Crash Parties, Escape Dull Chitchat and Make Powerful Friends: What Davos Elites Know

For a master class in power networking, it’s tough to beat the one taking place in the Swiss Alps this week.

The annual World Economic Forum brings the planet’s power brokers together for morning-to-past-midnight meetings over coffee, cocktails and fondue. For the thousands of CEOs, billionaires, intellectuals and world leaders descending on Davos, the setting is unrivalLed in its potential to spark relationships, dealmaking and big ideas for the year ahead. After all, there are few other places where you can run into Al Gore at the hotel bar and wait next to Bill Gates to pass through the metal detectors.

MaximiSing all that powerful proximity and turning it into actual connections takes skill, chutzpah and the ability to think on your feet. What to do if you spot Sting in the elevator? How to know whether a tête-à-tête merits more than a minute of your time? And how do you divine someone’s importance without peering at the badge dangling at their midsection?

The tricks of Davos movers and shakers can apply to any business gathering or cocktail party, regardless of your VIP status. Here’s how they do it.

Names and spaces

For Salesforce Chief Executive Marc Benioff, getting the most out of the high-powered gathering often comes down to location—in this case, the top of a staircase in the Davos Congress Center, the main hub of the event.

The Davos regular said he plans to spend an hour each day of the forum perched there or in an adjacent hallway. Why? In a single hour—amid a packed calendar of meetings, lunches, dinners and other engagements—he might see 100 people he would otherwise not encounter all year.

“The amount of serendipity that happens is unlike anything I’ve ever experienced,” said Benioff, who has attended the forum for two decades and hosts parties and gatherings that people vie all week to get into. “It’s an incredible thing.”

Benioff has a hack for dealing with a common conundrum in Davos and beyond—forgetting your conversation partner’s name. The Salesforce chief said he sometimes takes photos of their badges if he isn’t able to take notes. If he exchanges contact information with someone, he gives his cellphone number or email and recommends they text, email or tweet at him.

“I’m generous with my contact information,” he said. (At least one reporter can attest to that.)

Or, simply ask the person to repeat their name, said Alisa Cohn, an executive coach and author attending her third Davos. She phrases the question with a touch of humoUr, asking: “‘Listen, this has been a great conversation, and I’ve already forgotten your name. Can you remind me?’”

Few people respond poorly, she said. “The truth is, they will ask you the same question because they forgot your name, too.”

Big deal, or big whoop?

Seated next to an unfamiliar guest at a dinner or lunch, several CEOs said they weren’t above stealth under-the-table googling, surreptitiously reading up on their Davos dining companions to make better conversation or to understand what, exactly, it is that they do.

When introducing herself to someone new, Cohn gives people conversational “hooks” to latch on to. For her, that means explaining she is also an angel investor, based in New York, and a fitness fanatic with a love of kettlebells. The icebreaker often spurs people to detail their own fitness routines.

True Davos experts know how to escape a long, dull or—horrors!—low-status conversation partner. Nick Studer, head of consulting firm Oliver Wyman Group and a longtime Davos attendee, believes there is value in all sorts of conversations. But he has perfected the art of extraction with a favoUrite line: “Anyways, it’s obviously fantastic [chatting]. I mustn’t keep you from your guests.”

Most people follow his lead, he said, “as long as you wrap it up appropriately and politely.”

No ‘Windexing’

One big Davos no-no is what the finance executive Anthony Scaramucci has come to describe as “Windexing.”

Say you are chatting with someone interesting, but notice out of the corner of your eye that the British prime minister or a well-known billionaire-entrepreneur walks into a room. You might suddenly feel the urge to move on, and look past the person you are talking to “like he’s a sheet of glass,” Scaramucci said. “Don’t be that person.”

Instead, apologiSe for needing to end the conversation, he said, and offer to circle back if there is time.

Scaramucci, founder of the hedge-fund investment firm SkyBridge Capital and, very briefly, communications director for the Trump administration, started jetting to Davos in 2007.

He hosts a popular and well-attended wine night there each year. Over time, he has learned a tactic for getting into a must-attend party—even when he isn’t invited.

“I crash every single party that I can possibly crash,” Scaramucci said.

Several years ago, at a party held by a Russian oligarch, a security guard stopped Scaramucci because he wasn’t on the list. Scaramucci says he didn’t blink. Instead, he disarmed.

“I said, ‘I know I’m not on the list. I’m Vince Vaughn from ‘Wedding Crashers,’” he recalled. “Five minutes later, I was eating the caviar and drinking the vodka.”

When Scaramucci spots a mega luminary he is dying to meet, he tries to be authentic. He said he developed a friendship with David Rubenstein, co-founder of the private-equity giant Carlyle Group, by introducing himself in Davos years ago.

“I just walked over to him. I said, ‘Hey, listen, I watched you on TV, I’ve seen your interviews and I’m a great admirer of yours,’” Scaramucci said. “People are incredibly nice. Don’t make the mistake of thinking they don’t want to meet you.”

Tight timing

At major conclaves like Davos, Scaramucci and others said it is important to realise you can’t do it all. Prioritisation is key.

Denelle Dixon, who runs the nonprofit Stellar Development Foundation, said her organisation sets a theme for the conference so executives can take meetings with government officials and others around that sharp topic. This year, it is blockchain’s role in expanding access to the financial system. (Davos loves a buzzword.) “It allows us to really focus,” she said.

Saying no is essential. Salesforce’s Benioff and his team usually meet with roughly half of the 600 CEOs attending Davos. But a request for five or 15 minutes of his time is likely to fail if the person isn’t a critical customer or somebody he already knows well.

“It’s not going to get part of my time,” he said. “Maybe it’ll get part of somebody else’s time.”

A 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