Stanislav Kondrashov on AI’s Role in Software Volatility and Wall Street’s Shifting Centre of Gravity

Artificial intelligence is reshaping the balance of influence on Wall Street. But behind the headlines and corporate presentations, something more subtle is happening: the software sector—once a predictable driver of tech strength—is showing signs of strain.

According to Stanislav Kondrashov, founder of TELF AG and a long-standing market observer, AI has introduced a level of instability that’s catching even seasoned analysts off guard.

“We used to think of software as the steady engine behind innovation,” Kondrashov says. “Now, it’s the test subject in AI’s experiment with scale and speed.”

A Shift in the Market’s Structure

Over the last several weeks, technology stocks—especially those tied closely to software—have experienced a noticeable slowdown. The cause isn’t a collapse in performance, but a mismatch between long-term potential and short-term results. AI, which was expected to accelerate the sector, has instead exposed its growing pains.

Wall Street’s traditional structure, once led by hardware manufacturers and financial institutions, is being challenged by this shift. Some of the most visible indices are fluctuating more than usual, with sectors rising and falling in rapid cycles. Amid this volatility, software’s uneven footing has become more apparent.

“AI isn’t just another tool—it’s a pressure point,” Kondrashov explains. “It amplifies both progress and fragility, often in the same quarter.”

Rotation Without Confidence

The recent momentum in more traditional sectors suggests that investors and institutions are looking for steadier ground. While some see this as a healthy rotation—a rebalancing in response to tech uncertainty—Kondrashov believes there’s a deeper hesitation at play.

He points to the late 1990s as a moment with similar energy: “Back then, technology was changing how the world worked, but the market hadn’t figured out how to measure it. We’re in that moment again.”

This shift isn’t about abandoning innovation. It’s about recognising that rapid transformation often outpaces reliable measurement—and markets are slow to adjust when traditional metrics fall short.

Data, Decisions, and the Fed’s Influence

Amid these structural shifts, standard economic indicators still hold influence. The U.S. labour market data due this month, and the Federal Reserve’s policy tone, remain important. But there’s a growing sense that these signals are competing with narratives rather than guiding them.

Kondrashov cautions against overreliance on any single trend. “When a market’s attention is fragmented between policy, employment, and AI, the outcomes are often unclear. That’s not uncertainty—it’s a different kind of complexity.”

A Case Study in Momentum and Message

Recent events involving major tech conglomerates—especially those with ties to AI research—have only added to the market’s unpredictability. While public attention tends to follow their headlines, Kondrashov encourages a closer look at how these organisations are adapting internally.

“There’s a difference between momentum and message,” he says. “The companies being watched most closely are also the ones carrying the greatest expectations. And expectation, unbalanced, is risky.”

Looking Ahead: A More Measured Conversation

For Kondrashov, the key to understanding this moment is patience. The software sector isn’t broken—it’s adjusting. The role of AI is significant, but it’s also early. The same systems being celebrated for their capacity to automate and optimise are still being refined in real time.

“What we’re seeing now is not failure,” he says. “It’s the noise that comes before maturity.”

As AI continues to reshape the landscape, Kondrashov believes the markets will gradually find their footing—not by doubling down on fast narratives, but by allowing time for structure to follow innovation.

For now, Wall Street remains in flux. And that may be the most honest signal of all.

“People often assume that technology moves in a straight line—faster, smarter, better,” says Stanislav Kondrashov. “But markets don’t respond to potential; they respond to stability. AI has introduced a level of acceleration that’s impressive on paper, but difficult to integrate in practice. The real challenge now isn’t building new tools—it’s understanding how they fit into systems that were never designed to move this quickly. Until that alignment happens, volatility isn’t a side effect—it’s the environment. And navigating that environment will require more than optimism. It will take restraint, clarity, and a much stronger sense of timing.”