Countdown to the AI Bull Market? Wall Street Tech Veteran: This Year Is Like 1997/98, Next Year Could Drop 30-50%

marsbitPublished on 2026-05-13Last updated on 2026-05-13

Abstract

"AI Bull Market Countdown? Wall Street Veteran: This Year Feels Like 1997/98, Next Year Could Drop 30-50%" In an interview, veteran tech analyst Dan Niles draws parallels between the current AI boom and the 1997-98 period of the internet boom, suggesting the bull run isn't over yet. The core new driver is identified as "Agentic AI," which performs multi-step tasks and consumes vastly more computing power than conversational AI. This shift is expected to boost demand for cloud infrastructure and benefit CPU makers like Intel and AMD, potentially pressuring GPU leader Nvidia. However, Niles warns of significant short-term overbought conditions in semiconductors. His central warning is for a potential major market correction of 30-50% starting in early 2027. Drivers include a slowdown from high growth comparables, the outsized capital demands of companies like OpenAI, and a wave of massive tech IPOs sucking liquidity from the market. A J.P. Morgan survey of 56 global investors aligns with this view, finding that 54% expect a >30% U.S. stock correction by 2027. Among mega-cap tech, Niles favors Google due to its full-stack AI capabilities and cash flow, expresses concern about Meta's user growth, and sees potential for Apple's AI Siri and foldable iPhone. Niles advises investors to be nimble, hold significant cash, and closely monitor the conflicting signals from equities, oil prices, and bond yields, which he believes cannot all be correct simultaneously.

Original Author: Long Yue

Original Source: Wall Street News

The current market situation is strikingly similar to 1997-1998—a Wall Street tech veteran is already starting the countdown for the AI bull market.

On May 11, Dan Niles, a well-known chip analyst from the dot-com bubble era and founder of Niles Investment Management, gave an in-depth interview on "The Master Investor Podcast," systematically presenting his judgment on the current AI market trend: the AI bull market is not over yet, but he predicts a major correction could occur around early 2027, and investors should start preparing now.

Meanwhile, a JPMorgan survey of 56 global investors found: 54% expect the U.S. stock market to experience a correction of over 30% this year or next, with 45% believing it will happen in 2027—highly aligning with Dan Niles' assessment.

It's 1997-1998, Not 1999, and Certainly Not 2000

Niles compares the current market to 1997-1998, not the peak bubble years of 1999-2000 that many fear.

The logic is as follows: ChatGPT launched at the end of 2022, and AI infrastructure build-out is now entering its fourth year. During the internet era, the Netscape browser debuted in 1994, and 1997-1998 was also the third and fourth years.

In 1997, the Thai currency crisis erupted, the S&P 500 fell up to 11% intra-year but still closed the year up 31%. In 1998, the Russian bond default and Long-Term Capital Management (LTCM) collapse saw the S&P 500 drop up to 19% intra-year, yet it still gained 27% for the full year.

Niles says: "Back then, the overarching theme of internet infrastructure build-out provided a cushion, so every macro shock became a buying opportunity. It's the same today."

He believes the oil price shock triggered by the Iran war is a "man-made event," easier to resolve than the currency crisis or bond defaults of the past, therefore judging this to be another cyclical low.

Agentic AI: The New Fuel Driving This Bull Market Forward

Niles attributes the core driver of this year's market to one term: Agentic AI.

Simply put, previously you would ask ChatGPT a question, and it would give you an answer. This is "conversational AI."

Agentic AI is fundamentally different. Dan Niles gives an example: "You can tell it, 'This is Wilfred, go to the BBC website and get this data, go to Bloomberg for that data, go to CNBC for something else, then compile it all into an Excel spreadsheet.'" This series of operations requires numerous concurrent API calls, consuming 10 to 100 times more compute tokens than a chat-based AI.

Data already proves this: For the two months before OpenAI's release of [presumably a key Agentic AI model/API] on January 30, 2026, token growth was about 20%; in the two months after release, token growth exceeded 120%.

This has directly boosted capital expenditure expectations for hyperscale cloud providers: at the start of the year, the market expected ~30% capex growth for 2026; after Q1 earnings, this rose to 60%; and after the latest round of earnings, it climbed again to 70%.

Niles' conclusion: This is not a small change; it's an order-of-magnitude leap, sufficient to support further gains in AI-related stocks.

Changing Hardware Landscape: CPU Comeback, GPU Under Pressure

The architectural nature of Agentic AI is quietly rewriting the competitive landscape of AI hardware.

Training large models involves repeating the same task, which GPUs excel at; conversational AI inference is also manageable. But Agentic AI requires simultaneously managing multiple applications and coordinating multi-step tasks, which is essentially "orchestration"—a CPU's strong suit.

Dan Niles says: "The ratio used to be roughly 8 GPUs to 1 CPU. As we shift to Agentic, that ratio will move closer to 1 to 1."

This means: Intel and AMD benefit, while Nvidia is "marginally affected in terms of its stock price performance."

But Semiconductors Are Severely Overbought

Dan Niles shifts gears: short-term risks cannot be ignored. "In the short term, the current overbought level in semiconductors is the most severe since just before the 2000 or 1995 crashes. That's certain."

He specifically notes the semiconductor ETF is up about 70% year-to-date, and even the Iran war shock couldn't push it down.

However, he stresses that short-term overbought conditions do not equate to a breakdown in long-term logic—the demand for compute from Agentic AI is real. He is willing to accept the risk of Intel potentially falling 15-20% in the short term because he believes the stock will be even higher by year-end.

2027: Where Will the 30-50% Correction Come From?

Dan Niles is already mapping out scenarios for the next cycle.

The Agentic AI surge began around January 30, 2026. Based on this, by early 2027, growth will start lapping tough high-base comparisons, and growth rates will naturally slow significantly. At that point, what happens to the market?

"I think, from the highs they are at then, these stocks could drop 30% to 50%," he says.

The reference point is recent: in 2022, the "Magnificent 7" tech giants fell an average of 46%—that was just the aftermath of the pandemic-era tech build-out wave receding, far smaller in scale than the current AI frenzy.

Another potential trigger point is OpenAI. Dan Niles points out that OpenAI and Anthropic combined account for about half of the backlog orders at hyperscale cloud vendors. The two companies went from a combined ~$7 billion in annualized revenue in early 2025 to now approaching $70 billion (Anthropic ~$45B, OpenAI ~$24B)—an astonishing growth, but this money must be squeezed out of other companies' budgets.

"When OpenAI's revenue was still $20 billion at year-end, it publicly claimed a commitment of $1.4 trillion in capital expenditure over the next eight years. Where does that money come from? If OpenAI runs into problems, that would significantly accelerate this process."

He also highlights a structural liquidity pressure: IPOs from companies like OpenAI, SpaceX, and Anthropic are coming in succession, each potentially valued in the trillions of dollars. "That money has to come from somewhere else. Fund managers aren't sitting on piles of idle cash; they have to sell something else."

Three Signals Flashing Simultaneously: Stocks, Oil, Bonds—One Must Be Wrong

The first thing Dan Niles does every morning is check oil prices, bond yields, and the stock market simultaneously.

The current combination makes him uneasy: stocks at all-time highs, oil prices up about 60% year-to-date, and both the U.S. 10-year and 30-year Treasury yields hitting yearly highs.

Historically, in 10 out of the past 12 recessions, a sustained rise in oil prices preceded them. If oil stays around $90 for one or two quarters, inflation will pick up, consumer purchasing power will be eroded, and then a major stock market correction becomes inevitable. McDonald's recent earnings mentioned pressure on low-end consumers, with same-store sales missing expectations—when these signals start appearing, you have to worry.

He also notes that the incoming Fed Chair Kevin Warsh is inclined to cut rates and views AI as a deflationary force, "which is a positive factor pushing the market higher in the short term." But he warns that if 10-year or 30-year yields keep climbing, market valuations will face real pressure. His conclusion:

Among stocks, oil, and bonds, one must be wrong. When one of them reprices, it could trigger significant market turmoil.

His advice is concise: "Hold lots of cash now.—Just at the end of March, I thought it was a good time to be aggressive entering the market. But now, I think you should hold lots of cash and be highly vigilant about the eventual resolution."

JPMorgan: 54% of Institutional Investors Expect a Major Correction in 2027

Dan Niles' warning is not an isolated view.

A roadshow feedback report released on May 12, 2026, by JPMorgan's global market strategy team shows that analyst Eduardo Lecubarri led the team to five cities in Latin America, meeting with 56 institutional investors.

The core data from the report is as follows:

  • 92% of surveyed investors believe the stock market return for the full year 2026 will be positive, but not a single one expects gains exceeding 20%;
  • 54% of surveyed investors expect a stock market correction of over 30% sometime between 2026 and 2027 (9% expecting it in 2026, 45% in 2027);
  • 75% of surveyed investors believe there is more than 20% upside remaining before reaching a tech bubble peak;
  • Regarding regional allocation, views on Europe were highly consistent—100% underweight Europe, 100% overweight the U.S.;
  • The sectors most favored by investors are, in order: Technology, Utilities, Industrials.

This highly aligns with Dan Niles' "1998 logic": the bull market is far from over, but the timeline for a major correction is already quietly forming within market consensus.

Quantum Computing: Huge Potential, But Don't Rush

At the end of the interview, Dan Niles also discussed quantum computing. He is a firm long-term believer: "I'm a firm believer in quantum; I think we will get there eventually"—but he cites Bill Gates' famous quote: We tend to overestimate technology in the short term and underestimate it in the long term.

"The earliest AI paper was written over 50 years ago. When did ChatGPT appear? End of 2022. Quantum computing likely follows a similar path. The arrival of quantum computing IPOs will bring back market attention, but truly disruptive applications will take longer to arrive than most people imagine."

Big Tech Company Divergence: Google Out in Front

The recent earnings from tech giants have made Dan Niles' judgment clearer.

Google Cloud: Q4 YoY growth 48%, latest quarter accelerated to 63%, a 15 percentage point acceleration.

AWS: Accelerated from 24% to 28%, a 4 percentage point increase—respectable given its size as the largest cloud provider.

Microsoft Cloud: From 38% to 39%, almost flat.

"These numbers tell you who is truly executing and who is gaining market share," Dan Niles says.

He states his conclusion directly: "Who is the best big tech company to own for the next 3 to 5 years? Clearly Google. They have the full technology stack; you should bet on them. Unless something dramatic happens, they will continue to be winners because they have everything and have massive cash flow to support it."

Google's advantages include: its own large language model Gemini, in-house AI chips (over a decade of history, the longest among the three cloud vendors), strong cash flow supported by its ad business, and the Android ecosystem covering over 75% of global smartphones. Microsoft relies on OpenAI and lacks its own foundational model; Amazon's AI products have limited brand recognition.

Meta's situation is relatively concerning. Dan Niles points out Meta has no public cloud, so it can't sell excess compute to external businesses; its in-house ASIC chip development also started relatively late. More importantly, this quarter Meta saw the first-ever quarterly decline in Family of Apps user numbers—between the two growth engines for its ad monetization model (user count and price per user), the former has now turned, "That is something to worry about."

Regarding Apple, Dan Niles believes the AI-powered Siri and the foldable iPhone will drive a replacement cycle—citing the iPhone 6 as an example: screen size increased from 4 to 5.5 inches, pushing Apple's revenue growth from 7% to 28%.

Stay Nimble, Don't Be Greedy

Dan Niles summarizes his market philosophy in one phrase: "Be Nimble. Hold strong convictions, but hold them loosely."

His assessment framework is: short-term momentum is upward, with Agentic AI and expectations of easier monetary policy still being two key engines; but by early 2027, these growth numbers will start lapping tough comparisons, the explosive growth from Agentic AI will enter a more moderate phase, and combined with the potential risks from OpenAI and the liquidity shock from mega-IPOs, "stock prices could drop 30% to 50% from the highs at that time."

What to do now? Hold more cash, keep a close eye on the three coordinates every morning—oil prices, Treasury yields, and the stock market—and be ready to adjust at any moment.

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Related Questions

QAccording to Dan Niles, why is the current AI boom period analogous to 1997-1998 rather than the bubble peak of 1999-2000?

ADan Niles compares the current period to 1997-1998 because, similar to the internet boom where Netscape launched in 1994, we are now in the 3rd/4th year of AI infrastructure build-out following ChatGPT's 2022 launch. He argues that, like in 1997-1998, macroeconomic shocks during this phase of foundational investment present buying opportunities rather than signaling the end of the cycle.

QWhat is Agentic AI and how does it differ from the previous generation of AI, according to the article?

AAgentic AI differs from conversational AI (like ChatGPT) by being capable of performing multi-step, coordinated tasks across different applications based on a single instruction. For example, it can gather data from BBC, Bloomberg, and CNBC, then compile it into an Excel spreadsheet. This requires significantly more concurrent processing, consuming 10 to 100 times more compute tokens than simple chat-based AI.

QHow does Dan Niles expect the rise of Agentic AI to shift the competitive landscape among major hardware companies like Intel, AMD, and Nvidia?

ADan Niles expects Agentic AI to benefit CPU makers like Intel and AMD at the relative expense of GPU leader Nvidia. He explains that while GPUs excel at repetitive tasks like model training, the 'orchestration' of multiple concurrent tasks in Agentic AI is a CPU strength. He predicts the hardware ratio in AI systems will shift from roughly 8 GPUs per 1 CPU toward a 1-to-1 ratio.

QWhat major market risk does Dan Niles predict for around early 2027, and what are two key factors he cites that could trigger it?

ADan Niles predicts a potential market correction of 30-50% around early 2027. Two key triggering factors he cites are: 1) The year-over-year growth rates for AI companies will start to compare against the high base established by the Agentic AI boom that began in early 2026, leading to a natural slowdown. 2) Potential risks from companies like OpenAI, whose massive capital expenditure plans and growth depend on budgets being reallocated from other areas, and a wave of multi-trillion dollar IPOs (e.g., OpenAI, SpaceX) that could drain liquidity from the broader market.

QBased on the recent earnings reports of major cloud providers, which company does Dan Niles identify as the best-positioned 'big tech' company for the next 3-5 years, and why?

ADan Niles identifies Google (Alphabet) as the best-positioned big tech company. He points to Google Cloud's accelerating revenue growth (from 48% to 63% YoY), its complete, in-house technology stack (including the Gemini LLM and over a decade of in-house AI chip development), massive cash flow from its advertising business, and the global reach of its Android ecosystem. In contrast, he notes Microsoft's reliance on OpenAI and Amazon's lower-profile AI products as relative weaknesses.

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How Does SPERO,$$s$ Work? SPERO,$$s$ employs a multi-faceted framework that distinguishes it from conventional cryptocurrency projects. Here are some of the key features that underline its uniqueness and innovation: Decentralised Governance: SPERO,$$s$ integrates decentralised governance models, empowering users to participate actively in decision-making processes regarding the project’s future. This approach fosters a sense of ownership and accountability among community members. Token Utility: SPERO,$$s$ utilises its own cryptocurrency token, designed to serve various functions within the ecosystem. These tokens enable transactions, rewards, and the facilitation of services offered on the platform, enhancing overall engagement and utility. Layered Architecture: The technical architecture of SPERO,$$s$ supports modularity and scalability, allowing for seamless integration of additional features and applications as the project evolves. This adaptability is paramount for sustaining relevance in the ever-changing crypto landscape. Community Engagement: The project emphasises community-driven initiatives, employing mechanisms that incentivise collaboration and feedback. By nurturing a strong community, SPERO,$$s$ can better address user needs and adapt to market trends. Focus on Inclusion: By offering low transaction fees and user-friendly interfaces, SPERO,$$s$ aims to attract a diverse user base, including individuals who may not previously have engaged in the crypto space. This commitment to inclusion aligns with its overarching mission of empowerment through accessibility. Timeline of SPERO,$$s$ Understanding a project's history provides crucial insights into its development trajectory and milestones. Below is a suggested timeline mapping significant events in the evolution of SPERO,$$s$: Conceptualisation and Ideation Phase: The initial ideas forming the basis of SPERO,$$s$ were conceived, aligning closely with the principles of decentralisation and community focus within the blockchain industry. Launch of Project Whitepaper: Following the conceptual phase, a comprehensive whitepaper detailing the vision, goals, and technological infrastructure of SPERO,$$s$ was released to garner community interest and feedback. Community Building and Early Engagements: Active outreach efforts were made to build a community of early adopters and potential investors, facilitating discussions around the project’s goals and garnering support. Token Generation Event: SPERO,$$s$ conducted a token generation event (TGE) to distribute its native tokens to early supporters and establish initial liquidity within the ecosystem. Launch of Initial dApp: The first decentralised application (dApp) associated with SPERO,$$s$ went live, allowing users to engage with the platform's core functionalities. Ongoing Development and Partnerships: Continuous updates and enhancements to the project's offerings, including strategic partnerships with other players in the blockchain space, have shaped SPERO,$$s$ into a competitive and evolving player in the crypto market. Conclusion SPERO,$$s$ stands as a testament to the potential of web3 and cryptocurrency to revolutionise financial systems and empower individuals. With a commitment to decentralised governance, community engagement, and innovatively designed functionalities, it paves the way toward a more inclusive financial landscape. As with any investment in the rapidly evolving crypto space, potential investors and users are encouraged to research thoroughly and engage thoughtfully with the ongoing developments within SPERO,$$s$. The project showcases the innovative spirit of the crypto industry, inviting further exploration into its myriad possibilities. While the journey of SPERO,$$s$ is still unfolding, its foundational principles may indeed influence the future of how we interact with technology, finance, and each other in interconnected digital ecosystems.

156 Total ViewsPublished 2024.12.17Updated 2024.12.17

What is $S$

What is AGENT S

Agent S: The Future of Autonomous Interaction in Web3 Introduction In the ever-evolving landscape of Web3 and cryptocurrency, innovations are constantly redefining how individuals interact with digital platforms. One such pioneering project, Agent S, promises to revolutionise human-computer interaction through its open agentic framework. By paving the way for autonomous interactions, Agent S aims to simplify complex tasks, offering transformative applications in artificial intelligence (AI). This detailed exploration will delve into the project's intricacies, its unique features, and the implications for the cryptocurrency domain. What is Agent S? Agent S stands as a groundbreaking open agentic framework, specifically designed to tackle three fundamental challenges in the automation of computer tasks: Acquiring Domain-Specific Knowledge: The framework intelligently learns from various external knowledge sources and internal experiences. This dual approach empowers it to build a rich repository of domain-specific knowledge, enhancing its performance in task execution. Planning Over Long Task Horizons: Agent S employs experience-augmented hierarchical planning, a strategic approach that facilitates efficient breakdown and execution of intricate tasks. This feature significantly enhances its ability to manage multiple subtasks efficiently and effectively. Handling Dynamic, Non-Uniform Interfaces: The project introduces the Agent-Computer Interface (ACI), an innovative solution that enhances the interaction between agents and users. Utilizing Multimodal Large Language Models (MLLMs), Agent S can navigate and manipulate diverse graphical user interfaces seamlessly. Through these pioneering features, Agent S provides a robust framework that addresses the complexities involved in automating human interaction with machines, setting the stage for myriad applications in AI and beyond. Who is the Creator of Agent S? While the concept of Agent S is fundamentally innovative, specific information about its creator remains elusive. The creator is currently unknown, which highlights either the nascent stage of the project or the strategic choice to keep founding members under wraps. Regardless of anonymity, the focus remains on the framework's capabilities and potential. Who are the Investors of Agent S? As Agent S is relatively new in the cryptographic ecosystem, detailed information regarding its investors and financial backers is not explicitly documented. The lack of publicly available insights into the investment foundations or organisations supporting the project raises questions about its funding structure and development roadmap. Understanding the backing is crucial for gauging the project's sustainability and potential market impact. How Does Agent S Work? At the core of Agent S lies cutting-edge technology that enables it to function effectively in diverse settings. Its operational model is built around several key features: Human-like Computer Interaction: The framework offers advanced AI planning, striving to make interactions with computers more intuitive. By mimicking human behaviour in tasks execution, it promises to elevate user experiences. Narrative Memory: Employed to leverage high-level experiences, Agent S utilises narrative memory to keep track of task histories, thereby enhancing its decision-making processes. Episodic Memory: This feature provides users with step-by-step guidance, allowing the framework to offer contextual support as tasks unfold. Support for OpenACI: With the ability to run locally, Agent S allows users to maintain control over their interactions and workflows, aligning with the decentralised ethos of Web3. Easy Integration with External APIs: Its versatility and compatibility with various AI platforms ensure that Agent S can fit seamlessly into existing technological ecosystems, making it an appealing choice for developers and organisations. These functionalities collectively contribute to Agent S's unique position within the crypto space, as it automates complex, multi-step tasks with minimal human intervention. As the project evolves, its potential applications in Web3 could redefine how digital interactions unfold. Timeline of Agent S The development and milestones of Agent S can be encapsulated in a timeline that highlights its significant events: September 27, 2024: The concept of Agent S was launched in a comprehensive research paper titled “An Open Agentic Framework that Uses Computers Like a Human,” showcasing the groundwork for the project. October 10, 2024: The research paper was made publicly available on arXiv, offering an in-depth exploration of the framework and its performance evaluation based on the OSWorld benchmark. October 12, 2024: A video presentation was released, providing a visual insight into the capabilities and features of Agent S, further engaging potential users and investors. These markers in the timeline not only illustrate the progress of Agent S but also indicate its commitment to transparency and community engagement. Key Points About Agent S As the Agent S framework continues to evolve, several key attributes stand out, underscoring its innovative nature and potential: Innovative Framework: Designed to provide an intuitive use of computers akin to human interaction, Agent S brings a novel approach to task automation. Autonomous Interaction: The ability to interact autonomously with computers through GUI signifies a leap towards more intelligent and efficient computing solutions. Complex Task Automation: With its robust methodology, it can automate complex, multi-step tasks, making processes faster and less error-prone. Continuous Improvement: The learning mechanisms enable Agent S to improve from past experiences, continually enhancing its performance and efficacy. Versatility: Its adaptability across different operating environments like OSWorld and WindowsAgentArena ensures that it can serve a broad range of applications. As Agent S positions itself in the Web3 and crypto landscape, its potential to enhance interaction capabilities and automate processes signifies a significant advancement in AI technologies. Through its innovative framework, Agent S exemplifies the future of digital interactions, promising a more seamless and efficient experience for users across various industries. Conclusion Agent S represents a bold leap forward in the marriage of AI and Web3, with the capacity to redefine how we interact with technology. While still in its early stages, the possibilities for its application are vast and compelling. Through its comprehensive framework addressing critical challenges, Agent S aims to bring autonomous interactions to the forefront of the digital experience. As we move deeper into the realms of cryptocurrency and decentralisation, projects like Agent S will undoubtedly play a crucial role in shaping the future of technology and human-computer collaboration.

824 Total ViewsPublished 2025.01.14Updated 2025.01.14

What is AGENT S

Discussions

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