In an interview with Bloomberg, Gary Gensler, the former Chairman of the United States Securities and Exchange Commission (SEC), said that investors should focus more on real applications and fundamentals than on short-term emotions and market-driven campaigns in the face of bitcoin, encrypted assets and AI.
Talk about bitcoin: Don't just look at market sentiment.
Gensler states that markets tend to fluctuate significantly before basics, particularly in the area of bitcoin and, more broadly, digital assets. He said that investment decision-making should not be based on speculation and short-term excitement, but should go back to whether the assets themselves had a real purpose and whether the long-term value drivers were in place.
In his interview, he stressed the need for investors to be alert to “emotional trading only”. This statement perpetuates his consistent cautious attitude towards the high volatility and speculative climate of the encrypted market.
AI investments are warming, and revenue remains to be validated
Turning to artificial intelligence, Gensler argued that AI was one of the most transformative technologies of the time, but that current market expectations of AI might have been ahead of actual results.
He compared this round of AI heat with past technological revolutions, arguing that capital is usually invested in infrastructure on an early, large-scale basis, and then the market reassesss whether these inputs can be translated into real returns. According to him, this year's financial flows to AI infrastructure are expected to be about $750 billion, almost three times as high as two years ago.
In his view, the current AI transaction is in fact based on two levels of judgement: whether the head of a business like OpenAI and a large cloud service provider can prove that they have a significant income; and whether the landing application of AI can increase productivity in a broader economic activity, thereby supporting current large capital spending.
Regulation and exit pressure or volatility
Gensler also mentioned that as the AI system raises more concerns about privacy, bias, accuracy and transparency in algorithm decision-making, the regulatory pressures that Governments may face in the future may increase.
At the market level, he indicated that some AI companies with high valuations but limited profitability were not easily priced. If early investors, including windfall investors and sovereign wealth funds, begin to phase out of the hold, the market may face a more pronounced push.
He added that newly listed companies and AI enterprises still in the private sector might be more vulnerable to the realization of such funds. At the same time, regulatory environment change and global competition may also continue to increase industry volatility.