Хиймэл оюун ухааны хөгжил эрчимжихийн хэрээр технологийн салбарын гүйцэтгэх захирлууд бодит байдлаас тасрах буюу хиймэл оюун ухааны чадамжийг хэт үнэлэх хандлагатай болсныг Box компанийн үүсгэн байгуулагч Аарон Леви шүүмжилжээ.
Box компанийн үүсгэн байгуулагч Аарон Левигийн үзэж буйгаар, технологийн салбарын удирдлагууд хиймэл оюун ухааныг ашиглан хялбарчилсан загвар туршиж үзээд, бүх ажлыг AI агентууд бүрэн гүйцэтгэх боломжтой гэх төөрөгдөлд автдаг байна. Гэвч програм хангамж хөгжүүлэлт, алдаа засах, гэрээ хэлэлцээрийн нарийн ширийн нөхцөлийг ойлгох зэрэг бодит үйл ажиллагааны түвшний ажлуудыг тэд өөрсдөө гүйцэтгэдэггүй тул автоматжуулалтын хязгаарыг бүрэн ухамсарладаггүй аж. Тэрээр захирлуудад хиймэл оюун ухааныг өөрсдийн үйл ажиллагаанд өргөнөөр ашиглаж, түүний давуу болон сул талыг бодитоор мэдрэхийг зөвлөжээ.
Энэхүү хандлага нь салбарын хэмжээнд томоохон өөрчлөлтүүдийг дагуулж байна. Layoffs.fyi мэдээллийн санд дурдсанаар, 2026 оны эхний таван сарын байдлаар технологийн 152 компани 115,430 ажилтнаа цомхотгосон нь өмнөх онтой дүйцэхүйц үзүүлэлт юм. Олон компани хиймэл оюун ухааныг нэвтрүүлж буйгаа цомхотголын шалтгаан хэмээн тайлбарлаж байгаа боловч энэ нь бизнесийн бусад шийдвэрүүдтэй холбоотой байж болзошгүй гэж шинжээчид үзэж байна. Тухайлбал, ClickUp компанийн гүйцэтгэх захирал Зеб Эванс 3,000 орчим AI агентыг нэвтрүүлснийхээ дараа нийт ажиллах хүчнийхээ 22 хувийг цомхотгосон нь анхаарал татаж байна.
Гэвч хиймэл оюун ухаан нь бүтээмжийг шууд өсгөнө гэсэн таамаглалыг эрдэм шинжилгээний судалгаанууд бүрэн нотлохгүй байна. Калифорнийн их сургуулийн судалгаагаар AI нэвтрүүлэлт болон нийт бүтээмжийн өсөлтийн хооронд шууд хамаарал байхгүйг тогтоожээ. MIT-ийн судлаачдын дүгнэлтээр, одоогийн LLM загварууд 2029 он гэхэд тексттэй холбоотой ажлуудын 80-95 хувийг хангалттай түвшинд гүйцэтгэх төлөвтэй байгаа ч хүний ажлыг бүрэн орлох чадамжид хүрэхэд дахин хэдэн жил шаардлагатай гэж үзэж байна.
Дэлгэрэнгүйг эх сурвалжаас харах
↓Эх сурвалжийг нээх ↓
There is a certain wildness in the tech industry these days that both mimics previous eras of large changes, like cloud computing (runaway costs in the early days), and is like nothing we’ve ever seen before (record revenues accompanied by mass layoffs).
A theory doing the rounds attempts to explain the phenomenon: Tech executives, especially CEOs, are collectively suffering from delusions of grandeur thanks to AI. And at least one tech CEO has said so out loud: Box founder Aaron Levie.
“CEOs are uniquely prone to AI psychosis because they’re sufficiently distant from the last mile of work that still has to happen to generate most value with AI,” Levie wrote on X.
CEOs “play with AI,” develop a prototype, or generate a contract, to use Levie’s examples, and then make the leap to believing agents can do the work.
But these top-level executives aren’t the people who have to review code, discover bugs, and identify calls to hallucinated libraries before software is deployed. They aren’t responsible for training AI models on a company’s idiosyncratic contract terms, nor do they have to spend days combing through contracts to find sneaky terms, as Levie indicates.
In other words, Levie’s theory posits, CEOs don’t really understand processes well enough to know what really can and can’t be automated. But that lack of knowledge doesn’t stop them from acting on their beliefs.
It’s important to note that Levie is not an AI hater. Quite the opposite. He mostly posts AI positivity on X to his 2.7 million followers, writing blogs titled, “Headless software is the future” on how software built for AI agents is the way forward. He also puts his money where his mouth is, backing AI startups as an active angel investor.
So what are CEOs to do instead? Levie advises CEOs to use AI “a ton” to really see what it can and can’t do, “and come out the other side with an appreciation for both the upside and the real work.”
I have enough faith in humanity to believe that there are CEOs out there attempting to do just that, but right now, they seem to be in the minority.
In only the first five months of 2026, the tech industry has already had nearly as many layoffs as in all of 2025: 115,430 people have been fired from 152tech companies so far in 2026, compared to 124,636 people let go by 275 companies in 2025, according to industry layoff tracker Layoffs.fyi.
And the bulk of companies have pointed to AI as a reason for cutting these jobs. Many argue that the biggest tech companies are AI washing, or crediting AI productivity gains in the past or future, when other business decisions and metrics are really driving the cuts.
Still, some of these stories are surprising. Zeb Evans, the CEO of project management and productivity software startup ClickUp, proudly declared on X that he had laid off almost a quarter of his employees — 22% — after rolling out about 3,000 AI agents to do internal work.
Evans swore this wasn’t done to reduce costs. Instead, he wants a workforce composed of people who run AI agents and spend their days quickly reviewing the agents’ work. He believes this will create a “100x org,” as he calls it.
While AI can be a very useful tool, the data on AI and productivity doesn’t support such assumptions. By miles.
A meta analysis of other research published in October in UC Berkeley’s California Management Review found “no robust relationship between AI adoption and aggregate productivity gain.”
Research published in March by the National Bureau of Economic Research did conclude that AI adoption improved productivity, but noted “a productivity paradox, in which perceived productivity gains are larger than measured productivity gains.”
After creating thousands of agents to work on tasks, researchers at MIT concluded that agents just aren’t doing human-quality work yet in many cases. They predict at the current rate of LLM improvement, models will “be able to complete most text-related tasks with success rates of, on average, 80%–95% by 2029 at a minimally sufficient quality level.”
In other words, AI is on track to perform at base competence on most tasks in about three years. These researchers believe agents will need another few years to outperform humans.
Meanwhile, research published in the Harvard Business Review showed that when everyone is using AI to produce more stuff, the bottleneck simply shifts to executives. Their work awaits the people that must authorize all the stuff everyone is producing. If everyone is empowered to act, then from what OpenAI experienced last year, we can tell that things may get out of control.
Are CEOs ready for that? If not, the most certain outcome of the ongoing CEO AI psychosis will simply be organizational chaos.
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