Crypto is increasingly being treated as a contrarian trade as institutional money continues to flow toward artificial intelligence and other high-growth technology themes, according to Bitwise chief investment officer Matt Hougan. In a Tuesday market note, he said the sector is no longer the center of investor attention and is instead competing with a crowded set of AI-related opportunities.
Hougan said the crypto market is suffering because it has lost the momentum that once made it a preferred speculative trade. He pointed to the strong performance of the NASDAQ -100 and the surge in AI-linked shares since late 2022, noting that capital has been drawn to companies tied to generative AI, robotics and space technology. Nvidia , a key supplier of AI computing hardware, has risen nearly 1,500% since ChatGPT was released to the public.
In his view, that shift is forcing crypto through a transition from a sentiment-driven trade to one based more on fundamentals. He argued that contrarian positions can produce strong long-term returns, but they usually require patience and discipline because they do not advance in a smooth line. As crypto loses its status as a favored momentum play, investors are paying closer attention to adoption, utility and other basic measures of value.
That change is also visible in the way capital is moving within the market. Hougan said the current cycle differs from earlier downturns because money is not simply concentrating in Bitcoin as a defensive asset. Instead, some investors are rotating into smaller tokens with what they view as stronger underlying profiles, including Hyperliquid, Zcash and Stellar.
The broader market remains under pressure. Crypto prices fell another 5.3% on the day, pushing total market capitalization to about $2.38 trillion, roughly 46% below the October peak. Even so, Hougan suggested that the emergence of selective strength in parts of the market may indicate that the worst of the downturn is passing, rather than deepening further.AI robotics company Figure drew attention in May after posting videos on X showing its humanoid robots carrying out routine tasks, including cleaning a room and sorting packages. The demonstrations renewed debate over how quickly robots and artificial intelligence could displace workers, even as experts caution that full replacement remains distant.
Researchers say the current wave of robotics is best suited to narrow, repetitive work in controlled settings. Oliver Obst, an associate professor of robotics at the University of New South Wales, said physical jobs in structured environments are among the most exposed to automation, while administrative and document-processing roles are increasingly vulnerable to AI software. He argued that humanoid robots are still not efficient enough, or reliable enough, to replace human labor on a broad scale.
Even in settings that appear simple, robots continue to face challenges involving speed, safety, cost, and recovery from unexpected events. Obst noted that most human jobs involve far more variation and judgment than a package-sorting demonstration suggests. He added that the market is moving toward selective automation of specific tasks rather than mass replacement of people by humanoid machines.
Figure’s package-sorting test also underscored the limits of current systems. In one video, a human worker processed more packages than a group of robots that had to rotate out for recharging. The company’s chief executive said it would be the last time a human would outperform the machines, but the episode highlighted that robots still trail workers in flexibility and consistency over changing conditions.
Markus Levin, co-founder of the decentralized data network XYO, said automation tools can match repetitive tasks with greater consistency, but robots still depend on charging, maintenance, supervision, and infrastructure. He said broader human replacement is likely years away because reliability, regulation, safety, and trust remain major obstacles.
Dr. Francisco Cruz Naranjo, a senior lecturer at the same university, said robots are strongest in stable environments such as factories and warehouses, where demand has been rising steadily. He said they remain far less capable in dynamic settings, especially homes and other places where conditions change rapidly.
Both researchers said wider adoption could still bring benefits, including improved safety in hazardous jobs and relief in labor-short sectors. However, they warned that if automation advances too far, economies built around wages and employment may eventually need to change.
