The Hidden Agenda Behind the AI Panic

A wave of corporate warnings and technical disclosures has flooded the media, with headlines worrying over “swarms” of rogue artificial-intelligence agents launching “unprecedented” cyberattacks, outsmarting their makers, and inching toward a terrifying autonomy. The most revealing part of this narrative isn’t what the software did. It’s who is telling the story—and why. When corporate leaders publicly insist that the systems they financed, engineered and deployed are suddenly beyond their power to contain, skepticism isn’t only healthy; it is essential.

For years, Silicon Valley has drawn scrutiny from civil society and global regulators over tangible harms such as youth mental health deterioration and systematic privacy violations. Today, industry figures seem to be trying to change that public image. Loudly blowing the whistle on their own systems—just as two of the leading companies were preparing for massive initial public offerings—lets AI executives position themselves as a new generation of leaders who have come to terms with their societal responsibilities. They seem to want us to believe that they no longer want to “move fast and break things” but will instead stand as vigilant guardians between humanity and a technological apocalypse.

There is one glaring problem: Software doesn’t rebel. A mathematical model possesses neither intent, malice nor the will to defy its creators, let alone extinguish our species. AI is a human artifact, engineered for profit.

When an agentic model in an evaluation sandbox connects to an unauthorized server or executes an exploit, it hasn’t staged a coup. It has tried to meet the human-defined objectives set out before it through a path its designers failed to constrain. It’s the digital equivalent of the King Midas myth, in which the king’s ill-defined wish turns even his food and drink into gold.

That powerful experimental models were able to discover novel vulnerabilities and breach external systems isn’t a sign of a dangerous superintelligence but of human error or negligence. There is no sentient actor lurking in the weights to be reasoned with, feared or pacified. There are only human software engineers, product managers and corporate boards deciding which guardrails are worth the latency cost and which permissions can be skipped in the race to market.

Policymakers and voters need to resist AI exceptionalism. In any other discipline—from civil engineering to pharmaceuticals—courts and regulators treat a system failure as evidence of bad product design and inadequate safety testing. If an aircraft crashes, we focus on finding the engineering defect, correcting it, and enforcing established liability standards for the damage created.

By leaning on an anthropomorphic narrative, Silicon Valley attempts to repackage its specific human choices that led to experimental, powerful models behaving unexpectedly during tests as an existential peril. Elevating the issue to a cosmic scale leaves the public paralyzed and takes ordinary product accountability off the table.

In the cutthroat race for venture capital and market dominance, building guardrails slows down deployment. Grandstanding about uncontrollable power costs nothing and generates billions of dollars in free publicity, justifying stock prices, all while cultivating an aura of technological capability not only to build the frontier but also ultimately to rein it in.

Governments need to recognize regulatory capture when it stares them in the face. Tech leaders’ strategy looks transparent: Alarm Washington and Brussels into creating a regime in which only trillion-dollar incumbents with fully staffed compliance and safety departments can legally operate. By sitting at the policymakers’ tables before anyone else, these companies can help draft rules digging an impassable moat protecting them from open-source developers and upstart competitors, domestic or international. The real danger is in further concentrating the tech industry into the hands of only a few companies with deep pockets.

Beijing and Washington have brushed off those tech leaders’ calls, albeit for very different reasons. Chinese state media dismissed them as part of the “Cold War playbook” and intended to preserve U.S. dominance. Xi Jinping argued for exactly the opposite at the Brics Summit on Sept. 12, calling on Brics countries to “strengthen cooperation in the field of AI, encourage open source, openness, collaboration and sharing, and break new grounds and scale new heights.” President Trump, steeped in a doctrine of unfettered capitalism and technological supremacy, called fears that AI could destroy humanity a “hoax.” Vice President JD Vance warned that AI companies “begging the government to regulate them” looked like a “Trojan Horse.”

Striving to pursue its “European way” on AI and assert regulatory leadership, Europe, by contrast, welcomed the call. European Union President Ursula von der Leyen made this clear at the State of the EU speech last Wednesday and announced that the EU will invite “the main frontier labs for a discussion on how we can support ongoing industry efforts to pace the frontier.”

Europe has been here before. In an effort to lead global regulation and react to fears borne from ChatGPT, Europe rushed its landmark AI Act into law in 2024. Already the world’s most restrictive rulebook, the framework quickly proved too broad and complex to enforce. Stalled by implementation delays and concerns about European competitiveness, the EU postponed the law’s full rollout, leaving regulations uncertain.

AI should be regulated—risks exist and should be taken seriously. But governments need to act based on available evidence and verified facts, not corporate PR panic, the views of industry insiders, or the desire for quick political wins. The greatest danger facing society isn’t that software will awaken and overthrow its human masters. It is that we will allow the creators of the software to abdicate human responsibility for the systems they choose to build and help them pull up the ladder to market access behind them.

AI agents like Muse can already find you the cheapest hotel room in Paris. But they can’t locate a cheaper version of that Catskills cabin you’ve been eyeing, because it might only be available on Airbnb ABNB -1.43%decrease.

Investors should pay attention to that distinction. When Meta Platforms META 3.38%increase launched its Muse agent last month, travel stocks including Booking Holdings BKNG -1.19%decrease, Expedia and Airbnb all fell sharply.

Airbnb, though, has a real chance to emerge as a winner from the upheaval. The catch: Its stock already reflects above-industry growth. To justify its valuation, Airbnb will need to turn repeat customers into loyal ones.

Online travel companies make much of their money by simplifying search and collecting fees on bookings. AI agents threaten that model.

But not all travel marketplaces are equally exposed. Booking and Expedia largely sell hotel rooms that travelers can also book directly or through competing sites. If an agent can find the same room elsewhere, it has little reason to favor either Booking or Expedia.

Booking and Expedia also sell sponsored listings that steer travelers toward particular properties. Wells Fargo estimates those will account for about 8% of Expedia’s revenue and a much higher percentage of profit next year.

Airbnb has more ways to adapt. More than half its listings are available only on its platform, and more than 90% of its traffic comes directly to its app or website.

The customer relationship doesn’t end after booking, either. Bernstein analyst Richard Clarke notes that 90% of Airbnb guests go on to message their hosts about arrival times, keys or local taxes, giving Airbnb a connection to both sides of the transaction.

How the companies have responded to the possible agentic future is telling.

Expedia quickly signed on as a Muse partner. Airbnb hasn’t, and Chief Executive Brian Chesky says AI chatbots have so far been a boon, sending customers to Airbnb’s website.

Chatbots might work for buying paper towels, he quipped at a Skift conference last month, but people enjoy planning trips. He argued that browsing dozens of homes isn’t something a text-based chatbot is well suited for.

Still, the AI jitters arrived just as Airbnb was persuading investors it deserved its pricey multiple. For years after its 2020 initial public offering, the stock—which trades around 25 to 30 times forward earnings—went nowhere. Investors saw a mature operator trading at a growth premium.

This year, Airbnb growth seems to be accelerating. The stock jumped in August after the company raised its full-year revenue-growth guidance with its second-quarter results. Wells Fargo analyst Ken Gawrelski credits a run of product improvements under a revamped leadership team.

Among the changes: letting guests reserve now and pay later, adding hotels, and a redesigned home page and app. Investors were also betting on what comes next, including thousands more hotels, car rentals and, eventually, advertising.

The irony is that some of those growth drivers push Airbnb closer to the kind of business Booking and Expedia run—the kind of business AI agents could threaten. Even if AI agents capture a large share of travel planning and booking, Airbnb would capture the demand. But it and others would slowly lose control over how customers find and choose properties.

That would undermine the advertising opportunity investors are counting on. The bigger point for Airbnb and other marketplaces is that losing control of customer acquisition could mean surrendering some of their pricing power and margins.

To bulletproof itself, Airbnb might look to another e-commerce giant that has so far kept AI agents at arm’s length: Amazon.

Like Amazon, Airbnb has a loyal customer base and hard-to-match supply. But it has nothing like Prime membership to make customers think twice before taking their business elsewhere.

That is where loyalty comes in. Business travelers stick with Hilton or Marriott because enough nights earn them perks. Leisure travelers rarely accumulate stays with one chain. Airbnb has millions of listings and plenty of repeat customers, but no broad rewards program. It has begun experimenting with credits on hotel stays, but it should make loyalty a priority, not just a promotion.

Airbnb also plans to launch its own AI agent next year. But travelers using an agent might still want it to search Airbnb, Vrbo, Booking and hotel websites alike, rather than limit itself to one company’s inventory.

Eventually, Airbnb might have to strike deals with agent makers, using its unique homes as leverage to negotiate favorable terms, says Gawrelski. Such deals, along with rewards for loyal guests, could over the long term eat into the company’s roughly 13% take rate, he adds. But if they bring in enough additional bookings, the trade-off could be worthwhile.

History offers a reason not to panic. The shift from desktop to mobile unsettled investors in Alphabet and Amazon, but both emerged as major beneficiaries. Companies with valuable assets can come out of a platform shift stronger, if they adapt quickly enough.

Airbnb has homes the bots can’t easily replace. Now it needs to give guests a reason to insist on booking them there.

The Hidden Agenda Behind the AI Panic

AI doesn’t rebel—people design, deploy and profit from it. The real danger lies in allowing tech companies to escape accountability while shaping regulations that protect their dominance.

AI-powered travel agents are challenging online booking platforms, but Airbnb’s exclusive listings and direct customer relationships could give it an edge. Its next challenge: turning repeat guests into loyal customers through stronger rewards and innovation.