.
The hotter reading reduced confidence that interest rates would fall quickly and pushed bond yields higher. That matters particularly for companies whose valuations depend on profits expected well into the future, as well as highly leveraged infrastructure operators that may need to refinance.
CoreWeave has emerged as a closely watched test case. The specialist cloud-computing company has accumulated substantial debt and lease obligations to build AI capacity, while relying on a concentrated group of large technology customers.
Its shares fell sharply during the sell-off, while the cost of insuring its debt against default climbed. CoreWeave has argued that its contracted backlog more than covers its obligations and that financial markets do not always understand its business model. Nevertheless, its securities have become a proxy for investor confidence in debt-funded AI infrastructure.
Oracle, another major investor in AI computing capacity, fell 8.8 per cent in Friday trading, while CoreWeave dropped 15.5 per cent.
The question is shifting from how much AI infrastructure can be built to how profitably it can be operated.
China adds another source of pressure
Interest rates were not the only catalyst. Reports of advances by Chinese memory-chip producer ChangXin Memory Technologies raised concerns that lower-cost Chinese products could increase competition across the global semiconductor industry.
Memory chips are essential to AI systems, but the industry is historically cyclical. Periods of tight supply and high pricing can encourage rapid investment, eventually producing oversupply and falling margins.
The prospect of a well-funded Chinese competitor expanding its technological capabilities unsettled investors in Samsung, SK Hynix and Micron. It also demonstrated that AI-related demand does not insulate chipmakers from conventional competitive pressures.
That combination—slower rate cuts, more expensive financing and potentially cheaper supply—challenged the assumption that every company exposed to AI would enjoy continually expanding margins.
A reset rather than the end of the boom
The sell-off does not establish that the AI boom is ending. Demand for computing power remains strong, the largest technology companies continue to generate formidable cash flows and many infrastructure projects are backed by long-term customer contracts.
What has changed is the market’s willingness to overlook the price and financing structure of that growth.
The most resilient companies are likely to be those able to fund investment from operating cash flow, secure long-duration customers and demonstrate that new capacity will earn returns comfortably above its financing costs.
More speculative operators may face greater scrutiny, particularly where debt is expensive, customers are concentrated or expected revenue depends on demand that has not yet materialised.
For Australian investors, the lesson extends beyond US technology shares. Local data-centre operators, infrastructure funds, electricity suppliers and property groups are increasingly exposed to the same investment cycle.
Artificial intelligence may remain one of the defining growth themes of the decade. But last week’s correction showed that enthusiasm for the technology does not eliminate financial discipline.
The next stage of the AI boom will be judged not only by computing power, model performance or demand for chips, but by something more traditional: whether the assets being financed can generate enough cash to repay the money borrowed to build them.
Fact box
Nasdaq Composite: Down 4.5 per cent for the week ended October 16, 2026
Philadelphia Semiconductor Index: Down approximately 11.4 per cent
Micron Technology: Down approximately 14.6 per cent
Samsung Electronics: Down approximately 18 per cent
SK Hynix: Down approximately 24 per cent
US September inflation: 3.7 per cent annually
Estimated 2026 AI-related investment-grade issuance: Approximately US$300 billion
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