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At a conference in Taipei early Monday, Nvidia (NVDA) CEO Jensen Huang said the company will drop a super PC chip in the fall that takes aim at Intel (INTC) and AMD (AMD). Huang attaching the word “super” to a new product is akin to dumping lighter fluid on an open flame.
The news sent shares of tech players Arm Holdings (ARM), IBM (IBM), Hewlett-Packard Enterprise (HPE), and ServiceNow (NOW) ripping higher like a giant fireball.
IBM stock was even up 10% at one point in the week after a resurfaced video of President Trump praising CEO Arvind Krishna was perceived as new by the AI bulls.
But what Huang said about the potential of artificial intelligence is what the AI bulls lapped up. I won’t say these were new thoughts from the always-bullish Huang. They were more like updates to prior upbeat comments that arrive at an important moment for tech investors.
“Every company will have agents running inside,” Huang said. “Every company will see that agents will need its own operating system. Every company is asking us, ‘How do we run agents safely? How do we build agents for our own workloads?’ There are going to be so many agents. The world is no longer limited by the number of people. Those agents are going to use more tools than ever.”
Mania fuel!
This was just Monday morning.
Monday evening brought whopper AI news from Hewlett-Packard Enterprise.
A few days removed from Dell’s (DELL) stock exploding 32.6% following a monster quarter and guidance, Hewlett Packard Enterprise experienced the same market reaction.
Hewlett Packard Enterprise’s stock rose 16% on Tuesday following much better-than-expected results and upbeat guidance amid the AI infrastructure boom. HPE CEO Antonio Neri told me he is so confident in the AI demand outlook that he was OK issuing 2027 guidance — in June.
“There is real demand,” Neri said, pushing back on the narrative that we are headed toward a dot-com era crash. Neri said he doesn’t see any AI demand peak on the horizon.
Chuck Robbins, CEO of Cisco (CSCO) — a competitor to HPE — sounded just as upbeat in our chat a few weeks ago when a big quarter at Cisco sent that stock skyrocketing.
I heard zero tone change when I spoke with Snowflake (SNOW) CEO Sridhar Ramaswamy at the company’s annual partner conference in San Francisco. This was a few days removed from Snowflake stock exploding by more than 30% the day after its earnings report.
Now to the research
Artificial intelligence has emerged as the defining technological force of the twenty first century. Governments are reshaping national strategies around it. Businesses are redesigning operating models to harness it. Investors are directing unprecedented levels of capital toward AI related ventures. Universities are revising academic curricula to prepare future generations, while professionals across industries are rethinking the nature of work itself. The pace of innovation and the scale of public attention have elevated AI from a specialized field of computer science to a central topic of global economic and social discourse. Against this backdrop, one question has become increasingly relevant.
How long will AI mania last
The answer depends largely on what is meant by the word mania. If it refers to the extraordinary wave of public enthusiasm, speculative investment, soaring market valuations, and expectations that sometimes exceed technological reality, history suggests that such periods are rarely permanent. If, however, it refers to the long term integration of artificial intelligence into the global economy, scientific research, industry, and everyday life, then the transformation is likely to extend well beyond the current decade. Distinguishing between temporary market excitement and enduring technological progress is essential for investors, policymakers, business leaders, educators, and citizens seeking to make informed decisions.
Lessons from Technological History
History offers a consistent lesson. Nearly every revolutionary technology has experienced an initial period of intense optimism followed by a phase of adjustment before becoming an indispensable part of society.
The railway expansion of the nineteenth century attracted enormous investment and speculative activity before financial corrections reshaped the industry. Electricity inspired widespread excitement before quietly becoming the invisible foundation of modern civilization. The internet experienced the dramatic Dot Com Bubble around the turn of the millennium, during which countless companies disappeared after market valuations proved unsustainable. Yet the internet itself went on to redefine commerce, communication, education, and culture. Smartphones followed a comparable trajectory, evolving from luxury devices into essential tools used by billions of people every day.
Artificial intelligence appears to be following this familiar historical pattern. Market enthusiasm may fluctuate over time, but the underlying technology is steadily becoming embedded in the infrastructure of the global economy.
Why AI Excitement Is Different
Unlike many previous waves of technological enthusiasm, artificial intelligence is already producing measurable value across a wide range of industries. The technology is no longer confined to laboratories or experimental projects. It is increasingly integrated into real world operations and decision making.
Healthcare systems are using AI to assist with medical imaging, accelerate drug discovery, predict disease risks, and support clinical decision making. Financial institutions employ AI to strengthen fraud detection, enhance risk assessment, improve anti money laundering systems, and streamline customer service. Manufacturers are adopting AI driven predictive maintenance, robotics, and automated quality control to improve efficiency. Agriculture is benefiting from precision farming, crop monitoring, and weather based decision support. Educational institutions are incorporating AI assisted tutoring and adaptive learning systems, while scientific researchers rely on AI to analyze complex datasets and accelerate discovery.
These practical applications distinguish artificial intelligence from technologies that remain largely speculative. Its economic relevance is already evident across multiple sectors.
The Economic Reality
Economic institutions increasingly view artificial intelligence as a major driver of future growth, although the precise magnitude remains uncertain.
Goldman Sachs has estimated that widespread adoption of generative AI could increase global gross domestic product by approximately seven percent over a decade under certain economic scenarios. McKinsey Global Institute has projected that generative AI could contribute between 2.6 trillion and 4.4 trillion United States dollars in annual economic value by enhancing productivity and creating new sources of growth. PwC has estimated that artificial intelligence could add as much as 15.7 trillion United States dollars to the global economy by 2030 through improvements in productivity and increased consumer demand.
These projections should be interpreted carefully. They represent scenario based estimates built upon assumptions regarding technological progress, regulatory developments, workforce adaptation, investment patterns, and rates of adoption. They illustrate AI’s potential rather than guarantee future outcomes.
Why Some Experts Warn About a Bubble
Despite AI’s remarkable promise, many economists and market analysts caution that excessive optimism can create financial imbalances.
Some technology companies are valued on the basis of exceptionally ambitious expectations for future earnings. Numerous AI startups continue to operate without clearly established pathways to long term profitability. Investment in advanced semiconductor manufacturing, data centers, cloud infrastructure, and electricity generation has expanded at an extraordinary pace, raising legitimate questions about future returns. In some cases, organizations are adopting AI technologies without clearly defined commercial objectives, motivated more by competitive pressure than measurable business value.
History repeatedly demonstrates that when expectations become disconnected from underlying economic fundamentals, market corrections often follow. Such corrections, however, should not necessarily be interpreted as evidence that the underlying technology lacks long term value.
The Productivity Challenge
A central question facing economists is whether artificial intelligence will generate productivity gains at the scale currently anticipated.
Previous technological revolutions often required years, or even decades, before their full economic benefits became visible in national productivity statistics. Economist Robert Solow famously observed in 1987 that computers seemed to appear everywhere except in the productivity data. Over time, digital technologies fundamentally transformed business operations and economic performance.
Artificial intelligence may follow a similar trajectory. Its most significant economic contributions may emerge gradually as organizations redesign workflows, acquire new skills, and integrate AI into broader operational systems rather than through immediate productivity gains alone.
Regulation Will Shape the Future
The future development of artificial intelligence will be influenced not only by technological innovation but also by public policy and regulatory frameworks.
The European Union has adopted the AI Act, one of the world’s first comprehensive legal frameworks governing artificial intelligence. The United States continues to develop a combination of sector specific oversight and executive guidance, while China has introduced regulations addressing generative AI services and algorithmic recommendation systems. Many other countries are developing national AI strategies designed to balance innovation with public safety, privacy protection, cybersecurity, intellectual property rights, and ethical considerations.
Well designed regulation may slow certain applications in the short term, but it can also strengthen public confidence and create conditions for more sustainable and responsible innovation.
The Workforce Question
Perhaps no aspect of artificial intelligence has attracted more public attention than its potential impact on employment.
Research published by organizations including the International Labor Organization, the Organization for Economic Cooperation and Development, and the World Economic Forum suggests that AI is more likely to transform occupations than eliminate work altogether. Routine cognitive tasks may become increasingly automated, while demand for skills such as creativity, critical thinking, emotional intelligence, leadership, and interdisciplinary problem solving is expected to increase.
Throughout history, technological revolutions have displaced certain occupations while creating entirely new industries and career opportunities. The transition, however, may involve significant social and economic challenges, underscoring the importance of lifelong learning and workforce reskilling.
The Infrastructure Constraint
The expansion of artificial intelligence depends on a sophisticated physical and digital infrastructure that extends far beyond software development.
Advanced semiconductors, high performance data centers, reliable electricity supplies, cloud computing capacity, highly skilled engineers, and robust cybersecurity systems all represent critical components of the AI ecosystem. Limitations in any of these areas may naturally slow the pace of AI deployment even if market demand continues to grow rapidly.
Infrastructure constraints therefore remain an important factor shaping the future trajectory of artificial intelligence.
What This Means for Emerging Economies
For emerging economies such as Bangladesh, artificial intelligence presents both significant opportunities and important policy challenges.
AI has the potential to strengthen banking efficiency, expand financial inclusion, improve healthcare delivery, enhance agricultural productivity, modernize education, support disaster management, improve public administration, and increase export competitiveness. Realizing these benefits, however, requires sustained investment in digital infrastructure, human capital, research capacity, cybersecurity, ethical governance, and modern regulatory institutions.
Technology alone cannot deliver long term development. Sustainable progress depends upon building the institutional capacity needed to use AI responsibly and effectively.
A Balanced Outlook
The current wave of enthusiasm surrounding artificial intelligence will almost certainly evolve over time.
The exceptional optimism reflected in financial markets is unlikely to persist indefinitely. Some companies will fail to achieve commercial success. Certain investments will generate disappointing returns. Some technological promises will take considerably longer to materialize than initially expected.
These developments should not be interpreted as evidence that artificial intelligence itself has failed. Rather, they are characteristic of the maturation process that has accompanied nearly every major technological revolution throughout modern history.
Inference
The more meaningful question may not be “How long will AI mania last” but rather “How will societies adapt once artificial intelligence becomes ordinary”
History suggests that public excitement eventually subsides, while transformative technologies quietly become woven into the fabric of everyday life. Artificial intelligence appears more likely to follow the path of electricity, the internet, and smartphones than that of a short lived technological trend. Periods of exuberance may be followed by market corrections, yet the underlying transformation is expected to continue as AI becomes increasingly integrated into commerce, science, healthcare, education, finance, manufacturing, and public services.
The challenge facing governments, businesses, educators, and individuals is therefore not simply to predict when the current excitement will diminish. It is to prepare thoughtfully for a future in which artificial intelligence is no longer regarded as extraordinary, but as an essential and enduring foundation of the global economy.