AI "Is Not a Dot-Com Bubble," Federal Reserve Chair Jerome Powell Says

Federal Reserve Chair Jerome Powell doesn’t think the AI boom is another dotcom bubble. Speaking at a meeting of the Federal Reserve Open Market Committee, he argued that the current wave of artificial intelligence investment is grounded in profit-making firms and real economic activity rather than speculative excess. 

“These companies..actually have business models and profits and that kind of thing,” he said. “So it’s really a different thing” from the dotcom bubble, where investment capital flowed to firms with no clear business models. 

Also, one might note, the AI investments we currently see are not especially large, as a percentage of gross domestic product, compared to investment levels of prior general-purpose technologies such as railroads. 

Technology/Wave	Estimated Peak Investment as % of GDP	Time Period
Railroads	≈6%	Late 19th Century (e.g., 1870s boom)
IT/Dot-com Boom	≈4.6%	Q4 2000 (Peak for private domestic investment in information processing equipment and software)
AI (Current Estimate)	≈1.3%−1.5%	Estimated 2025 (Focus on AI data center capital expenditures)
Telecom	≈1%	≈2000−2001 or 2020 Peak (Specific boom estimates vary)

Also, AI investment levels are far below levels of dot-com era investment. 

The dot-com era investments happened across a wide range of information processing equipment and software categories, while AI investment is much more narrowly focused on high-performance chips and servers, as well as the data centers which house them. 

That doesn’t mean overinvestment is no risk at all. Markets tend to overshoot before correcting, so some “waste” (overinvestment that does not produce a positive outcome)  will happen. 

That might well be a different matter than a general “investment bubble in AI,” though.

Can OpenAI Exceed All Prior Enterprise Software Market Shares?

If OpenAi does manage, by about 2030 or 2031, to earn $100 billion or so in annual revenues, it might at that point be supplying up to a third of all enterprise software revenues, if one attributes its platform and ecosystem revenues to the "enterprise" category.

Some will argue that makes little sense, since ChatGPT right now is consumer oriented. But the analogy is the Microsoft platform, where even consumer revenues are underpinned by enterprise use cases (software licenses are sold to device suppliers, not directly to consumers, even when consumers buy the appliances).

And if OpenAI does reach such lofty (for now) sales figures, it will be on the back of total platform revenues, not just chatbot revenues.

Enterprise IT Segment	2024 Annual Revenue (USD)	Description
IT Services	$1.5 trillion	Includes outsourcing, consulting, operations & maintenance, cloud migration, and cybersecurity .
Enterprise Software	$280–320 billion	Covers CRM, ERP, business intelligence, content management, and supply chain systems .
IT Hardware	~$140 billion	Includes server, storage, and data center equipment .

That would be an unprecedented level of market share, as the global leaders in enterprise software tend to have mid-single-digit market shares. 

Segment	Leading Vendors	Market Share Estimates (2024/2025)
Enterprise Software (total)	Microsoft, SAP, Oracle, Salesforce, IBM	Each holds low to mid-single-digit percent market share globally. Microsoft and SAP are typically top 2 or 3 by revenue .
ERP (Enterprise Resource Planning)	Oracle, SAP, Microsoft	Oracle (6.5%), SAP (6.5%), Top 10 vendors jointly 26.5% market share .
CRM (Customer Relationship Management)	Salesforce, Microsoft, Oracle, SAP, Adobe	Salesforce (26.1%), Microsoft (5.9%), Oracle (4.4%), SAP (3.5%), Adobe (5–6%) .
Cloud Infrastructure Services	Amazon AWS, Microsoft Azure, Google Cloud	AWS (30%), Azure (20%), Google Cloud (12–13%), together >60% global share .
IT Services	Accenture, IBM, Tata Consultancy, Infosys, Cognizant	Each between 2–5% of global services revenue, with significant fragmentation .

OpenAI IPO in 2026?

Reuters reports that OpenAI is considering an initial public offering with a firm valuation of $1trillion as early as 2026. That might make it the largest IPO ever. 

A $1 trillion valuation today implies that investors believe OpenAI is on an accelerated track to be a $50-100 billion revenue company in the near term, with a defensible technology that will allow it to capture a dominant share of the multi-trillion dollar global AI market.

OpenAI's current projected revenue is around $12 billion to $15 billion (annualized for 2025). To reach a $1 trillion valuation at its current revenue, it would need a 66x to 83x revenue multiple.

That implies annual revenue somewhere between$50 billion to $125 billion. 

That also implies that OpenAI maintains triple-digit or very-high double-digit growth rates for five to seven years. 

It also might imply that OpenAI is not just conquering a new software category, but is capturing a significant portion of global information technology spending, including developer tools, cloud services, and enterprise software across multiple industries.

That might seem unrealistic, but would fit the “winner take most” or “winner take all” character of recent internet markets. 

Such a valuation might also imply difficulty for traditional suppliers of enterprise software, as ChatGPT increasingly becomes a functional substitute for many traditional functions and apps. 

Of course, rivals including Anthropic, Google DeepMind, and Meta also are building platforms, distribution networks and developer ecosystems designed to secure long-term dominance in the field. 

You can make your own guess as to the likelihood of OpenAI achieving its goal of supporting its $1 trillion valuation with revenues. 

Why Bitcoin Miners are Pivoting to High-Performance Computing

There is a good reason why many bitcoin mining companies are pivoting to high-performance computing: the revenue per kWh is significantly higher, while doing so also smooths out income performance because there is a shift to recurring service revenue and away from the commodities nature of bitcoin valuation.

AI workloads, particularly for training large language models, command a premium price. Leasing out a megawatt of infrastructure capacity to a creditworthy AI customer can generate revenue significantly higher than using that same MW to mine Bitcoin.

Metric	Bitcoin Mining (Post-Halving)	AI / HPC Hosting (H100/A100 Pods)
Revenue per kWh Equivalent	∼$0.07 to $0.09	∼$0.25 to $0.35
Annual Revenue per MW	∼$613,000 to $788,000	∼$2.2 million to $$3.1 \text{ million}
EBITDA Margin	∼55% to 65%	∼70% to 80%
Revenue Source	Volatile block rewards (Bitcoin price-dependent)	Predictable, multi-year contracts with creditworthy clients

There also are equity valuation implications. Bitcoin Miners typically trade at a valuation multiple of 6x to 12x EV/EBITDA. Leading data center operators (such as Equinix or Digital Realty) trade at multiples of 20x to 25x EV/EBITDA.

Microsoft, OpenAPI Tighten and Loosen Their Relationship

Microsoft's relationship with OpenAI agreement removes some restrictive elements and arguably strengthens the alliance. 

The agreement locks in Microsoft's priority access to OpenAI's technology and massive cloud spending, while granting OpenAI the flexibility and corporate structure it needs to accelerate its growth than it perhaps used to be.  

Microsoft's intellectual property rights to OpenAI's models and products, including those developed post-Artificial General Intelligence, are extended through 2032. 

OpenAI will purchase an incremental $250 billion in Microsoft Azure cloud computing services, confirming Azure as the primary platform for OpenAI's massive compute needs.

But OpenAI gains the ability to work with other partners to jointly develop some products (though API products remain exclusive to Azure), as well as use other cloud providers for non-API products. 

According to the latest agreement between OpenAI and Microsoft, Microsoft holds an investment in OpenAI Group PBC valued at approximately $135 billion, representing roughly 27 percent of the total. 

But the new agreement, while preserving some early features, also allows each firm more flexibility to pursue other relationships. 

OpenAI remains Microsoft’s frontier model partner and Microsoft continues to have exclusive IP rights and Azure API exclusivity until Artificial General Intelligence (AGI).

OpenAI can now jointly develop some products with third parties. 

API products developed with third parties will be exclusive to Azure. Non-API products may be served on any cloud provider.

Microsoft also can now independently pursue AGI alone or in partnership with third parties.

Search and AI Chabot Lines Blurring?

Without question, AI for e-commerce is displacing some amount of shopper activity. For example, AI chatbots seem to be displacing some other sources, most notably perhaps, search. But there are some nuances. 

Anecdotally, I find Google’s AI Overviews to be useful much of the time, so for casual online shopping research, Google search continues to function suitably, without the need to go to an AI engine. 

And that might not be unusual, though many younger users probably prefer using chatbots rather than search for e-commerce-related queries. 

Some 58 percent of consumers prefer to use AI tools instead of traditional search engines in 2025, up from 25 percent in 2023, according to research by Capital One Shopping.

Still, when AI overviews are available, they seem to get used, suggesting that the difference between search and AI chatbots is narrowing and perhaps even merging. 

Perhaps 60 percent of searches now terminate without users clicking through to another website, according to Bain & Company, when AI summaries are present. Shopping queries on ChatGPT doubled in six months from January to June 2025, growing from 7.8 percent  to 9.8 percent of all searches.

The distinction between "AI chatbots" and "search with AI Overviews" is important. Most consumers still use search engines, but those search engines now incorporate AI features, blurring the line between “search” and “AI chatbot” use. 

The data shows that while standalone AI chatbots remain a small fraction of total search activity, AI-generated content within traditional search engines has become dominant in how consumers receive information.

source: McKinsey 

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