For years, wealth managers competed for entrepreneurs after they sold their companies or executives after their stock options finally became liquid.
Artificial intelligence is changing the timing.
Private banks and wealth-management firms are now trying to build relationships with employees at companies such as OpenAI and Anthropic before any major IPO takes place, hoping to position themselves for what could become one of the largest waves of newly created technology wealth since the early days of Facebook, Google and Nvidia.
The strategy is simple.
If an engineer, researcher or executive is sitting on millions of dollars of private-company equity today, a wealth manager does not want to wait until that person becomes visibly wealthy. By then, every major bank and advisory firm will already be competing for the account.
So they are approaching them early.
The Financial Times reports that banks, private wealth managers and specialist advisers have been stepping up efforts to court employees at some of the world’s most valuable private AI companies as expectations grow that future liquidity events could turn thousands of staff members into multimillionaires.
The result is a new kind of gold rush.
This time, the people prospecting are not AI startups.
They are private bankers.
OpenAI and Anthropic Employees Are Sitting on Enormous Paper Wealth
The reason wealth managers are so interested is valuation.
OpenAI and Anthropic have become two of the most valuable private technology companies in the world. Employee compensation at high-growth startups often includes equity, meaning staff can accumulate substantial paper wealth long before they receive actual cash.
That wealth can remain difficult to use while the company is private.
A researcher may technically own shares worth millions based on the latest fundraising valuation, but those shares are not the same as publicly traded stock.
He cannot necessarily sell them whenever he wants.
There may be transfer restrictions.
Secondary sales may happen only during organized tender offers.
Tax liabilities can become complicated.
And the value itself can change dramatically before a public listing ever occurs.
That combination creates exactly the type of financial complexity private banks like to solve.
A conventional salaried employee may need help with retirement planning and investments.
An AI employee holding large amounts of illiquid private stock may need advice on taxes, liquidity, estate planning, concentration risk and how much borrowing is sensible against future wealth that may not yet be accessible.
That is a much more lucrative relationship for a wealth-management firm.
Banks Want the Client Before the IPO
Timing is everything.
Once a major IPO happens, the wealth becomes visible.
An employee whose shares become publicly tradable can suddenly receive calls from private banks, investment firms, family offices and tax advisers.
Competition becomes intense.
So firms are trying to establish trust earlier.
That might mean helping an employee understand stock options.
It could mean structuring loans.
It could involve tax planning before a tender offer.
Or it may simply mean becoming the first adviser he thinks of when liquidity finally arrives.
This is not unique to AI.
Silicon Valley banks have long built relationships with startup employees before companies go public.
What is different now is the potential scale.
The current AI boom has pushed private-company valuations so high that even employees several levels below the founders can potentially hold extraordinary amounts of equity.
If OpenAI, Anthropic or another major AI company eventually goes public at a huge valuation, the number of newly wealthy employees could be substantial.
Secondary Share Sales Are Already Creating Liquidity
Employees do not necessarily have to wait for an IPO.
Large private technology companies increasingly organize secondary share sales, sometimes called tender offers, allowing employees and early investors to sell part of their holdings to new buyers.
These transactions serve several purposes.
They give staff liquidity.
They can help companies retain employees who might otherwise leave for firms offering public stock.
They also establish a fresh market valuation without requiring the company to complete an IPO.
For wealth managers, secondary sales are important because they turn theoretical wealth into actual cash.
An employee who suddenly receives several million dollars from selling part of his private-company stake immediately needs decisions around taxes, diversification and reinvestment.
That is when financial advisers become valuable.
OpenAI has previously used employee share sales as part of its compensation structure, while Anthropic and other fast-growing AI companies have also attracted intense investor demand in private markets.
The more these secondary transactions grow, the less wealth managers have to wait for a traditional public offering.
The Biggest Risk Is Concentration
An employee at an AI startup may feel wealthy because his equity has appreciated rapidly.
That does not mean his finances are diversified.
In fact, the opposite may be true.
His salary comes from one company.
His career depends on that company.
His biggest asset may also be stock in that same company.
If the company performs well, everything rises together.
If it runs into trouble, his job and his wealth can fall at the same time.
That is classic concentration risk.
For a wealth manager, one of the most important jobs after liquidity becomes available is helping the client decide how much of that concentrated exposure should be sold.
That decision can be emotionally difficult.
Employees may strongly believe in the company.
They may have watched its value multiply.
Selling can feel like abandoning the opportunity just before the biggest gains arrive.
But holding everything can create extraordinary financial risk.
The basic principle of diversification remains relevant even when the company involved happens to be one of the hottest businesses in artificial intelligence.
Investors can explore the broader logic of concentration and diversification through the U.S. Securities and Exchange Commission’s investor education resources.
Taxes Can Become Complicated Very Quickly
Equity compensation is not one financial event.
It can create several.
Stock options may have tax consequences when exercised.
Restricted shares can create taxable income when they vest.
Secondary sales can create capital gains.
Moving between states or countries can complicate matters further.
An employee who joins an AI company early may also hold shares with an extremely low original cost basis.
If those shares later become worth millions, the difference between exercising, holding and selling at different times can create major tax consequences.
That is one reason wealth managers are not the only professionals targeting the sector.
Tax accountants, estate lawyers and specialist advisers also see opportunity.
When the potential wealth reaches eight or nine figures, planning decisions made before an IPO can matter far more than decisions made after it.
IPO Wealth Can Arrive Faster Than Employees Expect
Technology history provides plenty of examples.
Employees at companies such as Google, Facebook and other successful startups became multimillionaires when private equity converted into publicly tradable shares.
The psychological transition can be abrupt.
Someone may spend years thinking of his stock as a theoretical benefit listed on an internal portal.
Then a liquidity event turns it into actual wealth.
That creates unfamiliar decisions.
Should he buy a house?
Should he keep working?
How much stock should he sell?
How much tax should he reserve?
Should he create a trust?
How should he invest the rest?
The larger the windfall, the more expensive a poor decision becomes.
That is why private banks want to reach employees before the emotional impact of sudden wealth arrives.
AI Employees Are Particularly Attractive Clients
Not every technology employee receiving equity becomes an ideal private-banking client.
AI companies are different because of how aggressively they have competed for talent.
The race for elite researchers and engineers has driven compensation packages higher.
Some companies have offered extraordinary salaries, signing bonuses and equity grants to specialists with experience in frontier models, infrastructure and AI safety.
That means even employees who joined relatively recently may own meaningful stakes.
The competition for talent also creates another financial wrinkle.
An engineer moving from one company to another may have equity at several firms simultaneously.
He could hold vested shares in one AI company while receiving a new equity grant from a competitor.
Managing that portfolio can become complicated before any company goes public.
Wealth Managers Are Competing With Tech-Native Advisers
Traditional private banks are not alone.
A younger generation of financial advisers has built businesses specifically around startup founders and technology employees.
These firms often understand option exercises, tender offers, startup valuations and concentrated private equity better than traditional advisers built around publicly traded portfolios.
That gives them an advantage.
A banker talking broadly about stocks and bonds may sound less useful to an Anthropic engineer trying to decide whether to exercise options before a tender offer.
The competition is therefore not simply between JPMorgan, Goldman Sachs, Morgan Stanley and other major institutions.
It also includes specialized advisers, family-office firms and technology-enabled wealth platforms.
The firms that win these clients will likely be the ones that understand private-company equity before the employee becomes conventionally wealthy.
An IPO Is Not Guaranteed
The enthusiasm needs some caution.
A huge private valuation does not guarantee an equally successful public listing.
Private markets can tolerate valuation structures that public investors later challenge.
Growth can slow.
Regulation can change.
Competition can intensify.
The AI business itself may evolve dramatically before any specific company lists.
That means wealth managers cannot treat current paper wealth as guaranteed future cash.
Employees should not either.
A private-company share price established during a funding round may reflect investor expectations that never fully materialize.
An IPO could happen at a higher valuation.
It could happen at a lower one.
It could be delayed for years.
The company could remain private indefinitely.
That uncertainty is precisely why sophisticated planning matters.
The AI Boom Is Creating a New Class of Private Wealth
The most interesting part of this story is not that bankers want rich clients.
That has always been true.
What is changing is where the next generation of wealth is being created.
Twenty years ago, private banks focused heavily on founders, hedge-fund managers and technology executives.
Today, frontier AI researchers can hold equity stakes that may eventually rival the wealth once reserved for senior corporate executives.
That reflects the extraordinary economic value investors are placing on AI talent.
The person training models or designing inference infrastructure may not have founded the company.
But if he joined early enough and received the right equity package, he can still become extremely wealthy.
That changes the market for financial advice.
The Competition Has Already Started
The irony is that the IPOs everyone is preparing for may still be years away.
That does not matter.
Wealth managers know relationships are easier to build before money becomes liquid.
An OpenAI or Anthropic employee who receives thoughtful advice today may remain with the same adviser when his shares eventually become worth tens of millions of dollars.
That future revenue can justify years of early relationship-building.
For the banks involved, the calculation is straightforward.
Artificial intelligence may create enormous value.
Some of that value will eventually land in the personal accounts of employees.
And the financial institutions that arrive first want to make sure those accounts land with them.
The AI gold rush is therefore creating a second gold rush around it.
The first is about building the models.
The second is about managing the fortunes of the people who built them.
